NVIDIA

nvidia’s-new-ai-audio-model-can-synthesize-sounds-that-have-never-existed

Nvidia’s new AI audio model can synthesize sounds that have never existed

At this point, anyone who has been following AI research is long familiar with generative models that can synthesize speech or melodic music from nothing but text prompting. Nvidia’s newly revealed “Fugatto” model looks to go a step further, using new synthetic training methods and inference-level combination techniques to “transform any mix of music, voices, and sounds,” including the synthesis of sounds that have never existed.

While Fugatto isn’t available for public testing yet, a sample-filled website showcases how Fugatto can be used to dial a number of distinct audio traits and descriptions up or down, resulting in everything from the sound of saxophones barking to people speaking underwater to ambulance sirens singing in a kind of choir. While the results on display can be a bit hit or miss, the vast array of capabilities on display here helps support Nvidia’s description of Fugatto as “a Swiss Army knife for sound.”

You’re only as good as your data

In an explanatory research paper, over a dozen Nvidia researchers explain the difficulty in crafting a training dataset that can “reveal meaningful relationships between audio and language.” While standard language models can often infer how to handle various instructions from the text-based data itself, it can be hard to generalize descriptions and traits from audio without more explicit guidance.

To that end, the researchers start by using an LLM to generate a Python script that can create a large number of template-based and free-form instructions describing different audio “personas” (e.g., “standard, young-crowd, thirty-somethings, professional”). They then generate a set of both absolute (e.g., “synthesize a happy voice”) and relative (e.g., “increase the happiness of this voice”) instructions that can be applied to those personas.

The wide array of open source audio datasets used as the basis for Fugatto generally don’t have these kinds of trait measurements embedded in them by default. But the researchers make use of existing audio understanding models to create “synthetic captions” for their training clips based on their prompts, creating natural language descriptions that can automatically quantify traits such as gender, emotion, and speech quality. Audio processing tools are also used to describe and quantify training clips on a more acoustic level (e.g. “fundamental frequency variance” or “reverb”).

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Facebook, Nvidia push SCOTUS to limit “nuisance” investor suits after scandals


Facebook, Nvidia ask SCOTUS to narrow legal paths to retrieve investor losses.

The Supreme Court will soon weigh two cases that could potentially make it harder for misled investors to sue Big Tech companies after major scandals.

One case involves one of the largest tech scandals of all time, the Facebook-Cambridge Analytica data breach. In 2019, Facebook agreed to pay “more than $5 billion in civil penalties to settle charges by the Federal Trade Commission (FTC) and the Securities and Exchange Commission (SEC) that it had misled its users and investors over the privacy and security of user data on its platform,” a Supreme Court filing said.

The other case involves an allegation that Nvidia intentionally hid how much of its 2017–2018 GPU demand was due to a volatile cryptocurrency boom and not Nvidia’s core gaming business—allegedly misleading investors ahead of a crypto crash. After the bust, Nvidia suddenly had to slash half a billion dollars from its earnings projection, and market experts later estimated that the firm had understated its crypto-related revenue by more than a billion. In 2022, Nvidia paid a $5.5 million SEC penalty over the inadequate disclosures that one SEC chief said “deprived investors of critical information to evaluate the company’s business in a key market.”

Investors, however, have not yet settled their own legal challenges. In both cases, investors suing convinced the 9th Circuit that the companies were guilty of misleading investors. But now, the tech companies have appealed to the Supreme Court, hoping to reverse those rulings.

In case documents, each claimed that their investors have not satisfied high legal bars, which Nvidia argued Congress designed to prevent “frivolous” or “nuisance” lawsuits from going on “fishing expeditions” to claim securities “fraud by hindsight.” Both warned that SCOTUS upholding the 9th Circuit rulings risked flooding courts with frivolous suits, with Nvidia cautioning that such lawsuits can be “used to injure the entire US economy.”

The Supreme Court will hear arguments in the Facebook case on Wednesday, November 6, then the Nvidia case on November 13.

SCOTUS may be persuaded by tech companies still stuck coping with the aftermath of scandals. A former SEC lawyer, Andrew Feller, told Reuters that the Supreme Court’s conservative majority may continue its “recent track record of handing down business-friendly decisions that narrowed the authority of federal regulators” in these cases. Both cases give justices opportunities to “rein in the power of private plaintiffs to enforce federal rules aimed at punishing corporate misconduct,” Reuters reported.

