What you need to know

• Dell will reportedly lay off 12,500 employees this week.
• The move is being made to make the tech giant "leaner," according to a memo sent to Dell employees.
• If the estimated job cut figure is accurate, it would mean Dell has cut 24,500 jobs in the past 15 months.

Dell will cut thousands of jobs this week in a move that will reorganize the company's sales team and place a bigger emphasis on AI. While the company has not confirmed the exact figure, reports indicate that Dell will lay off 12,500 people. One former Dell employee, Ian Armstrong, referred to the layoffs as a "bloodbath" on LinkedIn. Armstrong also pointed people to an alumni channel aimed at helping people during the transition. This is only the latest set of massive cuts by the tech giant, which are estimated to total 24,500 over the past 15 months.

"We are getting leaner," said Dell executive Bill Scannell and John Byrne in a memo to employees sent out Monday. "We’re streamlining layers of management and reprioritizing where we invest."

Dell did not confirm how many employees will be laid off this week. A spokesperson said to Bloomberg, "through a reorganization of our go-to-market teams and an ongoing series of actions, we are becoming a leaner company."

When I was still a starry-eyed 20-something living with my then-fiancée, the only way I could stream video on my TV was through its HDMI ports and my laptop. This had served me well for years — and still does, when I’m desperate — but dealing with the setup was cumbersome.

 

Then came the original Chromecast in 2013, and it was a revelation. Suddenly, I had this tiny black stick, shaped like an oversized key, that plugged right into my TV’s HDMI port and let me cast video through the air and onto my 55-inch screen in glorious high definition. And all it cost was $35? Incredible, especially in 2013.

 

It felt like pure magic. It was a basically invisible device that I didn’t even need an app for, and it let me beam music and video to my TV with almost no muss or fuss. I used it to watch Netflix shows and, more than once, to host karaoke parties at my house via YouTube’s vast catalog of karaoke videos.

 

My first Chromecast, photographed for an eBay listing. (It didn’t sell.)

 

Photo: Wes Davis / The Verge

But time doesn’t stand still, even for the Chromecast. Other streaming products that followed offered what Google’s miracle stick did, serving up easy wireless streaming via an HDMI dongle, for just as cheap and with more features. If you wanted more, there was Apple’s fancy and overpowered streaming box. Or you could just use the built-in features of countless smart TVs that themselves used Google’s wireless casting standard.

 

Google served up plenty of revisions of the Chromecast, but in the end, there was simply no place left for it. And now, Google has discontinued it, replacing it with something much more powerful (and expensive).

 

Still, while the market for streaming gadgets has come a long way, there was something great about the original Chromecast’s simplicity. It was nice to not need to keep track of a remote, and I loved that it was hidden behind my TV. The once-great HDMI dongle’s day may be over, but it served me well.

 

Rest easy, Chromecast. You were a very good dongle.

 

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SAN FRANCISCO — A federal judge’s ruling that Google broke the law to maintain a monopoly in search has dealt a blow to one of Big Tech’s main arguments against regulation: that America’s antiquated antitrust laws aren’t flexible enough to address the fast-changing nature of tech innovation.

On Monday, Judge Amit Mehta of the U.S. District Court for the District of Columbia wrote in a 277-page decision that Google had broken Section 2 of the Sherman Act, a law signed into effect by President Benjamin Harrison in 1890.

The ruling was the first major antitrust ruling against a Big Tech company since a federal court ruled against Microsoft in 2000 for maintaining a monopoly through its operating system. Since then, Google and a small handful of other firms have become titans of the internet age, pulling in revenue never before seen in the history of business and touching the lives of billions of people every day. For most of the past 20 years, the U.S. government has encouraged their growth, rarely intervening in acquisitions or launching antitrust lawsuits against them.

That has changed in recent years, as politicians, regulators, smaller competitors and consumers have become more critical of Big Tech’s power. This court case is the first in a series that have been launched against Google, Meta, Amazon and Apple, all of which have pushed back. In its defense in this case, Google argued that the rapid evolution of the internet, including the rise of TikTok and the artificial intelligence boom, meant that the company did not have a monopoly. Even Google competitors and critics who welcomed the government’s lawsuit worried that Washington didn’t have the tools to constrain tech giants.

“The one lesson I take from this is that antitrust law has a lot of flexibility in it. It seems able to accommodate dealing with these large companies,” said Neil Chilson, who previously served as the Federal Trade Commission’s chief technologist and is now head of AI policy at the Abundance Institute, a tech think tank.

For decades, most judges and antitrust experts subscribed to a view of competition law that focused on whether company behavior increased prices for end consumers. Big Tech products like Facebook’s social network, or Google’s Gmail or search engine, didn’t come under scrutiny because they were free for regular people to use. But as the companies acquired competitors, grew rapidly richer and became gatekeepers to the internet, some scholars argued that the consumer price-focused approach to antitrust needed to be revolutionized.

Politicians also began souring on Big Tech as concerns grew in the late 2010s about social media’s impact on polarization and children’s mental health. While lawmakers were previously loath to be seen as anti-tech or anti-innovation, Silicon Valley has more recently become a popular political punching bag for people from both parties.

The investigations into Big Tech began under the Trump administration, as tech CEOs were repeatedly hauled in front of Congress to answer questions on misinformation, competition and alleged bias. Trump’s Justice Department sued Google in October 2020, and the department continued the lawsuit after Biden took power, culminating in last fall’s trial and Monday’s ruling against the company.

Many Big Tech critics were thrilled about Mehta’s decision, suggesting it bodes well for prosecutors in pending Big Tech antitrust cases and bolsters the argument that internet giants are using their dominance to stifle competition in emerging technologies. Nidhi Hegde, interim executive director of the American Economic Liberties Project, a think tank that has advocated for more aggressive antitrust enforcement, called it “a resounding signal that the anti-monopoly movement is here to stay.”

The Justice Department’s antitrust lawsuit against Apple bears some similarities to the Google search case, alleging that the tech giant uses its prominence in smartphones to control app developers. But as with the Google case, much will depend on how the court defines the relevant market — as the tighter iPhone ecosystem or the broader smartphone market in which Apple is one of multiple rivals. Apple has said it would “vigorously defend” itself in the case and has sought to have it dismissed.

The Federal Trade Commission has also filed antitrust lawsuits against Amazon and Meta. The agency is challenging the online retailer over the fees it charges merchants on its marketplace, while it argues in the Meta case that Facebook has quashed competition, especially by buying rivals Instagram and WhatsApp. Both companies have promised spirited defenses and say they aren’t monopolies. (Amazon founder Jeff Bezos owns The Washington Post.)

“This decision generates momentum for those other cases in the coming months,” said Notre Dame Law School Professor Roger Alford, who is consulting for state attorneys general in a second anti-monopoly case against Google, involving its role in the digital advertising market.

But other antitrust experts say Mehta’s decision itself won’t likely have such influence. “Antitrust cases are so case-by-case,” said Sam Weinstein, a professor at Cardozo School of Law and a former Justice Department antitrust lawyer. “What happens in a Google case will have very little bearing on what happens with a Facebook case or an Amazon case.”

Google has already said it would appeal Monday’s ruling to the U.S. Court of Appeals. A ruling from that court could have a more widespread effect on how judges around the country think about antitrust and Big Tech, Weinstein said. “That’s going to be a very important decision.” If Google loses there it could try to get the matter before the Supreme Court.

However Google fares in any appellate court, the judgment will be grounded, like Mehta’s, in the body of antitrust law that has grown up over more than 130 years. U.S. lawmakers have periodically proposed updating legislation to specifically address new internet technologies. Such efforts have never drawn enough backing to pass into law.

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In Arthur C Clarke’s short story The Nine Billion Names of God, a sect of monks in Tibet believes humanity has a divinely inspired purpose: inscribing all the various names of God. Once the list was complete, they thought, he would bring the universe to an end. Having worked at it by hand for centuries, the monks decide to employ some modern technology. Two sceptical engineers arrive in the Himalayas, powerful computers in tow. Instead of 15,000 years to write out all the permutations of God’s name, the job gets done in three months. As the engineers ride ponies down the mountainside, Clarke’s tale ends with one of literature’s most economical final lines: “Overhead, without any fuss, the stars were going out.”

It is an image of the computer as a shortcut to objectivity or ultimate meaning – which also happens to be, at least part of, what now animates the fascination with artificial intelligence. Though the technologies that underpin AI have existed for some time, it’s only since late 2022, with the emergence of OpenAI’s ChatGPT, that the technology that approached intelligence appeared to be much closer. In a 2023 report by Microsoft Canada, president Chris Barry proclaimed that “the era of AI is here, ushering in a transformative wave with potential to touch every facet of our lives”, and that “it is not just a technological advancement; it is a societal shift”. That is among the more level-headed reactions. Artists and writers are panicking that they will be made obsolete, governments are scrambling to catch up and regulate, and academics are debating furiously.

Businesses have been eager to rush aboard the hype train. Some of the world’s largest companies, including Microsoft, Meta and Alphabet, are throwing their full weight behind AI. On top of the billions spent by big tech, funding for AI startups hit nearly $50bn in 2023. At an event at Stanford University in April, OpenAI CEO Sam Altman said he didn’t really care if the company spent $50bn a year on AI. Part of his vision is for a kind of super-assistant, one that would be a “super-competent colleague that knows absolutely everything about my whole life, every email, every conversation I’ve ever had, but doesn’t feel like an extension”.

But there is also a profound belief that AI represents a threat. The philosopher Nick Bostrom is among the most prominent voices asserting that AI poses an existential risk. As he laid out in his 2014 book Superintelligence, if “we build machine brains that surpass human brains in general intelligence … the fate of our species would depend on the actions of the machine super-intelligence.” The classic cautionary tale here is that of an AI system whose only – seemingly inoffensive – goal is making paperclips. According to Bostrom, the system would realise quickly that humans are a barrier to this task, because they might switch off the machine. They might also use up the resources needed for the manufacturing of more paperclips. This is an example of what AI doomers call the “control problem”: the fear that we will lose control of AI because any defences we’ve built into it will be undone by an intelligence that’s millions of steps ahead of us.

Before we do, in fact, cede any more ground to our tech overlords, it’s worth casting your mind back to the mid-1990s and the arrival of the world wide web. That, too, came with profound assertions of a new utopia, a connected world in which borders, difference and privation would end. Today, you would be hard pressed to argue that the internet has been some sort of unproblematic good. The fanciful did come true; we can carry the whole world’s knowledge in our pockets. This just had the rather strange effect of driving people a bit mad, fostering discontent and polarisation, assisting a renewed surge of the far right and destabilising democracy and truth.

It’s not that you should simply resist technology; it can, after all, also have liberating effects. Rather, when big tech comes bearing gifts, you should probably look closely at what’s in the box.

What we call AI at the moment is predominantly focused on large language models, or LLMs. The models are fed massive sets of data – ChatGPT essentially hoovered up the entire public internet – and trained to find patterns in them. Units of meaning, such as words, parts of words and characters, become tokens and are assigned numerical values. The models learn how tokens relate to other tokens and, over time, learn something like context: where a word might appear, in what order, and so on.

That doesn’t sound impressive on its own. But when I recently asked ChatGPT to write a story about a sentient cloud who was sad the sun was out, the results were strikingly human. Not only did the chatbot produce the various components of a children’s fable, it also included a story arc in which, eventually, “Nimbus” the cloud found a corner of the sky and made peace with a sunny day. You might not call the story good, but it would probably entertain my five-year-old nephew.

Robin Zebrowski, professor and chair of cognitive science at Beloit College in Wisconsin, explains the humanity I sensed this way: “The only truly linguistic things we’ve ever encountered are things that have minds. And so when we encounter something that looks like it’s doing language the way we do language, all of our priors get pulled in, and we think: ‘Oh, this is clearly a minded thing.’”

This is why, for decades, the standard test for whether technology was approaching intelligence was the Turing test, named after its creator Alan Turing, the British mathematician and second world war code-breaker. The test involves a human interrogator who poses questions to two unseen subjects – a computer and another human – via text-based messages to determine which is the machine. A number of different people play the roles of interrogator and respondent, and if a sufficient proportion of interviewers is fooled, the machine could be said to exhibit intelligence. ChatGPT can already fool at least some people in some situations.

The science fiction author Arthur C Clarke. Composite: Gemunu Amarasinghe/AP/Guardian design

Such tests reveal how closely tied to language our notions of intelligence are. We tend to think that beings that can “do language” are intelligent: we marvel at dogs that appear to understand more complex commands, or gorillas that can communicate in sign language, precisely because such acts are closer to our mechanism of rendering the world sensible.

But being able to do language without also thinking, feeling, willing or being is probably why writing done by AI chatbots is so lifeless and generic. Because LLMs are essentially looking at massive sets of patterns of data and parsing how they relate to one another, they can often spit out perfectly reasonable-sounding statements that are wrong or nonsensical or just weird. That reduction of language to just collection of data is also why, for example, when I asked ChatGPT to write a bio for me, it told me I was born in India, went to Carleton University and had a degree in journalism – about which it was wrong on all three counts (it was the UK, York University and English). To ChatGPT, it was the shape of the answer, expressed confidently, that was more important than the content, the right pattern mattering more than the right response.

All the same, the idea of LLMs as repositories of meaning that are then recombined does align with some assertions from 20th-century philosophy about the way humans think, experience the world, and create art. The French philosopher Jacques Derrida, building on the work of linguist Ferdinand de Saussure, suggested that meaning was differential – the meaning of each word depends on that of other words. Think of a dictionary: the meaning of words can only ever be explained by other words, which in turn can only ever be explained by other words. What is always missing is some sort of “objective” meaning outside this neverending chain of signification that brings it to a halt. We are instead forever stuck in this loop of difference. Some, like Russian literary scholar Vladimir Propp, theorised that you could break down folklore narratives into constituent structural elements, as per his seminal work, Morphology of the Folktale. Of course, this doesn’t apply to all narratives, but you can see how you might combine units of a story – a starting action, a crisis, a resolution and so on – to then create a story about a sentient cloud.

Today, AI can take previously unconnected, even random things, such as the skyline of Toronto and the style of the impressionists, and join them to create what hasn’t existed before. But there is a sort of discomforting or unnerving implication here. Isn’t that also, in a way, how we think? Raphaël Millière, an assistant professor at Macquarie University in Sydney, says that, for example, we know what a pet is (a creature we keep with us at home) and we also know what a fish is (an animal that swims in large water bodies); we combine those two in a way that keeps some characteristics and discards others to form a novel concept: a pet fish. Newer AI models boast this capacity to amalgamate into the ostensibly new – and it is precisely why they are called “generative.”

Even comparatively sophisticated arguments can be seen to work this way. The problem of theodicy has been a topic of debate among theologians for centuries. It asks: if an absolutely good God is omniscient, omnipotent and omnipresent, how can evil exist when God knows it will happen and can stop it? It radically oversimplifies the theological issue, but theodicy, too, is in some ways a kind of logical puzzle, a pattern of ideas that can be recombined in particular ways. I don’t mean to say that AI can solve our deepest epistemological or philosophical questions, but it does suggest that the line between thinking beings and pattern recognition machines is not quite as hard and bright as we may have hoped.

The sense of there being a thinking thing behind AI chatbots is also driven by the now common wisdom that we don’t know exactly how AI systems work. What’s called the black box problem is often framed in mystical terms – the robots are so far ahead or so alien that they are doing something we can’t comprehend. That is true, but not quite in the way it sounds. New York University professor Leif Weatherby suggests that the models are processing so many permutations of data that it is impossible for a single person to wrap their head around it. The mysticism of AI isn’t a hidden or inscrutable mind behind the curtain; it’s to do with scale and brute power.

Yet, even in that distinction – that AI is able to do language only through computing power – there is still an interesting question of what it means to think. York University professor Kristin Andrews, who researches animal intelligence, suggests that there are lots of cognitive tasks – remembering how to get food, recognising objects or other beings – that animals do without necessarily being self-aware. In that sense, intelligence may well be attributed to AI because it can do what we would usually refer to as cognition. But, as Andrews notes, there’s nothing to suggest that AI has an identity or a will or desires.

So much of what produces will and desire is located in the body, not just in the obvious sense of erotic desire but the more complex relation between an interior subjectivity, our unconscious, and how we move as a body through the world, processing information and reacting to it. Zebrowski suggests there is a case to be made that “the body matters for how we can think and why we think and what we think about”. She adds, “It’s not like you can just take a computer program and stick it in the head of a robot and have an embodied thing.”

Computers might in fact approach what we call thinking, but they don’t dream, or want, or desire, and this matters more than AI’s boosters let on. When we use our intelligence to craft solutions to economic crises or to tackle racism, we do so out of a sense of morality, of obligation to those around us – our cultivated sense that we have a responsibility to make things better in specific, morally significant ways.

Perhaps the model of the computer in Clarke’s story – something that is kind of a shortcut to transcendence or omniscience – is thus the wrong one. Instead, Deep Thought, the computer in Douglas Adams’s The Hitchhiker’s Guide to the Galaxy, might be closer. When asked “the answer to the Ultimate Question of Life, the Universe and Everything”, it of course spits out that famously obtuse answer: “42”.

The absurdity of the answer points to an easily forgotten truth. Life and its meaning can’t be reduced to a simple statement, or to a list of names, just as human thought and feeling can’t be reduced to something articulated by what are ultimately ones and zeros. If you find yourself asking AI about the meaning of life, it isn’t the answer that’s wrong. It’s the question.

This March, I spent two days at the Microsoft headquarters, just outside Seattle. Microsoft is one of the tech incumbents that is most “all in” on AI. To prove just how much, they brought in journalists from around the world to participate in an “innovation campus tour”, which included a dizzying run of talks and demos, meals in the seemingly neverending supply of on-site restaurants, and a couple of nights in the kind of hotel writers usually cannot afford.

We were walked through a research centre, wearing earplugs to block out the drone of a mini field of fans. We attended numerous panels: how teams were integrating AI, how those involved with “responsible AI” are tasked with reining in the technology before it goes awry.

There was lots of chatter about how this work was the future of everything. In one session, the affable Seth Juarez, principal programme manager of AI platforms, spoke of AI as being like moving from a shovel to a tractor: that it will, in his words, “level up humanity”.

Some of the things we saw were genuinely inspiring, such as the presentation by Saqib Shaikh, who is blind and has spent years working on SeeingAI. It’s an app that is getting better and better at labelling objects in a field of view in real time. Point it at a desk with a can and it will say, “A red soda can, on a green desk.” There were other hopeful ideas for how AI could be used: to preserve dying languages, improve the accuracy of scans for tumours, or better predict where to deploy disaster response resources – usually by processing large amounts of data and then recognising and analysing patterns within it.

At the end of a panel at Microsoft on AI research, we were each offered a copy of a book titled AI for Good, detailing more altruistic uses. One of the projects mentioned in the book involved using machine learning to predict where best to put solar panels in India. That’s encouraging stuff, the sort of thing that lets one momentarily feel a hint of relief or hope that, maybe, some things are going to get better. But many of the problems preventing, say, the deployment of solar power in India do not relate to a lack of knowledge. More often, the problems are the lack of resources, the absence of political will, the power of entrenched interests and, more plainly, money.

This is what the utopian vision of the future so often misses: if and when change happens, the questions at play will be about if and how certain technology gets distributed, deployed, taken up. It will be about how governments decide to allocate resources, how the interests of various parties affected will be balanced, how an idea is sold and promulgated, and more. It will, in short, be about political will, resources, and the contest between competing ideologies and interests. The problems facing the world – not just climate breakdown but the housing crisis, the toxic drug crisis, or growing anti-immigrant sentiment – aren’t problems caused by a lack of intelligence or computing power. In some cases, the solutions to these problems are superficially simple. Homelessness, for example, is reduced when there are more and cheaper homes. But the fixes are difficult to implement because of social and political forces, not a lack of insight, thinking, or novelty. In other words, what will hold progress on these issues back will ultimately be what holds everything back: us.

The idea of an exponentially greater intelligence, so favoured by big tech, is a strange sort of fantasy that abstracts out intelligence into a kind of superpower that can only ever increase. In this view, problem-solving is like a capacity on a dial that can simply be turned up and up. To assume this is what’s called “tech solutionism”, a term coined a decade ago by the writer Evgeny Morozov. He was among the first to point to how Silicon Valley tended to see tech as the answer to everything.

Computer pioneer Alan Turing. Composite: Universal Images Group/Getty Images/Guardian design

Some Silicon Valley businessmen have taken tech solutionism to an extreme. It is these AI accelerationists whose ideas are the most terrifying. Marc Andreessen was intimately involved in the creation of the first web browsers and is now a billionaire venture capitalist who has taken up a mission to fight against the “woke mind virus” and generally embrace capitalism and libertarianism. In a screed published last year, titled The Techno-Optimist Manifesto, Andreessen outlined his belief that “there is no material problem – whether created by nature or by technology – that cannot be solved with more technology”. When the historian Rick Perlstein attended a dinner at Andreessen’s $34m home in California, he found a group adamantly opposed to regulation or any kind of constraint on tech (in a tweet at the end of 2023, Andreessen called regulation of AI “the new foundation of totalitarianism”). When Perlstein related the whole experience to a colleague, he “noted a similarity to a student of his who insisted that all the age-old problems historians worried over would soon obviously be solved by better computers, and thus considered the entire humanistic enterprise faintly ridiculous”.

Andreessen’s manifesto also included a section in which he listed off a series of enemies. It included all the usual rightwing bugbears: regulation, know-it-all academics, the constraint on “innovation”, progressives themselves. To the venture capitalist, these are all self-evident evils. Andreessen has been on the board of Facebook/Meta – a company that has allowed mis- and disinformation to wreak havoc on democratic institutions – since 2008. However, he insists, apparently without a trace of irony, that experts are “playing God with everyone else’s lives, with total insulation from the consequences”.

Having spoken to experts, it seems to me as though the promise of AI lies in dealing with sets of data that exist at a scale humans simply cannot operate at. Pattern recognition machines put to use in biology or physics will probably yield fascinating, useful results. AI’s other uses seem more mundane, at least for now: taking financial statements and reconciling figures, transcribing and summarising meetings, triaging emails more efficiently, making it easier to access simple things like travel itineraries.

That isn’t to say AI is some benevolent good, however. An AI model can be trained on billions of data points, but it can’t tell you if any of those things is good, or if it has value to us, and there’s no reason to believe it will. We arrive at moral evaluations not through logical puzzles but through consideration of what is irreducible in us: subjectivity, dignity, interiority, desire – all the things AI doesn’t have.

To say that AI on its own will be able to produce art misunderstands why we turn to the art in the first place. We crave things made by humans because we care about what humans say and feel about their experience of being a person and a body in the world.

There’s also a question of quantity. In dropping the barriers to content creation, AI will also flood the world with dreck. Already, Google is becoming harder to use because the web is being flooded with AI-crafted content designed to get clicks.

Yet it’s also the imbrication of AI into existing systems that is cause for concern. As Damien P Williams, a professor at the University of North Carolina at Charlotte, pointed out to me, training models absorb masses of data based on what is and what has been. It’s thus hard for them to avoid existing biases, of the past and the present. Williams points to how, if asked to reproduce, say, a doctor yelling at a nurse, AI will make the doctor a man and the nurse a woman. Last year, when Google hastily released Gemini, its competitor to other AI chatbots, it produced images of “diverse” Nazis and the US’s founding fathers. These odd mistakes were a ham-fisted attempt to try to pre-empt the problem of bias in the training data. AI relies on what has been, and trying to account for the myriad ways we encounter and respond to the prejudice of the past appears to simply be beyond its ken.

OpenAI CEO Sam Altman. Composite: Carlos Barría/Reuters/Guardian design

The structural problem with bias has existed for some time. Algorithms were already used for things like credit scores, and already AI usage in things like hiring is replicating biases. In both cases, pre-existing racial bias emerged in digital systems. That’s not to say that AI won’t also kill us. More recently, it was revealed that Israel was using a version of AI called Lavender to help it attack targets in Gaza. The system is meant to identify members of Hamas and Palestinian Islamic jihad and then provide their locations as potential targets for airstrikes – including their homes. According to the Israeli Palestinian +972 Magazine, many of these attacks killed civilians.

As such, the threat of AI isn’t really that of a machine or system which offhandedly kills humanity. It’s the assumption that AI is in fact intelligent that causes us to outsource crucial social and political functions to computer software – it’s not just the tech itself which becomes integrated into day-to-day life but also the particular logic and ethos of tech and its libertarian-capitalist ideology.

The question is then: to what ends AI is deployed, in what context, and with what boundaries. “Can AI be used to make cars drive themselves?” is an interesting question. But whether we should allow self-driving cars on the road, under what conditions, embedded in what systems – or indeed, whether we should deprioritise the car altogether – are the more important questions, and they are ones that an AI system cannot answer for us.

Everyone from a tech bro placing his hopes for human advancement on a superhuman intelligence to an army relying on AI software to list targets evinces the same desire for an objective authority figure to which one can turn. When we look to artificial intelligence to make sense of the world – when we ask it questions about reality or history or expect it to represent the world as it is – are we not already bound up in the logic of AI? We are awash with digital detritus, with the cacophony of the present, and in response, we seek out a superhuman assistant to draw out what is true from the morass of the false and the misleading – often to only be misled ourselves when AI gets it wrong.

We are living in a time where truth is unstable, shifting, constantly in contestation. Think of the embrace of conspiracy theories, the rise of the anti-vax movement, or the mainstreaming of racist pseudoscience. Every age has its great loss – for modernism, it was the coherence of the self; for postmodernism, the stability of master narratives – and now, in the 21st century, there is an increasing pressure on the notion of a shared vision of reality.

When the systems that give shape to things start to fade or come into doubt, as has happened to religion, liberalism, democracy and more, one is left looking for a new God. There is something particularly poignant about the desire to ask ChatGPT to tell us something about a world in which it can occasionally feel like nothing is true. To humans awash with a sea of subjectivity, AI represents the transcendent thing: the impossibly logical mind that can tell us the truth.