Facebook defends describing risk as hypothetical

The Facebook case centers on an SEC disclosure where Facebook said that its business may be harmed by a data breach, posing that as a hypothetical, without mentioning the ongoing Cambridge Analytica data breach. Specifically, Facebook wrote, “[a]ny failure to prevent or mitigate . . . improper access to or disclosure of our data or user data . . . could result in the loss or misuse of such data, which could harm our business and reputation and diminish our competitive position.”

Investors felt misled, accusing Facebook of hiding the breach by only presenting the risk as a hypothetical that implied no breach had ever occurred in the past and certainly did not disclose the present risk.

However, in a SCOTUS filing, Facebook insisted that “no reasonable investor would interpret a risk disclosure using probabilistic, forward-looking language as impliedly representing that the specified triggering event had never occurred in the past.”

Facebook is now arguing that SCOTUS agreeing that the company should have disclosed the major data breach “would result in a regime under which companies would be required to disclose every previous material incident they have experienced—effectively creating a sweeping regime of omissions liability.”

According to Facebook, news broke about the Cambridge Analytica data breach in 2015, and its business wasn’t immediately harmed. Following that logic, the social media company hopes that SCOTUS will agree that Facebook was only required to disclose the data breach in its SEC filing if Facebook knew its business would likely be harmed from the ongoing breach.

By affirming the 9th Circuit ruling, Facebook alleged, SCOTUS would be “vastly expanding the circumstances in which risk disclosures are deemed false or misleading,” exposing to legal challenges “a wide range of previously immune forward-looking statements—revenue projections, future business plans or objectives, and the like.”

But investors suing argue that Facebook is still being misleading about the data scandal in its court filings.

“The only reason Facebook has ever given to explain why the misappropriation risked no harm was that the event was allegedly disclosed to the public in 2015 and no one cared,” investors’ SCOTUS brief said. But in 2015, a report exposing a data breach tied to a Ted Cruz campaign was denied by Cambridge Analytica and prompted a Facebook investigation that concluded no damage had been done.

“Facebook actively misled the public about its investigation, ‘represent[ing] that no misconduct had been discovered,'” investors alleged, and “Facebook’s deception extended to its public filings with the SEC.”

According to investors, the real damage was done when the true extent of the Cambridge Analytica scandal was exposed in 2018. That caused substantial revenue losses that Facebook likely understood it was risking while allegedly leaving investors blind to those risks for years.

Investors argue that disclosure should not be required of every data breach that hits Facebook, whether it harms its business or not, but that the Cambridge Analytica data breach was significant and should have been disclosed as a material risk. The 9th Circuit agreed, holding that “publicly treating such a material adverse event as a merely hypothetical prospect can be misleading even if the event has not yet produced follow-on business harm because the company has kept the truth from the public.”

They further argued that requiring so-called overdisclosure wouldn’t trigger unwarranted litigation, as Facebook suggests, because Congress has always “given considerable attention to concerns over abusive private litigation.”

If Facebook wins, investors alleged, SCOTUS risks giving any tech company “a license to intentionally mislead investors about the occurrence of hugely material events by describing those events as purely hypothetical prospects.” Siding with Facebook would allegedly give “companies an incentive to stuff their annual reports with boilerplate, generic warnings that reveal little about the company’s actual business and to cover up events that could give rise to corporate scandals, as Facebook did here.”

Facebook argued that if the SEC is concerned about specific disclosures connected to the data breach, “the SEC can invoke the rulemaking process to impose” a requirement that companies must disclose all “past material adverse events.”

Nvidia disputes expert’s crypto data

While the Facebook case involved a bigger scandal, the Nvidia case could have bigger legal implications if Nvidia wins.

In the Nvidia case, investors argued that Nvidia CEO Jensen Huang made public statements allegedly misleading investors by downplaying the high demand for GPUs tied to volatile crypto markets. To plead their case, investors relied on statements from Nvidia employees, internal documents like meeting slides, industry research, as well as an expert opinion crunching general market numbers and estimating that Nvidia “underreported its crypto revenues by $1.126 billion.”