Lingering at the edges of Clarke’s short story about the Tibetan monks was a similar sense of technology as the thing that lets us exceed our mere mortal constraints. But the result is the end of everything. In turning to technology to make a deeply spiritual, manual, painstaking task more efficient, Clarke’s characters end up erasing the very act of faith that sustained their journey toward transcendence. But here in the real world, perhaps meeting God isn’t the aim. It’s the torture and the ecstasy of the attempt to do so. Artificial intelligence may keep growing in scope, power and capability, but the assumptions underlying our faith in it – that, so to speak, it might bring us closer to God – may only lead us further away.

In 10 or 20 years from now, AI will undoubtedly be more advanced than it is now. Even so, if I’m lucky enough to be around, I’ll step out of my home with my AI assistant whispering in my ear. There will still be cracks in the sidewalk. The city in which I live will still be under construction. Traffic will probably still be a mess, even if the cars drive themselves. Maybe I’ll look around, or look up at the sky, and my AI assistant will tell me something about what I see. But things will still keep moving on only slightly differently than they do now. And the stars? Against what might now seem like so much change, the sky will still be full of them.

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In what’s being described as its biggest change ever, Taco Bell is rolling out artificial intelligence-powered drive-thrus to hundreds of US locations by the end of this year. That means consumers will soon be greeted by a computer, rather than a human employee, when they order at a Taco Bell drive-thru.

The burrito chain has been testing AI drive-thru ordering in 100 stores across 13 states, and is slated to expand the test to “hundreds more,” parent company Yum! Brands said in a press release, per Inc. Taco Bell’s ultimate goal is to implement the technology in all of its restaurant locations.

The latest initiative comes in the wake of McDonald’s AI drive-thru hoopla, which went viral across social media. Back in June, the fast-food giant announced it was ending a test run of its AI drive-thru technology partnership with IBM in more than 100 restaurants nationwide following customer complaints. Several TikTok users shared videos showing the faulty system miscalculating orders (in the case of two customers, who were given 260 Chicken McNuggets much to their anguish) and producing unappetizing food combinations, like ice cream with ketchup and butter.

In a statement to CNBC, McDonald’s said it isn’t ruling out potential AI drive-thru plans in the future: “As we move forward, our work with IBM has given us the confidence that a voice ordering solution for drive-thru will be part of our restaurants’ future. We see tremendous opportunity in advancing our restaurant technology and will continue to evaluate long-term, scalable solutions that will help us make an informed decision on a future voice ordering solution by the end of the year.”

Despite McDonald’s struggles, Taco Bell is sure that it won’t run into similar problems with its AI drive-thru. Yum! Brands’ chief innovation officer Lawrence Kim told CNN that the initial roll out has already led to greater ordering accuracy, happier employees and shorter drive-thru wait times.

“We are confident that we’ve approached this the right way,” Kim told the outlet, adding that it’s taken two years of testing, gathering employee and customer feedback and improving the technology to be successful with the new drive-thrus. CNN noted that Yum! Brands didn’t provide any actual data on the said successes. Yum! Brands did say it now earns $30 billion in sales (about 50% of its total revenue) from digital-first ordering channels.

Yum! Brands also refrained from specifying which technology partners the corporation is working with to make its AI drive-thrus a possibility.

Kim explained that Yum! Brands is strengthening its AI system by training it to understand different pronunciations of certain words and menu items, namely “quesadilla” (“kay-sah-dee-ya” versus “kay-sah-DILL-uh”). He added that Taco Bell employees are still listening on the other end of the drive-thru, so if the AI system struggles to comprehend an order, an employee can jump in and take over.

Kim also addressed the main concern with AI powered technology, saying the ordering system would not replace human jobs. Instead, the AI system will “enhance the team member experience so they can focus on other tasks that are a priority for them,” Kim told CNN.

In addition to Taco Bell, Chipotle, Wingstop and Panera are just a few major chains that have been experimenting with AI in their restaurants nationwide. Del Taco began testing the technology in 2022 but announced in February of this year that it would no longer use voicebots from Presto Automation to take orders in the drive-thru.

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So far, the previews have been mostly positive. IGN enjoyed its time with the game, especially with human co-op players, but it notes the bots that replace human players if none are available are not that smart. GameSpot also liked the preview build but had some issues with learning about its customization options.

Focus Interactive has released the final PC hardware requirements for Warhammer 40K: Space Marine II on its X account. Note that the game will require the use of a solid-state drive for storage in your PC gaming rig. Otherwise, the game won't need a high-end PC to run.

Minimum (1920x1080, 30 fps, low graphics preset)

• Requires a 64-bit processor and operating system
• OS: Windows 10/11 64-bit
• Processor: AMD Ryzen 5 2600X / Intel Core i5-8600K
• Memory: 8 GB RAM
• Graphics: 6 GB VRAM, AMD Radeon RX 580 / Nvidia GeForce GTX 1060
• DirectX: Version 12
• Storage: 75 GB available space - SSD Required

Recommended (1920x1080, 60 fps, ultra graphics preset)

• Requires a 64-bit processor and operating system
• OS: Windows 10/11 64-bit
• Processor: AMD Ryzen 7 5800X / Intel Core i7-12700
• Memory: 16 GB RAM
• Graphics: 8 GB VRAM, AMD Radeon RX 6800 XT / Nvidia GeForce RTX 3070
• DirectX: Version 12
• Storage: 75 GB available space - SSD Required

If you want to play the game four days earlier on September 5, you can pre-order the Gold Edition for PS5 and Xbox Series X|S consoles for $99.99 on Amazon, or you can do the same for the PC version via Steam.

As an Amazon Associate, we earn from qualifying purchases.

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AMD had announced Zen 5 Ryzen 9000 series of CPUs in June this year. While originally expected to release on 31st July, AMD delayed its release to August. Just a day before release, AMD officially announced their prices.

AMD Ryzen 7 9700X & Ryzen 5 9600X Reviews

Meanwhile, AMD Ryzen 7 9700X and Ryzen 5 9600X reviews are officially out. Let’s check some of them.

Tom’s Hardware

Tom’s Hardware reviewed both AMD Ryzen 7 9700X & Ryzen 5 9600X.

They found the Ryzen 9700X to be 12% faster than previous-gen Ryzen 7700X. It was also 9% faster than Intel Core i7-14700K.

Even with Ryzen 9600X, they found it to be 12% faster than previous-gen Ryzen 7600X and Intel Core i5-14600K.

Even the power efficiency is great. Take Blender Classroom benchmark for example. While Ryzen 5 9600X and Ryzen 7 9700X both consumed 80W and 82W respectively. The previous-gen Ryzen 5 7600X and Ryzen 7 7700X both consumed way more, at 102W and 129W respectively.

Even the thermals are great. The temps of Ryzen 9600X never went above 69C in multithreaded tests. Which is excellent, as the previous-gen Ryzen 7000 was known to reach 95C.

We must mention, Tom’s Hardware is an outlier in performance. Other reviewers aren’t so impressed.

TechSpot

TechSpot tested just AMD Ryzen 7 9700X. It’s from the famous YouTuber Steve Walton from Hardware Unboxed, who have posted the video review for the same.

In above a dozen of games they tested, they found Ryzen 7 9700X to be just 3%, yes, just 3% faster than the previous-gen Ryzen 7 7700X CPUs. While having almost no difference in minimum FPS.

The Ryzen 9700X was in fact slower than Ryzen 7700X in some games.

In overall PC power usage in gaming, they found it to using be 3% less power. Which is good, but this shows that major power usage improvements have happened in applications, not games.

In simple words, Steve Walton calls the Ryzen 9700X a flop.

TechPowerUP

TechPowerUp too tested AMD Ryzen 7 9700X and AMD Ryzen 5 9600X respectively.

In gaming benchmarks (page 18) at 1080p, they found the Ryzen 9700X to be just 2% faster than the previous-gen Ryzen 7700X. However, it was faster than all the previous-gen Ryzen 7000 CPUs except Ryzen 7800X3D. In applications, the Ryzen 9700X was just 3% faster than the Ryzen 7700X.

Even Ryzen 9600X was just 3% faster than the previous-gen Ryzen 7600X CPU in gaming. It changed a bit in applications, where it was about 7% faster than Ryzen 7600X.

In power consumption (page 23), the numbers were interesting. Both Ryzen 9700X and Ryzen 9600X used way lesser power in applications than their previous-gen counter-parts when running at stock settings.

However, there was hardly any difference in power usage while gaming, both Ryzen 9700X and Ryzen 9600X used almost the same amount of power respectively than their previous-gen versions when running at stock settings.

Due to the above reasons, there were little noticeable difference in temperatures too while gaming. But when testing in Blender, the improvement in temperature was massive.

Why so bad performance numbers though. TechPowerUp says that it’s because of hard power limits that AMD has set. When all the power limits are removed, AMD CPUs seem to perform better.

Conclusion

Gamer Nexus too reviewed Ryzen 9700X (YouTube) and called it a wasted opportunity and we completely agree with them.

Both AMD Ryzen 7 9700X and Ryzen 5 9600X are uninspiring. They don’t offer much performance uplift, they cost a lot more currently and don’t offer that big an improvement in power efficiency in gaming. This is seen in almost all reviewers.

Only Tom’s Hardware got good performance out of them. Even there that could be an exception depending on games tested and binned CPU they got.

Except performance improvements in single thread, applications and power usage decrease in application, these two new CPUs offer no benefit whatsoever for the gamers.

All the big claims by AMD have turned out to be incorrect. If at all, these CPUs are made for datacenter workloads and not gamers.

Some are claiming that this is the worst CPU series by AMD in years. We wonder if they are purposely underpowering their CPUs to sell more X3D CPUs for gamers.

These AMD Ryzen 9000X3D CPUs are likely coming this September. AMD should try to release them as soon as possible.

Meanwhile, reviews for both AMD Ryzen 9 9950X and Ryzen 9 9900X are expected in a few days. It’s to be seen whether they perform similarly to AMD Ryzen 7 9700X and Ryzen 5 9600X or they perform better than those CPUs.

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Hope you enjoyed this news post.

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2023: Over 5,800 news posts | 2024 (till end of July): 3,313 news posts

United States District Judge Amit Mehta found Google guilty of building a monopolistic position in web search. The Mountain View corporation spent billions of dollars becoming the leading search provider for computing platforms and web browsers on PC and mobile devices.

Most of the $21 billion spent went to Apple in exchange for setting Google as the default search engine on iPhone, iPad, and Mac systems.

The judge will now need to decide on a penalty for the company's actions, including the potential of forcing Google to stop payments to its search "partners completely," which could have dire consequences for smaller companies like Mozilla.

Its most recent financials show Mozilla gets $510 million out of its $593 million in total revenue from its Google partnership. This precarious financial position is a side effect of its deal with Alphabet, which made Google the search engine default for newer Firefox installations.

The open-source web browser has experienced a steady market share decline over the past few years. Meanwhile, Mozilla management was paid millions to develop a new "vision" of a theoretical future with AI chatbots. Mozilla Corporation, the wholly owned subsidiary of Mozilla Foundation managing Firefox development, could find itself in a severe struggle for revenue if Google's money suddenly dried up.

Apple, one of the world's largest companies with many revenue sources, would likely withstand the financial hit if Google had to stop paying to get its search engine on Cupertino's devices. Conversely, Mozilla would not likely survive the hit, jeopardizing Firefox development. The open-source community could adopt the Red Panda browser for now, which has happened with other big, popular software projects.

For now, Mozilla is reviewing the court's decision and considering the potential impact on its business prospects. It says it has always championed competition in the search industry and will continue to offer a range of search options, including Google and its competitors. The court could also penalize Google in other ways, giving Mozilla at least a few more years of revenue and time to develop an exit strategy if it comes to that.

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Gamers Nexus (2.25M subscribers)

August 7, 2024

Video length: 33m 43s

00:00 - AMD R7 9700X CPU Review

02:28 - Price Comparison & Update

03:31 - Stability Problems

06:01 - Methodology & Software

08:04 - CPU Power Consumption on 9700X

09:05 - Efficiency Benchmark

10:05 - Frequency: All-Core Boost

11:13 - Frequency: Single-Core Boost

11:39 - Thermal Sensor Change Comparison

13:48 - Starfield Gaming CPU Benchmarks

15:05 - FFXIV: Dawntrail CPU Benchmarks (1080p & 1440p)

16:48 - Baldur's Gate 3 Best CPUs

17:57 - Dragon's Dogma 2 CPU Comparison

19:01 - F1 24 9700X vs. 7800X3D

20:22 - Stellaris Simulation Time

21:49 - Blender Best CPUs for Rendering

23:21 - Compression & Decompression

24:14 - Photoshop CPU Benchmarks

24:57 - Premiere CPU Tests

25:37 - Code Compile (Chromium)

26:07 - SpecWS Rodinia CFD

26:26 - SpecWS LAMMPS Biomedical Test

27:03 - Conclusion

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Paul's Hardware (1.48M subscribers)

August 7, 2024

Video length: 16m 56s

0:00 Welcome to my Ryzen 9600X and 9700X Review

0:56 A Few Notes on the Intel Situation

1:43 Spec Comparison

2:54 Testing Hardware

3:37 Power Draw

4:00 BENCHMARKS - Compute

8:24 Cyberpunk 2077 - 1080 and 4K

9:37 Starfield - 1080 and 4K

10:35 F1 23 - 1080 and 4K

11:30 Microsoft Flight Simulator - 1080 and 4K

12:57 Temp Testing - 360mm AIO vs Air Cooler

14:56 Conclusion and Closing Thoughts

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I've recommended AMD's Ryzen 5 5600X and, after an eventual price drop, the Ryzen 7 5800X for years since their release, with the latter installed in my gaming rig.

AMD always has the edge on affordability with desktop processors, but it often lags behind Intel on some performance metrics. Whether that matters to you would vary depending on a few value-centric factors.

However, despite dropping the power draw and price tag, the all-new AMD Ryzen 7 9700X has made some incredible performance breakthroughs in single-core benchmarks and even beats out my previous recommendation of the best gaming CPU on the market. Here's how it performed in my testing and where it ranks against its top rivals.

This review was made possible by a review sample provided by AMD. The company did not see the contents of the review before publishing. Some extra benchmark results (mainly for Intel Core CPUs) come from public databases and third-party sources, including CPU Monkey.

Ryzen 7 9700X: Price, availability, and specs

There's no free Wraith cooler, but the price drop is a great trade-off.

(Image credit: Ben Wilson | Windows Central)

 

AMD will sell the Ryzen 7 9700X through mainstream third-party storefronts, like Best Buy and Newegg, for a $359 MSRP from Thursday, August 8, 2024. It's an impressive increase in performance-per-dollar value, with about a 10% discount from the previous-gen Ryzen 7 7700X price tag.

 

The 9700X's base TDP has also significantly dropped to 65W, down from 105W on the 7700X and returning to match its older equivalents. The max turbo clock continues to creep up with each new Ryzen -700X chip, but the core/thread count remains steady alongside the L3 cache. Improvements delivered through AMD's Zen 5 architecture will be the key to how much performance has improved this year.

 

CPU	Cores / Threads	Max clock	L3	Base TDP	MSRP
AMD Ryzen 7 9700X	8/16	5.5 GHz	32 MB	65 W	$359
AMD Ryzen 7 7700X	8/16	5.4 GHz	32 MB	105 W	$399
AMD Ryzen 7 5700X	8/16	4.6 GHz	32 MB	65 W	$299
AMD Ryzen 7 3700X	8/16	4.4 GHz	32 MB	65 W	$329

 

Unlike the Ryzen 8000G Series, the Ryzen 9000 chips don't include AMD's XDNA 2 NPU (Neural Processing Unit) for any dedicated AI processing. However, the CPU chiplet still processes AI workloads with an 'enhanced' Advanced Vector Extensions 512 (AVX-512) datapath. AMD recently launched the Ryzen AI 300 Series mobile chips, focusing on generative AI with laptops instead.

 

A dual-core integrated Radeon graphics chiplet is included in the Ryzen 7 9700X, clocked at 2.2GHz, supporting video output for those without a dedicated graphics card. Expansion depends on your motherboard choice, though PCIe 5.0 support for modern GPUs and mandatory DDR5 RAM are standard.

Recommended hardware

AM5 sockets remain the standard for modern Ryzen CPUs, supported by AMD, until at least 2027.

(Image credit: Ben Wilson | Windows Central)

 

AMD recommends a traditional air cooler for the Ryzen 7 9700X and the upcoming 800 Series of AM5 motherboards, including X870 and X870E chipsets. While 870 Series motherboards will be able to push overclocked DDR5 memory speeds to 8000MT/s and beyond, AMD previously provided a sample of G.SKILL Trident Z5 Neo RGB DDR5-6400 RAM and still encourages an AUTO:1:1 DDR5-6000 EXPO profile where possible to stay in the performance "sweet spot."

Ryzen 7 9700X: Multi core performance

Geekbench 6 tests CPUs with burst performance.

(Image credit: Windows Central | CPU Monkey)

 

Cinebench 2024 tests CPUs with sustained stress.

(Image credit: Windows Central | CPU Monkey)

 

CPU-Z benchmarks both single and multi core performance in short bursts.

(Image credit: Windows Central | CPU Monkey)

 

7-Zip simulates archive compression and decompression techniques on the CPU.

(Image credit: Windows Central | CPU Monkey)

 

Depending on how you arrange the performance benchmark results, ranking AMD's octa-core Ryzen 7 9700X splits into two directions. For multi-core performance, this 65W processor is either outshone by four of Intel's 125W offerings over two modern generations in extended stress tests with Cinebench 2024: the 13th Gen Core i5-13600K and Core i7-13700K, plus the 14th Gen Core i5-14600K and Core i7-14700K, or it creeps slightly ahead with burst CPU performance tests in Geekbench 6.

 

While not as significant as the jump from the 5700X to 7700X, the Ryzen 7 9700X still delivers a generational multi-core performance bump despite dropping its base TDP by 40W.

The previous-generation Ryzen 7 7700X pulls ahead in one multi-core benchmark, compressing and decompressing synthetic 7-Zip archives. It also came close in the CPU-Z benchmark test but never outperformed the Ryzen 7 9700X in single-core performance. Intel's 14th Gen i7-14700K multi-core results are leagues ahead with twice the wattage and the explicit increase to 20 cores and 28 threads over the 8c/16t count on the Ryzen 7 9700X, as well as a $50 increase on its MSRP.

 

The mild multi-core bump from the Ryzen 7 7700X to the 9700X is more evident when compared with the older 5700X.

(Image credit: Windows Central | CPU Monkey)

 

AMD's efforts to achieve this multi-core performance at half the power of Intel's competing chips shouldn't be understated. A 40W base TDP drop from the previous-gen 105W Ryzen 7 7700X hasn't stopped the Ryzen 7 9700X from delivering a decent generational performance uplift, though it's certainly far from the significant leap AMD made from the 65W 5700X. Still, it's an impressive metric as AMD moves from Zen 4's 5nm manufacturing process to TSMC's 4nm and is part of an overall showcase in performance-per-watt improvements for the Ryzen 9000 Series.

 

These benchmarks reflect the Ryzen 7 9700X's 3.8GHz base frequency, another drop from the 105W Ryzen 7 7700X, which starts at 4.5GHz. Overclocking enthusiasts shouldn't worry, though, as the 9700X still boosts as high as 5.5GHz, slightly faster than the 7700X's 5.4GHz, despite the lower base power and maximum socket limits. Essentially, AMD can offer at least a minor bump to multi-core performance with the same 65W power draw that it used to, as it sticks with the AM5 socket until 2027 for potential upgrades to the top-end Ryzen 9 9950X following price drops.

Is the AMD Ryzen 7 9700X good for gaming?

The 9700X pulls ahead of the 7800X3D in burst processing.

(Image credit: Ben Wilson | Windows Central)

 

Even in sustained stress tests, the 9700X edges past the 7800X3D.

(Image credit: Ben Wilson | Windows Central)

 

Yes, absolutely. While it doesn't include AMD's 3D V-Cache aimed at gamers, the Ryzen 7 9700X still matches the previous-gen Ryzen 7 7800X3D, a powerhouse processor that has been all too easy to recommend as the best gaming CPU since its release. However, that shouldn't signal to gaming enthusiasts who adopted the Zen 4 -X3D chip that it's already time to upgrade. The performance improvements are marginal, so this serves as more of a temptation to those looking to upgrade from a Ryzen 5000 Series chip.

 

I still recommend the Ryzen 5 5600X to anyone building a budget gaming PC, and I run the Ryzen 7 5800X in my gaming desktop since it eventually dropped from its high MSRP. However, while it would mean a total motherboard upgrade from my AM4 range to a new AM5 equivalent compatible with the Ryzen 7 9700X, I can heartily recommend it as a perfect modern in-between for anyone in a similar situation as mine.

Ryzen 7 9700X: Single core performance

Sorting by single-core performance shows the 9700X on top.

(Image credit: Windows Central | CPU Monkey)

 

Rendering a virtual scene in Cinebench 2024 performed best on the 9700X with a single-core test.

(Image credit: Windows Central | CPU Monkey)

 

Intel's 14th Gen i7 pulls ahead ever so slightly in single-core performance with CPU-Z's benchmark.

(Image credit: Windows Central | CPU Monkey)

 

AMD mostly annihilates its competition in single-core performance, as the Ryzen 7 9700X shoots to the top of the pile with some of the best scores we've seen to date, save only for a CPU-Z result against Intel's 14th Gen i7-14700K. Given the lower physical core count of 8 on the 9700X compared to 20 on the 14700K, it's logical that each core can receive a higher share of wattage and offer stronger performance.

 

AMD wrestles the single-core crown away from Intel as the Ryzen 7 9700X challenges the 14th Gen i7-14700K in most CPU benchmarks.

If all cores were theoretically handling separate tasks equally, AMD would have the edge with a few more watts per core. It's another metric that will appeal to gamers, as single-core performance is usually a priority for many titles, though modern game engines can scale to multi-threaded options more effectively. Still, this bump to single-core performance is phenomenal, especially considering the Ryzen 7 9700X's mid-range position in the 9000 Series. If your suite of apps and games perform better with single-core optimizations, you'll love the 9700X.

Ryzen 7 9700X: The competition

If you're prepared to face potential issues, Intel has Core i5 and i7 alternatives in its 13th and 14th Gen.

(Image credit: Future)

 

AMD is launching the Ryzen 7 9700X and its entry-level sibling, the Ryzen 5 9600X, at the exact moment that Intel is experiencing an instability crisis with its 13th and 14th Gen Core desktop chips. While a microcode (firmware) patch is rolling out to compatible motherboards, there is still a risk that chips like the i7-13700K could be affected by an oxidization issue if manufactured in early 2023 before Intel had addressed it.

 

Ryzen 9000 chips weren't immune to launch problems, as AMD delayed the 9600X and 9700X to fix a production issue, which seemed to be little more than a model typo on the chips. Still, enthusiast PC builders who are comfortable updating their motherboard BIOS shouldn't be too wary of comparing the 9700X against its primary rivals, especially as Intel offers extended warranties and RMA assistance.

Ryzen 9000 vs. Intel 13th & 14th Gen

CPU	Cores	Threads	Max clock	L3/Smart Cache	Base TDP	MSRP
AMD Ryzen 7 9700X	8	16	5.5 GHz	32 MB	65 W	$359
Intel Core i7-14700K	20	28	5.6 GHz	33 MB	125 W	$409
Intel Core i7-13700K	16	24	5.4 GHz	30 MB	125 W	$409
Intel Core i5-13600K	14	20	5.1 GHz	24 MB	125 W	$329
Intel Core i5-14600K	14	20	5.3 GHz	24 MB	125 W	$319

 

Even if the recent microcode bug controversy hadn't happened and Intel was on a level playing field with AMD, there is still the matter of performance-per-watt and the surrounding costs of adopting each processor. Internally, AMD pits the Ryzen 7 9700X against Intel's 14th Gen Core i7-14700K — that's a $359 65W AMD chip with 8 cores and 16 threads against a $409 125W Intel variant with 20 cores and 28 threads.

 

I can't comfortably recommend Intel's 13th or 14th Gen chips to anyone who isn't extremely comfortable with system tweaks and regular BIOS updates to avoid issues.

Based on performance benchmarking results, the Ryzen 7 9700X is more comparable to a mid-range Intel 13th Gen Core i5-13600K, which launched at $329 but can be found for as low as $249.99 at Best Buy. However, even with a saving of around $100, I can't comfortably recommend Intel's 13th or 14th Gen chips to anyone who isn't extremely comfortable with system tweaks and regular BIOS updates to avoid issues.

 

Hardcore gamers should wait for the inevitable -X3D variants of the Ryzen 9000 Series unless you're updating from a much older machine. Anyone with an AM5 socket board likely wouldn't see significant boosts in the 9700X from their Ryzen 7000 or even 8000G chips, but those on older AM4 socket boards can target the 9700X for a mid-range upgrade. Intel users on equivalent 12th Gen chips and earlier would need to upgrade their motherboards no matter what, but they should be happy with the 9700X.

Ryzen 7 9700X: Should you buy?

AMD still uses the ugly heat spreader pattern with the 9700X, but I'll give them a pass based on its performance. (Image credit: Ben Wilson | Windows Central)

You should buy this if ...

✅ Your apps need strong single-core performance

 

The Ryzen 7 9700X exhibits some of the best performance in single-core testing that I've ever seen, so it's great for many games and creative apps.

 

✅ You're building a mid-range gaming PC

 

Alongside a generous price drop from last gen, the 9700X offers better performance-per-watt over the Ryzen 7000 Series and is a new hot pick over the 5600X.

You should avoid this if ...

❌ You're a hardcore gamer targeting the best specs

 

AMD will, presumably and inevitably, release -X3D variants of the Ryzen 9000 Series chips, which would make more sense than the 9700X for a high-end gaming rig utilizing AMD's 3D V-Cache.

 

❌ You already have an equivalent Ryzen 7000 Series chip

 

While the 9700X has made a generational improvement on multi-core performance (and especially single-core), there isn't enough of a leap over the previous-gen Ryzen 7 7700X.

 

---

 

AMD delivers phenomenal single-core performance in what is otherwise a mid-range processor in its latest Ryzen 9000 Series of desktop chips, with a 'good enough' generational multi-core improvement. Still, a generous price drop from the previous Ryzen 7000 -X chips alongside a return to a 65W base TDP make this an extremely hot pick for mid-tier custom desktop builders looking for the best performance-per-watt, taking over from the Ryzen 5 5600X/7 5800X as my ultimate value-for-money picks.