Nvidia claimed it’s far more plausible that the company simply made an “honest miscalculation” while navigating a complex emerging market.

To defend against the suit, Nvidia is arguing that the Private Securities Litigation Reform Act (PSLRA) imposes “special burdens on plaintiffs seeking to bring federal securities fraud class actions” through “heightened pleading requirements” to deter frivolous lawsuits arguing fraud by hindsight.

According to Nvidia, the PSLRA requires investors to allege particular facts based on particular contents of internal Nvidia documents, which goes beyond relying on an expert opinion. The tech company has urged SCOTUS that the 9th Circuit “‘significantly erode[d]” the PSLRA requirements by allowing Plaintiffs to “simply” hire “an expert who manufactured data to fit their allegations.”

“They hired an expert to create data and then filed a class action alleging that Nvidia and its CEO committed securities fraud by failing to disclose the data invented by Plaintiffs’ expert,” Nvidia argued.

This allegedly “eviscerates the guardrails that Congress erected to protect the public from abusive securities litigation” and creates a “dangerous” and “easy-to-replicate ‘roadmap’ for plaintiffs to sidestep the PSLRA in this recurring context.”

“Far from serving Congress’s goal of guarding against fishing expeditions by vexatious litigants, the Ninth Circuit’s opinion declares it open season so long as a plaintiff has funding to hire an expert,” Nvidia alleged.

Investors are hoping SCOTUS will uphold the 9th Circuit’s judgment. Instead of seeing their suit as frivolous, they argued that the SEC fine over the same misconduct “undermines any suggestion that this is the type of frivolous suit that the PSLRA was meant to screen out.”

They’ve disputed Nvidia’s arguments that they’ve relied solely on a hired expert to support their claims, arguing that each fact was corroborated by employee witnesses and third-party reports.

If Nvidia wins, investors warned, the SCOTUS decision would risk harming a wide range of private securities litigation that Congress has found “‘is an indispensable tool’ for ‘defrauded investors’ to ‘recover their losses without having to rely upon government action.'”

Photo of Ashley Belanger

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

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us-suspects-tsmc-helped-huawei-skirt-export-controls,-report-says

US suspects TSMC helped Huawei skirt export controls, report says

In April, TSMC was provided with $6.6 billion in direct CHIPS Act funding to “support TSMC’s investment of more than $65 billion in three greenfield leading-edge fabs in Phoenix, Arizona, which will manufacture the world’s most advanced semiconductors,” the Department of Commerce said.

These investments are key to the Biden-Harris administration’s mission of strengthening “economic and national security by providing a reliable domestic supply of the chips that will underpin the future economy, powering the AI boom and other fast-growing industries like consumer electronics, automotive, Internet of Things, and high-performance computing,” the department noted. And in particular, the funding will help America “maintain our competitive edge” in artificial intelligence, the department said.

It likely wouldn’t make sense to prop TSMC up to help the US “onshore the critical hardware manufacturing capabilities that underpin AI’s deep language learning algorithms and inferencing techniques,” to then limit access to US-made tech. TSMC’s Arizona fabs are supposed to support companies like Apple, Nvidia, and Qualcomm and enable them to “compete effectively,” the Department of Commerce said.

Currently, it’s unclear where the US probe into TSMC will go or whether a damaging finding could potentially impact TSMC’s CHIPS funding.

Last fall, the Department of Commerce published a final rule, though, designed to “prevent CHIPS funds from being used to directly or indirectly benefit foreign countries of concern,” such as China.

If the US suspected that TSMC was aiding Huawei’s AI chip manufacturing, the company could be perceived as avoiding CHIPS guardrails prohibiting TSMC from “knowingly engaging in any joint research or technology licensing effort with a foreign entity of concern that relates to a technology or product that raises national security concerns.”

Violating this “technology clawback” provision of the final rule risks “the full amount” of CHIPS Act funding being “recovered” by the Department of Commerce. That outcome seems unlikely, though, given that TSMC has been awarded more funding than any other recipient apart from Intel.

The Department of Commerce declined Ars’ request to comment on whether TSMC’s CHIPS Act funding could be impacted by their reported probe.