 

Intel might be having a rough time with its 13th and 14th Gen chips exhibiting microcode issues, but that doesn't entirely put them out of the race. On the contrary, most comparable Intel Core desktop processors are unaffected or remedied with a simple BIOS update. However, these power-hungry 125W chips are finally knocked off their top spot for single-core scores and can't beat AMD's pricing for this gen. It's an outstanding display from Team Red and scores one of the easiest recommendations I've ever made.

 

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AMD's Ryzen 5 5600X was one of my all-time favorite processors, thanks to an astronomically perfect balance of performance and price, even if I did spring a little extra cash for the 5800X in my desktop.

Nevertheless, any successor has a mountain to climb to receive the same praise as its 5000 Series precursor. Ryzen chips have always been a go-to pick for custom builders on a budget, and the -X range targets enthusiast gamers, with the AMD Ryzen 5 9600X opening as the entry-level chip in the new Ryzen 9000 Series.

Can it stand as the new hot pick for budding PC gamers looking to enter the modern age of AM5 motherboards with everything AMD's Zen 5 architecture can offer, or is it outshined by its slightly beefier Ryzen 7 9700X sibling and even AMD's previous-gen chips? Here's what I found in my testing.

This review was made possible by a review sample provided by AMD. The company did not see the contents of the review before publishing. Some extra benchmark results (mainly for Intel Core CPUs) come from public databases and third-party sources, including CPU Monkey.

Ryzen 5 9600X: Price, availability, and specs

AMD dropped its MSRP this year, but you'll still need to spring for an aftermarket CPU cooler.

(Image credit: Ben Wilson | Windows Central)

 

AMD will offer the Ryzen 5 9600X through major third-party storefronts, like Newegg and Best Buy, for a $279 MSRP from Thursday, August 8, 2024 — $20 cheaper than the previous-gen Ryzen 5 7600X and the 5600X before it.

 

The entry-level 9600X also sees AMD returning to a 65W base TDP, just like the Ryzen 5 5600X, after which it temporarily climbed to 105W for the 7600X. The base clock is 3.9GHz, higher than its mid-range sibling, the Ryzen 7 9700X, while the max turbo clock raises slightly this generation to 5.4GHz.

 

Core/thread count and L3 cache count remain the same at 6c/12t, meaning AMD has another chance to showcase performance-per-watt improvements with its 4nm manufacturing process and Zen 5 architecture within the new Ryzen 9000 Series.

 

CPU	Cores / Threads	Max clock	L3	Base TDP	MSRP
AMD Ryzen 5 9600X	6/12	5.4 GHz	32 MB	65 W	$279
AMD Ryzen 5 7600X	6/12	5.3 GHz	32 MB	105 W	$299
AMD Ryzen 5 5600X	6/12	4.6 GHz	32 MB	65 W	$299
AMD Ryzen 5 3600X	6/12	4.4 GHz	32 MB	95 W	$249

 

AMD doesn't include a dedicated NPU (Neural Processing Unit) for local AI processing on the Ryzen 9000 chips but has improved LLM performance overall with an 'enhanced' Advanced Vector Extensions 512 (AVX-512) datapath. Otherwise, AMD's recently launched Ryzen AI 300 Series mobile chips focus on generative AI in laptops, like the ASUS Zenbook S 16 (UM5606) that "challenges Snapdragon X and stomps Intel Meteor Lake."

 

For those looking into AI-specific workloads or entry-level builds, AMD's Ryzen 8000G Series will be more appropriate, including the previously reviewed Ryzen 7 8700G, which features stronger integrated graphics than the dual-core Radeon chiplet included in the Ryzen 5 9600X, clocked at 2.2GHz. Whichever way you go, DDR5 RAM remains mandatory with AM5 sockets, but the Ryzen 9000 Series supports PCIe 5.0 expansion slots.

Recommended hardware

AMD's plate design is still an enemy of thermal paste cleanliness, but AM5 is at least supported until 2027.

(Image credit: Ben Wilson | Windows Central)

 

AMD recommends a tower air cooler for the Ryzen 5 9600X and the upcoming 800 Series of AM5 socket motherboards, including X870 and X870E chipsets. While the former supports overclocked DDR5 memory with speeds up to 8000MT/s and above, AMD had previously provided a sample of G.SKILL Trident Z5 Neo RGB DDR5-6400 RAM and still encouraged an AUTO:1:1 DDR5-6000 EXPO profile to stay in the Ryzen performance "sweet spot."

Ryzen 5 9600X: Multi core performance

Geekbench 6 tests the burst performance capability of CPUs.

(Image credit: Windows Central | CPU Monkey)

 

Cinebench 2024 runs a longer, sustained stress test.

(Image credit: Windows Central | CPU Monkey)

 

CPU-Z tests both single core and multi core performance in a short test.

(Image credit: Windows Central | CPU Monkey)

 

7-Zip's benchmark simulates archive compression and decompression.(Image credit: Windows Central | CPU Monkey)

 

Much like the mid-range Ryzen 7 9700X, benchmarking the Ryzen 5 9600X delivers contrasting results, depending on whether you focus on multi-core or single-core performance. For burst processing tests in Geekbench 6, the 9600X pulls slightly ahead of a previous-generation Intel rival, the 13th Gen Core i5-13600K, and creeps reasonably close to the modern 14th Gen Core i5-14600K. Again, this is a 65W 8-core, 16-thread chip edging past a 125W 14c/20t Intel offering, which speaks volumes to AMD's leaps in power efficiency with Zen 5.

 

Generational multi-core improvements are minimal, as the 105W 7600X still beats the 65W 9600X in specific tests.

However, in sustained stress tests, the Ryzen 5 9600X falls further away from Intel and below AMD's last-gen chip, the Ryzen 7 7700X. It's not too unusual, given the higher 105W TDP on the Zen 4 7700X, but you can grab a 7700X for as low as $288 at Amazon, so it's tough to argue in favor of the 9600X with results like this. Generational multi-core improvements also range from slim numbers to negatives, with 7-Zip's simulated compression benchmark performing better on the 7000 Series chip.

 

The performance change from Ryzen 7000 to 9000 isn't as much of a multi-core leap as the previous 5000 to 7000 Series.

(Image credit: Windows Central | CPU Monkey)

 

Still, it's mostly good news for Zen 5, as the 9600X exhibits improvements in multi-core burst performance over the previous-gen 7600X, albeit much less than the jump from the Ryzen 5 5600X to the 7600X. The focus is entirely on power efficiency for the Ryzen 9000 Series chips, and the 65W 9600X is primarily a decent successor to the Ryzen 7000 Series entry-level offering, the power-hungry 105W Ryzen 5 7600X.

 

With results like these, it's clear to those who have already adopted AMD's Ryzen 7000 Series processors that the Ryzen 5 9600X isn't worth the hassle of an upgrade. However, if you're still rocking a Ryzen 5 3600X, 5600X, or an equivalent Intel 11th or 12th Gen Core i5, then you'd be overhauling your system with an AM5 socket motherboard anyway, and the affordable Ryzen 5 9600X makes more sense.

Is the AMD Ryzen 5 9600X good for gaming?

In burst performance, the 9600X comes incredibly close to the 7800X3D.

(Image credit: Windows Central | CPU Monkey)

 

Sustained stress tests show more of a separation, as games would.

(Image credit: Windows Central | CPU Monkey)

 

Yes, if you're on a strict budget. It even scores hot on the heels of my previous top gaming CPU recommendation: the Ryzen 7 7800X3D. While it doesn't sport the same gamer-centric 3D V-Cache as AMD's -X3D Series chips, and I expect a Ryzen 9000X3D Series will be released later this year, there's no denying that the entry-level 9600X is capable enough to handle modern PC gaming. If you want to build an affordable but modern gaming rig, the Ryzen 5 9600X is a cheaper entry-level CPU with excellent power efficiency.

Ryzen 5 9600X: Single core performance

Both of the new Ryzen 9000 chips come out on top in single core burst performance.

(Image credit: Windows Central | CPU Monkey)

 

It's the same story in Cinebench, as AMD pulls ahead in single core scores.

(Image credit: Windows Central | CPU Monkey)

 

Intel still edges ahead in specific tests, like CPU-Z's single core benchmark.

(Image credit: Windows Central | CPU Monkey)

 

AMD comes out on top with single-core testing, with the Ryzen 5 9600X and Ryzen 7 9700X scoring among the highest benchmark results I've ever seen for 65W chips. In every test, the 9600X beats its intended rival, Intel's 14th Gen Core i5-14600K, bested only by the Core i7-14700K in CPU-Z's benchmark. Again, these Ryzen 9000 Series processors are going up against 125W Core i5 and i7 chips with much higher physical core counts, theoretically dividing a higher even wattage to a per-core amount than Intel.

 

AMD's 65W Ryzen 9600X beats Intel's 125W Core i5-14600K single-core performance in every benchmark.

The real-world benefits of single-core performance are tricky to quantify for the average PC user, but many modern game engines still thrive on single-thread processing. Since the 9600X is so close to the 7800X3D in multi-core performance and actually better in single-core tests, it becomes a tempting new option as an entry-level Zen 5 gaming CPU. While I start to sound like a broken record, this is another testament to AMD's triumphs in higher performance at a much lower wattage than the competition and sets a new standard for single-core scores.

Ryzen 5 9600X: The competition

Even Intel's 13th Gen Core i5 chips will crush the Ryzen 5 7600X in multi-core performance (if they're stable enough.)

(Image credit: Daniel Rubino)

 

It's practically impossible to ignore Intel's instability crisis with its 13th and 14th Gen Core desktop chips, triggered by a microcode (firmware) bug that is permanently degrading affected processors. While the 13th Gen Core i5-13600K sells for around $234, it's currently impossible for me to recommend to anyone who isn't extremely comfortable with applying manual BIOS tweaks and firmware updates to prevent issues.

 

If you're unlucky enough to buy a 13th Gen Intel Core variant manufactured in early 2023, you might experience degradation caused by an oxidization problem discovered around this time. Intel is at least offering extended warranties and RMA assistance to those affected, but it hardly seems worth the risk to the majority of (presumably novice) PC builders looking at entry-level chips.

 

It's currently impossible for me to recommend Intel's 13th (or 14th) Gen to anyone who isn't extremely comfortable with manual BIOS tweaks and firmware updates to prevent issues.

Instead, the call for competitors comes from inside AMD's house. If you're a creator looking to maximize multi-core performance on an AM5 system, the Ryzen 7 7700X is only $288 at the time of writing, barely a few dollars more than the 9600X's MSRP. Otherwise, gaming enthusiasts might want to wait for the inevitable -X3D variants of AMD's Ryzen 9000 Series to take advantage of an updated version of 3D V-Cache.

 

Overall, if you're currently running an AMD 7000 Series chip or an Intel 13th Gen equivalent, then the Ryzen 5 9600X either won't provide enough of a performance bump or will be a negative trade-off. However, if you're still on Ryzen 3000 to 5000 or Intel 12th Gen and earlier, the 9600X is a great entry point to AMD's Zen 5 platform since you'll need an all-new AM5 socket motherboard anyway.

Ryzen 5 9600X: Should you buy?

It's a tricky position for the 9600X to open this new generation when it's followed so closely by Ryzen 7000 chips.

(Image credit: Ben Wilson | Windows Central

You should buy this if ...

✅ You're upgrading from much older hardware

 

The generational multi-core performance leaps are so minor if you're already running a Ryzen 7000 Series chip. Still, those on older processors with AM4 sockets will appreciate this affordable and versatile entry-level AM5 option.

 

✅ You'll benefit from single-core performance gains

 

AMD offers incredible single-core instructions-per-cycle (IPC) improvements for those reliant on software and games that better utilize single cores or generally lack multi-core optimizations.

You should avoid this if ...

❌ You're an all-out hardcore PC gamer

 

While it's tempting and more affordable than the previous-gen Ryzen 7 7800X3D, a 9000X3D variant will undoubtedly be released later this year, which will better suit high-end gaming (if you can afford the extra cost.)

 

❌ You're already on the AM5 socket

 

It's unlikely that you'll see any significant performance benefits from the 9600X if you're already running a Ryzen 7000 Series (or even 8000G Series)  processor — this is mostly a minor entry-level bump, not a major step-up.

 

---

 

The entry-level chip of any processor generation is never expected to blow the previous range out of the water. However, AMD still delivers incredible single-core performance with the Ryzen 5 9600X. It pulls ahead of, or at least matches, every comparable Intel Core i5 and Core i7 processor and does it all with a lower TDP and more affordable MSRP. Still, it's not going to tempt those who already adopted the Ryzen 7000 Series or Intel's 12th, 13th, or 14th Gen Core desktop chips.

 

Instead, the 9600X stands as the perfect entry point into AM5 socket motherboards and AMD's Zen 5 architecture, with prospects to upgrade to either a top-end Ryzen 9 9950X for creators or wait for the inevitable 9000X3D gaming chips. If you're running older AM4 or LGA1200 hardware, the 9600X offers some of the best performance-per-watt value on a budget, especially if your favorite software suite and games are better optimized for single-core processing.

 

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"We are absolutely blown away by the incredible support from the community for our mod. Your enthusiasm and feedback mean the world to us," says the team in a Discord announcement post. "We have some big plans for the future, starting with a hotfix."

The hotfix will focus on crashes and "essential systems like Buffout 4," alongside other fixes that need urgent attention. Next, the development team has plans to drop a "HUGE patch that will address all the issues reported in our Discord ⁠as well as a multitude of quest-related and other problems."

The mod developers plan to release the hotfix first to fans, followed by the much larger update. Unfortunately, no firm launch windows were given for either of the upcoming drops.

Surprisingly, the development team is even offering "1-on-1 troubleshooting sessions" with players who are having problems with installation issues or crashes. Moreover, the team will be hosting a special livestream on the official Team FOLON Twitch channel at 8 pm UK time on Thursday, August 8. Fans will be able to interact with the development team and get behind-the-scenes scoops during the stream.

Fallout: London is currently available to install via GOG for both GOG and Steam customers who need a DRM-free version. However, installing Fallout: London on a Steam copy does require jumping through some additional hoops. Check out the installation instructions for the mod's launch over here. The Epic Games Store version of Fallout 4 is still not compatible with the mod.

Via Eurogamer

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A deep learning model was as effective as radiologists in detecting clinically significant prostate cancer on multiparametric MRI, a retrospective study suggested.

In an internal test set of 400 examinations, the model's performance did not differ from that of experienced radiologists in detecting clinically significant prostate cancer, with area under the receiver operating characteristic curves (AUCs) of 0.89 and 0.89 for the deep learning model and radiologists, respectively (P=0.88), reported Naoki Takahashi, MD, of the Mayo Clinic in Rochester, Minnesota, and colleagues.

Results were similar on an external test set of 204 examinations, with AUCs of 0.86 and 0.84 for the deep learning model and the radiologists (P=0.68), they noted in Radiologyopens in a new tab or window.

Moreover, Takahashi and colleagues found that the deep learning model plus radiologists performed better than radiologists alone in the external test set (AUC 0.89 vs 0.84, P<0.001).

"We believe that our model has the potential to assist radiologists in identifying clinically significant prostate cancer and facilitate lesion biopsy, hence improving the diagnosis of prostate cancer," they wrote.

The authors explained that machine learning or deep learning models are usually trained using ground truths, which include manually annotated regions of interest that are correlated with pathology results.

However, they pointed out that this is a resource-intensive and time-consuming process, "limiting the number of cases that can be used for model development."

Thus, they said their model is "unique" in that the ground truth labels contained only the presence or absence of clinically significant prostate cancer without requiring information about lesion location.

In an editorial accompanying the studyopens in a new tab or window, Patricia M. Johnson, PhD, and Hersh Chandarana, MD, MBA, both of the NYU Grossman School of Medicine/NYU Langone Health in New York City, pointed out that while studies have consistently shown that MRI outperforms prostate-specific antigen (PSA) testing in screening for clinically significant prostate cancer, reducing the cost and increasing the accessibility of MRI "is critical for the viability of MRI screening programs."

This study "represents a step toward MRI screening for clinically significant prostate cancer by potentially decreasing the interpretation burden," they wrote.

Johnson and Chandarana noted that while the study used multiparametric MRI, "the field is shifting toward use of biparametric prostate MRI," which promises abbreviated examination times and minimizes patient discomfort.

With the "impressive results" demonstrated by deep learning with multiparametric MRI in the current study, extending this approach to biparametric MRI "could substantially amplify its utility and impact," they suggested, adding that training a similar model for biparametric MRI datasets "is a highly valuable direction for ongoing and future research."

Of note, Takahashi said in a press releaseopens in a new tab or window that he does not think the model can be used as a standalone tool, but should be used as "an adjunct in our decision-making process."

He added that he and his colleagues would like to conduct a prospective study examining how radiologists interact with the model's predictions. "We'd like to present the model's output to radiologists and assess how they use it for interpretation and compare the combined performance of radiologist and model to the radiologist alone in predicting clinically significant prostate cancer," he explained.

For this study, Takahashi and colleagues used data from patients without known prostate cancer at a single academic institution who underwent MRI from January 2017 to December 2019.

A total of 6,141 examinations from 5,555 individual patients met the inclusion criteria, with the final sample containing 5,735 examinations from 5,215 individual patients (mean age 66 years). Of these 1,514 examinations (1,454 patients) showed clinically significant prostate cancer.

Because the output from the deep learning model does not include tumor location, the researchers used a gradient-weighted class activation map (Grad-CAM) to show tumor localization. For true-positive examinations, Grad-CAM consistently highlighted clinically significant lesions, the authors said.

They also determined that integrating clinical features such as serum PSA levels and gland volumes with the deep learning image-only model and with radiologists' interpretations further improved the AUC on the internal test set.

Takahashi and colleagues acknowledged the study has limitations, including the fact that only radiologists who specialized in prostate MRI participated in the study.

"It is anticipated that the model will perform better than and further improve the diagnostic accuracy of trainees and general radiologists," they wrote.

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About seven years ago, the company had the chance to buy a stake in OpenAI, then a fledgling non-profit research organization working in a little-known field called generative artificial intelligence, four people with direct knowledge of those discussions told Reuters.

Over several months in 2017 and 2018, executives at the two companies discussed various options, including Intel buying a 15% stake for $1 billion in cash, three of the people said. They also discussed Intel taking an additional 15% stake in OpenAI if it made hardware for the startup at cost price, two people said.

Intel (INTC.O) ultimately decided against a deal, partly because then-CEO Bob Swan did not think generative AI models would make it to market in the near future and thus repay the chipmaker's investment, according to three of the sources, who all requested anonymity to discuss confidential matters.

OpenAI was interested in an investment from Intel because it would have reduced their reliance on Nvidia's chips and allowed the startup to build its own infrastructure, two of the people said. The deal also fell through because Intel's data center unit did not want to make products at cost, the people added.

An Intel spokesperson did not address questions about the potential deal. Swan did not respond to a request for comment and OpenAI declined to comment.

Intel's decision not to invest in OpenAI, which went on to launch the groundbreaking ChatGPT in 2022 and is now reportedly valued at about $80 billion, has not previously been made public.

It is among a series of strategic misfortunes that have seen the company, which was at the cutting edge of computer chips in the 1990s and 2000s, stumble in the era of AI, according to Reuters interviews with nine people familiar with the matter including former Intel executives and industry experts.

Last week, Intel's second-quarter earnings triggered a stock price decline of more than a quarter of its value in its worst trading day since 1974.

For the first time in 30 years, the tech company is worth less than $100 billion. The erstwhile market kingpin - whose marketing slogan "Intel Inside" long represented the gold standard of quality - is still struggling to get a blockbuster AI chip product to market.

Intel is now dwarfed by $2.6 trillion rival Nvidia (NVDA.O) which has pivoted from video game graphics to AI chips needed to build, train and operate large generative AI systems like OpenAI's GPT4 and Meta Platforms' (META.O), opens new tab Llama models. Intel has also fallen behind the $218 billion AMD (AMD.O).

Asked about its AI progress, the Intel spokesperson referred to recent comments by CEO Pat Gelsinger, who said the company's third-generation Gaudi AI chip, which it aims to launch in the third quarter of this year, would outperform rivals.

Gelsinger said the company had "20-plus" customers for the second and third generation of Gaudi and that its next-generation Falcon Shores AI chip would launch in late 2025.

"We are nearing the completion of a historic pace of design and process technology innovation, and we are encouraged by the product pipeline we're building to capture a greater share of the AI market going forward," the spokesperson told Reuters.

GAMING CHIPS SWEEP AI

On the OpenAI front, Microsoft (MSFT.O) stepped in to make an investment in 2019, propelling itself to the forefront of the AI era triggered by the 2022 release of ChatGPT and a frenzy of activity among the largest companies in the world to deploy AI.

Although in hindsight the prospective deal was a missed chance for Intel, the company has been gradually losing the battle for AI supremacy for more than decade, according to the former executives and industry experts interviewed.

"Intel failed in AI because they didn't present a cohesive product strategy to their customers," said Dylan Patel, founder of semiconductor research group SemiAnalysis.

For more than two decades, Intel believed the CPU, or central processing unit, like the ones that power desktop and laptop computers, could more effectively handle the processing tasks required to build and run AI models, according to four former Intel executives with direct knowledge of the company's plans.

Intel engineers viewed the graphics processing unit (GPU) video gaming chip architecture, used by rivals Nvidia and Advanced Micro Devices, as comparatively "ugly," one of the people said.

By the mid 2000s, though, researchers had discovered that the gaming chips were far more efficient than CPUs at handling the intensive data crunching necessary to build and train large AI models. Because GPUs are designed for game graphics, they can perform an enormous number of calculations in parallel.

Nvidia's engineers have spent years since then modifying the GPU architecture to tune them for AI uses, and built the software necessary to harness the capabilities.

"When AI hit ... Intel just didn't have the right processor at the right time," said Lou Miscioscia, analyst at Japanese investment bank Daiwa.

NERVANA AND HABANA

Since 2010, Intel has made at least four attempts to produce a viable AI chip, including acquiring two startups and at least two major homegrown efforts. None have made a dent against Nvidia or AMD in the rapidly expanding and lucrative market, according to three people with direct knowledge of the company's internal activities.

Intel's entire data center business is expected to generate sales of $13.89 billion this year - which includes the company's AI chips but many other designs too - while analysts expect Nvidia to generate data center revenue of $105.9 billion.

In 2016, Intel CEO Brian Krzanich sought to buy its way into the AI business by acquiring Nervana Systems for $408 million. Intel executives were attracted to Nervana's technology, which was similar to a tensor processing unit (TPU) chip made by Google, according to two former executives.

The TPU - specifically designed for building, or training, large generative AI models - stripped away a conventional GPU's features useful for video games and focused exclusively on optimizing AI calculations.

Nervana enjoyed some success with customers including Meta Platforms for its processor, though not enough to prevent Intel from switching horses and abandoning the project.

In 2019, Intel bought a second chip startup, Habana Labs, for $2 billion before it shut down Nervana's efforts in 2020.

Krzanich did not respond to a request for comment for this article.

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The Geekbench score of the alleged Snapdragon 8 Gen 4 (via Digital Chat Station on Weibo) shows the processor scoring a single-core score of 2884 points while scoring a multi-core score of 8840. There is no information about the GPU performance.

The CPU performance jump is almost 30% in the multi-core test when compared to the Snapdragon 8 Gen 3. The Snapdragon 8 Gen 4 single-core score also appears to be higher by 35% when compared with last year's flagship processor.

GPU performance might see some improvements with the Snapdragon 8 Gen 4 SoC as well. Since the Snapdragon 8 Gen 3 already beats the iPhone 15 Pro Max's 6-core GPU in performance, it is speculated that the Snapdragon 8 Gen 4 will continue this streak this year as well.

Moreover, there is also a chance that the performance scores may also see some gains with the Snapdragon 8 Gen 4 because these could be early benchmark tests on pre-production samples. Pre-production samples always have great room for improvement.

Besides, next year's Samsung Galaxy S25 series will come with the Snapdragon 8 Gen 4 for Galaxy processor, which would be a slightly overclocked version of the standard processor. There is also word that Samsung's Exynos 2500 could overtake the Snapdragon 8 Gen 4 in terms of performance.

Samsung could also introduce DLSS-like (Deep Learning Super Sampling) technology, which, along with Snapdragon 8 Gen 4's "GPU interpolation technology," would offer games like Genshin Impact to run at 120fps in 1080p resolution.

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In June this year, AMD officially announced Zen 5 based Ryzen 9000 series of CPUs. This new series are going to launch with four CPUs at the start, they are:

• AMD Ryzen 9 9950X
• AMD Ryzen 9 9900X
• AMD Ryzen 7 9700X
• AMD Ryzen 5 9600X

The Ryzen 9000 series has some key improvements over the Ryzen 7000. These include 16% IPC average claimed uplift, faster RAM support, improved manufacturing nm node, but most importantly, massively deduced TDP in Ryzen 9900X and below processors.

During their announcement, AMD made no mention of their release dates or prices. AMD later revealed that they are going to release them on 31st of July.

Then, in a surprise, AMD announced that they are delaying their release to August due to some unclarified issues they found during their quality testing during the packaging phase. They even recalled all the CPUs from the retailers and computer makers.

While the internet was wild with unconfirmed photos of AMD Ryzen 9000 CPUs having the wrong model number written on the CPU lid, it was not officially confirmed as the main reason by AMD.

Meanwhile, despite delaying the CPU release to August, AMD never officially announced their prices. Until now, that is.

Ryzen 9000 Prices Revealed

In a Twitter (now X) post, AMD officially revealed (via @ghost_motley & @harukaze5719) the prices of AMD Ryzen 9000 series of CPUs.

AMD Ryzen 9600X CPU will cost $279, AMD Ryzen 9700X $359, Ryzen 9900X $499 and Ryzen 9950X $649.

The SEP prices quoted in the tweet, means Suggested E-tail Price, which is virtually the same as MSRP.

Importantly, as earlier announced, Ryzen 7 9700X & Ryzen 5 9600X will release on 8th August. Whereas, Ryzen 9 9950X & Ryzen 9 9900X will release on 15th August.

Specs Table

For the benefits of the readers, we made a simple specs table, comparing the Ryzen 9000 CPUs and their comparable Ryzen 7000 series CPUs.

Conclusion

As one can see from the above prices, they are cheaper than the AMD Ryzen 7000 series. However, they are still more expensive than what people had earlier expected or even desired them to be.

Take Ryzen 9600X, it’s the cheapest Ryzen 9000 CPU we are going to see for some time. Yet it costs $279. Which budget or mainstream buyer will openly buy such an expensive 6-core CPU in this year. At best, the series should start with $200, if not less.

AMD always does this somehow. It releases its products at an expensive cost. The reviewers and buyers give it a bad review due to their costs. Then they reduce their prices later. But that reduction of prices hardly reach all parts of the world.

What took AMD so long to announce the prices of AMD Ryzen 9000 CPUs is anyone’s guess. But the biggest reason could be they could be waiting to what’s happening with Intel.

CPUs from Intel in the Raptor Lake and Raptor Lake Refresh series are crashing everywhere. Intel’s profits are down. Even Intel’s stock prices are down. Intel’s promised microcode updates for the crashing CPUs are still not available and not easy to deploy either.

In this, AMD could be very happy to price their CPUs as much as they want, because they know their competition is having a bad name right now due to their issues.

Whatever the reason, let’s hope the reviews for the Ryzen 9000 series are good. AMD is making big claims. But that claims are only validated when reviewers review them.

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Micron, one of the industry leaders in producing memory, announced its first PCIe Gen 6-based solid-state drives with significant leaps in performance compared to the current Gen 5-based SSDs.

According to the press release, Micron's first Gen 6 drives can reach sequential read speeds of over 26GB/s, which is almost double what we currently have on the market. For reference, the fastest PCIe Gen 5 solid-state drives peak at roughly 14GB/s. Micron's brand Crucial currently offers the T705, which can deliver 14,500MB/s of sequential read.

Sadly, you will have to wait a bit longer to get your hands on the first consumer-based PCIe Gen 6 solid-state drives. For starters, no consumer platform currently supports PCIe Gen 6—Intel's and AMD's latest motherboards can only work with PCIe Gen 5 solid-state drives.

Also, the promised drive is primarily aimed at data centers and edge devices to advance AI system architecture, deliver faster storage, and increase power efficiency. Micron plans to demonstrate that "it is the first to develop a PCIe Gen 6 SSD" at Flash Memory Summit 2024:

At FMS, Micron will demonstrate that it is the first to develop a PCIe Gen6 SSD for ecosystem enablement, once again showcasing its storage technology leadership. By making this technology — which delivers sequential read bandwidths of over 26GB/s — available to partners, Micron is kickstarting the PCIe Gen6 ecosystem.

Similar to the T705 for general consumers, Micron recently announced the 9550, which is claimed to be "the world's fastest data center SSD," with capacities reaching a whopping 30.72TB. The manufacturer says its 26GB/s-capable Gen 6 solid-state drive builds on top of that announcement.

Flash Memory Summit is happening from August 6 to August 8 at the Santa Clara Convention Center. Visitors can check out Micron's latest developments, demos, and interactive kiosks at booth 107.

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Even if you're a regular reader of my content, you may not know about my secret, hidden passion. I am an ant guy. Or well, aspiring ant guy, I should say. 

Ever since I was a wee sprog rummaging in the dirt in England's urban Midlands, I found myself fascinated by ants. The military urgency and sophisticated co-ordination, their biologically specialization and advanced social structure, their beautiful subterranean architecture. What LOVELY creatures, I would think to myself, only to be saddened when my parents refused me my boyhood dreams of owning my very own ant farm. With the march of time, I let my passions fade into the drudgery of adulthood, until now. 

I'm a grown up now with my grown up money, meaning I can buy an ant farm if I WANT TO. And no mean parents can STOP ME THIS TIME, although maybe my girlfriend probably can... but let's not stymie the dream just yet. 

Somehow, YouTube's uncanny algorithm peered into the deep recesses of my mind and began surfacing ant-based content recently. Channels like AntsCanada and Homemade Ecosystems fill my feed with 6-legged goodness, while I anticipate building my very own vivarium one day. 

But wait, Jez, wtf does this have to do with gaming? Well, friends, I'm here to tell you about the fantastic next best thing to owning your very own ant farm. Coming soon to Xbox, PC, and PlayStation: Empire of the Ants, which I had the privilege of playing just last week. 

Entire the Empire of the Ants

I saw the first trailers for Empire of the Ants during Xbox presentations, and found myself immediately drawn to its insecty goodness. The visuals are just stunning, and the video above is 100% representative of what I experienced on my RTX 4070 PC. Very well optimized, with charming tilt-shift visuals that emphasize the microscopic world of the ants and their ilk. 

Empire of the Ants is a strategy game at its core, and we'll get into the gameplay in just a moment. I want to first touch upon how surprised I was to discover that this is actually quite heavily story-based. I was expecting something a little more like Sim Ant before I'd done my research, but this is in fact very action oriented, with a surprising emphasis on story delivery. 

Empire of the Ants is based on a French science fiction novel by the same name, which juxtaposes a human story in Paris with that of an ant colony, also living in Paris. The book details the trials and tribulations of the ant colony and its characters, with science-based details that won the book a ton of praise in its heyday. It's almost a military war novel in essence, as the ants face down various threats to their colony and territory, and contest with unknown weapons from beyond their sphere of perception, and even royal court betrayal and intrigue. It seems Empire of the Ants follows a similar cadence, and describes itself as "Game of Thrones, with ants," full of twists and turns. I guess all the ants in the colony are technically related, after all.

 

Empire of the Ants is absolutely gorgeous and well-optimized, with detailed microcosmic visuals with

impressive depth of field effects.  (Image credit: Microids | Tower Five)

 

In my demo, I was able to go hands-on early with the build Microids plans to present at Gamescom 2024. The build gave me a good overview of the game's structure. You're presented with a variety of hub areas, where story beats play out. In my initial mission, I was tasked by the Queen to solve logistical issues facing the colony, that had just emerged from winter hibernation into spring. Indeed, as the seasons progress, or even missions, the landscape radically changes. It made me realize how a bit of rain for us is essentially a biblical, catastrophic flood event for ants, since after the first mission, rainwater basically flooded the entire map. Puddles are essentially oceans to an ant, and the game riffs on these types of notes quite heavily in its story delivery, much akin to the book according to reviews I've read. 

 

The story is penned in close collaboration with the original author, and features music composed by Mark Choi and Mathieu Alvado, who count Rayman and Baldur's Gate 3 among their achievements. Upon exploring the hub world and learning fresh aspects of the story, players will be able to enter tactical or explorative missions. Microids and developer Tower Five seem to have paid careful attention to making the game as accessible as possible without sacrificing depth, giving players two paths to pushing the story forward. If you don't fancy the hardcore tactical layer but still want to experience the story, the softer-paced explorative combat mode might be more your speed. I will say that Tower Five has done a great job of making the strategic layer incredibly accessible in its own right, though, with intuitive controls and gameplay design that should come naturally to even the freshest RTS larvae. 

Real strategy but accessible (and fun) for newcomers

Designed for controller as well as mouse and keyboard, Empire of the Ants has some of the most intuitive

gamepad controls I've seen from the genre.  (Image credit: Microids | Tower Five)

 

After meeting up with the Queen and committing myself to a pre-emptive strike on a hostile termite colony to the north, I entered into the game's first tactical mission to get a taste of what to expect from the game's beefy 20+ hour story campaign. 

 

Your savior ant acts as both a general and a cursor of sorts. You can move around easily using the joystick, and leap onto ledges and branches and cleverly stick to surfaces in a very anty kind of way. Crawling upside-down can be a bit disorienting at first, but your inner ant will eventually crawl to the surface, and you'll be commanding the six-legged hordes in no time. 

 

Empire of the Ants eschews the heavy resource management of games like Age of Empires or StarCraft, and instead opts for something a lot more action-oriented and fast paced.

 

The resource economy revolves around capturing rival nests from other types of colonizing bugs. Smaller colonies can be invaded and scattered, giving your bugs a new base from which to grow and harvest. Scouting is also key here, using your main ant to survey the locality, and build up your satellite colonies appropriately. 

 

For example, if you see a big food item nearby, it might be worth building a battalion of workers who can set up a supply line to that fallen food stuff. Having a steady supply of food can rapidly increase your unit production, and once you head into warfare, rapidly growing new populations of soldiers, ranged acid-spraying ants, or flying ant bombers becomes increasingly important.

 

The ant battles are as brutal as you might expect.

(Image credit: Microids | Tower Five)

 

The microcosmic worlds are incredibly-well detailed.

(Image credit: Microids | Tower Five)

 

You can ally with different types of insects, too, such as these beefy beetles.

(Image credit: Microids | Tower Five)

 

As you spread across the battlefield, your objectives will come into view. For the demo, my task was to destroy a rival termite colony threatening to encroach upon ant territory. Dispatching the termites would be more of a challenge than beating back smaller nests of budding rival ant species, and thankfully, the game gives you the tools to rise to the occasion. 

 

Unlockable via your nest locations, you can learn how to produce pheromone commands that can inspire, heal, and boost your armies in the locale. You can also spawn super units and other swarms of heavy bugs for those more difficult fights, although they're a lot more limited to access than basic units — so careful use is paramount. 

 

I was surprised how easy and intuitive the gamepad controls were, making good use of the playable ant as a sort of "cursor" to interact with nests for spawning units and the like. You literally crawl over the UI buttons to activate them, which is quite clever, and will make it ideal for devices like the ASUS ROG Ally and Steam Deck too. It's also easy to separate units into different categories to create separate groups and battalions, and send them across the battlefield using the camera to target specific icons. It's not unlike being a squad commander in Battlefield, assigning orders, although your squad is actually guaranteed to listen in Empire of the Ants. 

 

While Empire of the Ants was not quite the simulation strategy game I expected, the intriguing story and impressive visuals coalesces into a game well-worth anticipating. 

It's a bug's life for me

(Image credit: Microids | Tower Five)

 

Empire of the Ants is a very different kind of strategy game, that in essence leans more towards the likes of Minecraft Legends or even games like Overlord or Brutal Legend than something like Age of Empires, which should make it less intimidating to genre newcomers. The simplicity makes it easy to get into, and the royal court intrigue, arthropodic military politics, and stunning photorealism gives it a sense of uniqueness that similar action RTS titles often lack. 

 

I do wonder if the full game will have enough variety and depth in its combat scenarios to avoid repetition. I also wonder how emotionally connected I can possibly feel to ants that don't have facial expressions and the like, but I still find myself entranced enough to put this high up on my list of most anticipated upcoming Xbox games. 

 

Grab Empire of the Ants on November 7, 2024, for Steam, Xbox Series X|S, and PlayStation 5. 

 

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Back in 2013, Google first announced Chromecast, a small dongle that converted regular TVs into Smart TVs. It provided access to various internet apps, including YouTube and more. Over the years, the significance of Chromecast declined as most TVs came with their own OS and smart apps. Now, Google is replacing the Chromecast lineup with the more premium Google TV Streamer. The Google TV Streamer delivers both an entertainment and smart home experience.

Google TV Streamer comes with an improved processor, 4GB of RAM, and 32GB of storage for great performance. It supports 4K HDR with Dolby Vision and Dolby Atmos for a great audio and video experience.

Using Google TV Streamer, you can access popular streaming apps like YouTube TV, Netflix, Disney+, Apple TV, and more. It also provides access to live TV with 800+ free channels. Using the power of Google AI, content suggestions across all your subscriptions are presented in a single location. With Gemini, you can now get full summaries, reviews, and season-by-season breakdowns of content.

With ambient mode, you can display your favorite photos from Google Photos or create new images using generative AI and more. And you can use your voice to do all this.

Google TV Streamer has connectivity support for Matter and a built-in Thread border router that allows you to easily connect with smart home devices like locks and motion sensors. Additionally, the Google Home panel allows you to check your cameras, adjust the lights, and more.

Finally, Google TV Streamer allows you to cast content from your smartphone, control music in your house from your TV and even add it to speaker groups.

Google TV Streamer is available in two colors: Porcelain and Hazel (available only from the U.S. Google Store). You can pre-order it today for $99.99, and it will be available starting September 24th from the Google Store and other retailers.

Source: Google

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•     Google's big loss in monopoly case could have silver lining for Apple
•     US judge rules Google not required to accommodate rivals, aiding Apple's defense
•     Apple argues limiting third-party access to its tech is not anti-competitive behavior

Aug 6 (Reuters) - Apple (AAPL.O), opens new tab could be the winner after Alphabet's (GOOGL.O) Google lost its fight with the U.S. antitrust enforcers earlier this week, with a ruling that supports the iPhone maker's defense in its own antitrust court battle with U.S. prosecutors, legal experts said.

A federal judge mostly sided with state and federal antitrust enforcers in the blockbuster case on Monday that ruled Google's search business was an illegal monopoly, but threw out a claim by several U.S. states that one of Google's ad tools was designed to give the company an advantage over Microsoft's (MSFT.O) Bing.

That piece could help Apple's defense in its own anti-monopoly case, experts said.

The ruling underscored Supreme Court precedent that companies almost never have a "duty to deal" with their rivals, said Herbert Hovenkamp, who teaches antitrust at the University of Pennsylvania Carey Law School.

"Any case, including Apple, in which a duty to deal is a major portion, is going to get a close look," he said.

The states had claimed Google thwarted competition by failing to offer key features for rivals' ads through Search Ads 360, a tool for managing marketing campaigns across multiple search engines.

U.S. District Judge Amit Mehta agreed with Google that it was not required to spur competition by accommodating its rival.

"Their claim requires grappling with a host of questions that the court is ill-equipped to handle," the judge said.

That part of the ruling is good for defendants, said William Kovacic, a professor at George Washington University Law School and former commissioner of the U.S. Federal Trade Commission.

"It also is a reminder that the case is hardly finished," he said, adding that the case and appeals could take years.

To be sure, Apple could ultimately lose billions of dollars because of the Google case if the judge bans the search juggernaut from paying the iPhone maker and others to be the default search engine on their devices.

Mehta noted that Google had paid $26.3 billion in 2021 alone to ensure that its search engine is the default on smartphones and browsers, and to keep its dominant market share.

But the Google ruling could give Apple a boost in its case where the Justice Department says it hampered the development of third-party apps and devices.

The company last week asked for the case to be dismissed, arguing that putting reasonable limitations on third-party developers' access to its technology did not amount to anti-competitive behavior, and that forcing it to share technology with competitors would chill innovation.

The judge in Apple's case need not follow Mehta's ruling, though Apple may try to use it to persuade him.

The Justice Department will have to show Apple's interactions with developers were more like Google's payments to device makers, Hovenkamp said.

"In order to win, the government is going to have to point to some kind of agreement, because then the standard becomes more aggressive," he said.

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Comment In the wake of the AI boom, Nvidia has seen its revenues skyrocket to the point at which it briefly became the most valuable corporation in the world.

That growth was overwhelmingly driven by demand for its datacenter GPUs to train and run the ever-growing catalog of better, smarter, and bigger AI models. But as much as investors would like to believe CEO Jensen Huang's graphics processor empire will continue to grow, doubling quarter after quarter, nothing lasts forever.

As The Next Platform's Timothy Prickett Morgan predicted on last week's episode of The Register’s Kettle podcast, Nvidia's revenues will one day plateau.

If Nvidia's future revolved solely around selling GPUs and nothing else, that might be a big deal. But as Huang frequently reminds folks, Nvidia is every bit as much a software business as a hardware one.

Enabling new markets

From early on, Nvidia recognized the value of software to drive the adoption of GPUs. During a fireside chat with journalist Lauren Goode at SIGGRAPH last week, Huang drove home this point.

"Every time we introduce a domain specific library, it exposes accelerated computing to a new market," he explained. "It's not just about building the accelerator, you have to build the whole stack."

The first release of Nvidia's Compute Unified Device Architecture – better known now as CUDA – came in 2007 and provided an API interface for parallelizing non-graphics workloads across GPUs. While this still required developers and researchers to refactor code, the improvements over general-purpose processors were hard to ignore.

This was especially true for those in the HPC community – one of the first markets Nvidia pursued outside its old territories of gaming and professional graphics. In late 2012, Nvidia software investments helped to put the Oak Ridge National Laboratory's Titan supercomputer in the number one spot on the Top500.

Seventeen years after its initial release, CUDA is just one of an ever-growing list of compute frameworks tailored to specific markets – ranging from deep learning to computational lithography and quantum computing emulation.

Those frameworks helped Nvidia to create markets for its accelerators where little to none previously existed.

Going beyond enablement

Software is Nvidia's not-so-secret weapon, but until recently that weapon has taken the form of enablement. Over the past two years we've seen the accelerator champ's software strategy embrace a subscription pricing model in a meaningful way.

In early 2022, months before OpenAI's ChatGPT set off the AI gold rush, Nvidia CFO Collete Kress detailed the GPU giant's subscription fuelled roadmap – which, she opined, would eventually drive a trillion dollars in revenues.

At the time, Kress predicted $150 billion of that opportunity would be driven by Nvidia's AI Enterprise software suite. Even now that it's posting $26 billion quarters, the business is still well short of that trillion-dollar goal – but we are starting to get a better picture of how it may grow.

From a software standpoint, much of the work on AI enablement has already been done. Nvidia has poured enormous resources into developing tools like cuDNN, TensorRT LLM, and Triton Inference Service to get the most out of its hardware when running AI models.

However these are just pieces of a puzzle that must be carefully assembled and tuned to extract that performance, and tuning is going to be different for each model. It takes a level of familiarity with the model, software, and underlying hardware that enterprises are unlikely to have.

Building an AI easy button

At its GTC event last northern spring Nvidia revealed a new offering designed to lower the barrier to adopting and deploying generative AI at scale. That technology – called Nvidia Inference Microservices, or NIMs for short – essentially consists of containerized models and tools which ship with everything you need to run them preconfigured.

NIM containers can be deployed across just about any runtime that supports Nvidia's GPUs. That might not sound that exciting – but it's kind of the point. Container orchestration isn't exactly an easy problem to solve – just ask the Kubernetes devs. So why reinvent the wheel, when you can make use of existing tools and services in which customers are already invested?

The real value of NIMs seems to come from Nvidia engineers tuning things like TensorRT LLM or Triton Inference Server for specific models or use cases, like retrieval augmented generation (RAG). If you're not familiar, you can find our hands-on guide on RAG here, but the takeaway is that Nvidia is playing system integrator not only with its hardware, but with its software as well.

NIMs are not just clever packaging. By working toward a common API for how models and tools should communicate with one another, Nvidia can provide customers with templates designed to address specific use cases.

Nvidia's pricing ladder

A lower barrier to adoption and deployment of AI inferencing has upsides for both software licensing and hardware sales. On the software side of things, the AI Enterprise license necessary to deploy NIMs in production will set you back $4,500 per GPU per year, or $1 per GPU per hour.

So to deploy Meta's Llama 3.1 405B model with NIMs you'd not only need to rent or buy a system with 8x H100s or H200s – the minimum necessary to run the model without resorting to more aggressive levels of quantization – but you'd also be looking at $36,000/yr or $8/hr in licensing fees.

Assuming a useful lifespan of six years, that works out to between $180,000 to $420,480 in license revenues – per system – depending on whether you pay up front or by the hour. And realistically, enterprises looking to deploy AI are going to need more than one system for both redundancy and scale.

That price delta might make committing to an annual license seem like an obvious choice. But remember that we're talking about microservices that, if implemented properly, should be able to scale up or down depending on demand.

But, let's say Llama 3.1 405B is a little overkill for your needs and running a smaller model – a far less costly L40S or even L4S – might suffice. Nvidia's pricing structure is set up in a way that it drives customers toward more powerful and capable accelerators.

The AI Enterprise license costs the same regardless of whether you're running eight L40Ss or eight H200s. This creates a scenario where it may well be more economical to buy or rent fewer high-end GPUs and run the model at higher batch sizes or queues – since your license fees will be lower over the lifetime of the deployment.

And with single A100 and H100 instances becoming more common – Oracle Cloud Infrastructure, for example, announced availability last week – this is something that enterprises may want to take into consideration when evaluating the total cost of such a deployment.

A blueprint for competition

Assuming NIMs see widespread adoption, they could quickly become a major growth driver for Nvidia.

A little back of the napkin math tells us that if NIMs helped Nvidia attach an AI Enterprise to each of the two million some Hopper GPUs it's expected to ship in 2024, it'd be looking at another $9 to $17.5 billion in annual subscription revenues. Realistically, that's not going to happen – but even if it can realize a fraction of that we're still talking about billions of dollars in annual revenue.

That's not to say NIMs are without challenges. Compared to AI training, inferencing isn't particularly picky. There are several model runners that support inferencing across Nvidia, AMD, and even general-purpose CPUs. NIMs, by comparison, only run on Nvidia hardware – which could prove limiting for customers looking to leverage container orchestration systems like Kubernetes to deploy and serve their models at scale.

This probably won't be a big issue while Nvidia still controls the lion's share of the AI infrastructure market, but will no doubt be a big red flag for customers wary of vendor lock-in.

It might also grab the attention not only of shareholders, but also the Department of Justice. The DoJ is already said to be building an antitrust case against the GPU giant.

That said, if you just want to make models easier to deploy across various cloud and on-prem infrastructure, there's really nothing stopping anyone from creating their own NIM-equivalents, tuned to their preferred hardware or software of choice. In fact, it's surprising that more developers haven't done something like this already. We can easily imagine AMD and Intel bringing similar services to market – potentially even undercutting Nvidia by offering them at no cost.

Ultimately, the success of Nvidia's NIMs may depend on just how much more efficient or performant their tuning is, and how much easier they are to stitch together. ®

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• That ruling could provide a boost to the number two search engine.

All research shows that Alphabet Inc.’s (NASDAQ: GOOGL) Google has at least 80% of the search market share in the United States. Some data puts that closer to 85%. Microsoft Corp.’s (NASDAQ: MSFT) Bing has between 5% and 7%, and Yahoo has a majority of the rest. These numbers have not changed much in over two decades.

Judge Amit P. Mehta of the U.S. District Court for the District of Columbia wrote a 277-page opinion about Google’s place in the U.S. search world. The concussion boiled down to just a few words: “Google is a monopolist, and it has acted as one to maintain its monopoly.” Google will appeal.

What the Ruling Could Mean for Bing

HAKINMHAN / iStock via Getty Images

Does the number two search engine have a chance?

Part of the U.S. government’s argument is that Google pays companies, including Apple and Mozilla, to have Google as the search engine in their browsers. Google responded that people use its search product because it gives much more accurate and useful results. If Google cannot make these deals, it opens the door wide to Bing, because it may have a chance to bid for the browser partnerships with Google blocked from competing.

Bing generates about $6 billion a year for Microsoft. Google’s search division brings in about $200 billion. Neither of these figures includes international sales, but they still give an idea of the financial scale involved. Additionally, Bing would probably need to pay billions of dollars to Apple, for example, to be its default search engine, even if Google were not in the running. (Apple could always turn to Yahoo to force Microsoft to pay more for a browser deal).

It is much too early to tell whether the Google deal would add tens of billions of dollars to Bing’s revenue. One question Microsoft faces is whether the public considers Google the much better product. At this point, that is not clear.

Google will appeal the antitrust ruling. If it loses, Bing could become a major Microsoft profit engine.

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In the latest example of a troubling industry pattern, NVIDIA appears to have scraped troves of copyrighted content for AI training. On Monday, 404 Media’s Samantha Cole reported that the $2.4 trillion company asked workers to download videos from YouTube, Netflix and other datasets to develop commercial AI projects. The graphics card maker is among the tech companies appearing to have adopted a “move fast and break things” ethos as they race to establish dominance in this feverish, too-often-shameful AI gold rush.

The training was reportedly to develop models for products like its Omniverse 3D world generator, self-driving car systems and “digital human” efforts.

NVIDIA defended its practice in an email to Engadget. A company spokesperson said its research is “in full compliance with the letter and the spirit of copyright law” while claiming IP laws protect specific expressions “but not facts, ideas, data, or information.” The company equated the practice to a person’s right to “learn facts, ideas, data, or information from another source and use it to make their own expression.” Human, computer… what’s the difference?

YouTube doesn’t appear to agree. Spokesperson Jack Malon pointed us to a Bloomberg story from April, quoting CEO Neal Mohan saying using YouTube to train AI models would be a “clear violation” of its terms. “Our previous comment still stands,” the YouTube policy communications manager wrote to Engadget.

That quote from Mohan in April was in response to reports that OpenAI trained its Sora text-to-video generator on YouTube videos without permission. Last month, a report showed that the startup Runway AI followed suit.

NVIDIA employees who raised ethical and legal concerns about the practice were reportedly told by their managers that it had already been green-lit by the company's highest levels. “This is an executive decision,” Ming-Yu Liu, vice president of research at NVIDIA, replied. “We have an umbrella approval for all of the data.” Others at the company allegedly described its scraping as an “open legal issue” they’d tackle down the road.

It all sounds similar to Facebook’s (Meta’s) old “move fast and break things” motto, which has succeeded admirably at breaking quite a few things. That included the privacy of millions of people.

In addition to the YouTube and Netflix videos, NVIDIA reportedly instructed workers to train on movie trailer database MovieNet, internal libraries of video game footage and Github video datasets WebVid (now taken down after a cease-and-desist) and InternVid-10M. The latter is a dataset containing 10 million YouTube video IDs.

Some of the data NVIDIA allegedly trained on was only marked as eligible for academic (or otherwise non-commercial) use. HD-VG-130M, a library of 130 million YouTube videos, includes a usage license specifying that it’s only meant for academic research. NVIDIA reportedly brushed aside concerns about academic-only terms, insisting their batches were fair game for its commercial AI products.

To evade detection from YouTube, NVIDIA reportedly downloaded content using virtual machines (VMs) with rotating IP addresses to avoid bans. In response to a worker’s suggestion to use a third-party IP address-rotating tool, another NVIDIA employee reportedly wrote, “We are on [Amazon Web Services](#) and restarting a [virtual machine](#) instance gives a new public IP[.](#) So, that’s not a problem so far.”

404 Media’s full report on NVIDIA’s practices is worth a read.

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