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amd-unveils-powerful-new-ai-chip-to-challenge-nvidia

AMD unveils powerful new AI chip to challenge Nvidia

On Thursday, AMD announced its new MI325X AI accelerator chip, which is set to roll out to data center customers in the fourth quarter of this year. At an event hosted in San Francisco, the company claimed the new chip offers “industry-leading” performance compared to Nvidia’s current H200 GPUs, which are widely used in data centers to power AI applications such as ChatGPT.

With its new chip, AMD hopes to narrow the performance gap with Nvidia in the AI processor market. The Santa Clara-based company also revealed plans for its next-generation MI350 chip, which is positioned as a head-to-head competitor of Nvidia’s new Blackwell system, with an expected shipping date in the second half of 2025.

In an interview with the Financial Times, AMD CEO Lisa Su expressed her ambition for AMD to become the “end-to-end” AI leader over the next decade. “This is the beginning, not the end of the AI race,” she told the publication.

The AMD Instinct MI325X Accelerator.

The AMD Instinct MI325X Accelerator.

The AMD Instinct MI325X Accelerator. Credit: AMD

According to AMD’s website, the announced MI325X accelerator contains 153 billion transistors and is built on the CDNA3 GPU architecture using TSMC’s 5 nm and 6 nm FinFET lithography processes. The chip includes 19,456 stream processors and 1,216 matrix cores spread across 304 compute units. With a peak engine clock of 2100 MHz, the MI325X delivers up to 2.61 PFLOPs of peak eight-bit precision (FP8) performance. For half-precision (FP16) operations, it reaches 1.3 PFLOPs.

AMD unveils powerful new AI chip to challenge Nvidia Read More »

ars-technica-system-guide:-falling-prices-are-more-exciting-than-new-parts

Ars Technica system guide: Falling prices are more exciting than new parts

AMD's Ryzen 7700X makes enough sense to feature in our higher-end gaming build.

Enlarge / AMD’s Ryzen 7700X makes enough sense to feature in our higher-end gaming build.

Andrew Cunningham

It’s been a while since our last system guide, and a few new products—most notably AMD’s Ryzen 9000 series CPUs—have been released since then. But there haven’t been many notable graphics card launches, and new ones are still rumored to be a few months off as both Nvidia and AMD prioritize their money-printing AI accelerators.

But that doesn’t make it a bad time to buy a PC, especially if you’re looking for some cost-efficient builds. Prices of CPUs and GPUs have both fallen a fair bit since we did our last build guide a year or so ago, which means all of our builds are either cheaper than they were before or we can squeeze out a little more performance than before at similar prices.

We have six builds across four broad tiers—a budget office desktop, a budget 1080p gaming PC, a mainstream 1440p-to-4K gaming PC, and a price-conscious workstation build with a powerful CPU and lots of room for future expandability.

You won’t find a high-end “god box” this time around, though; for a money-is-no-object high-end build, it’s probably worth waiting for Intel’s upcoming Arrow Lake desktop processors, AMD’s expected Ryzen 9000X3D series, and whatever Nvidia’s next-generation GPU launch is. All three of those things are expected either later this year or early next.

We have a couple of different iterations of the more expensive builds, and we also suggest multiple alternate components that can make more sense for certain types of builds based on your needs. The fun of PC building is how flexible and customizable it is—whether you want to buy what we recommend and put it together or want to treat these configurations as starting points, hopefully, they give you some idea of what your money can get you right now.

Notes on component selection

Part of the fun of building a PC is making it look the way you want. We’ve selected cases that will physically fit the motherboards and other parts we’re recommending and which we think will be good stylistic fits for each system. But there are many cases out there, and our picks aren’t the only options available.

As for power supplies, we’re looking for 80 Plus certified power supplies from established brands with positive user reviews on retail sites (or positive professional reviews, though these can be somewhat hard to come by for any given PSU these days). If you have a preferred brand, by all means, go with what works for you. The same goes for RAM—we’ll recommend capacities and speeds, and we’ll link to kits from brands that have worked well for us in the past, but that doesn’t mean they’re better than the many other RAM kits with equivalent specs.

For SSDs, we mostly stick to drives from known brands like Samsung, Crucial, or Western Digital, though going with a lesser-known brand can save you a bit of money. All of our builds also include built-in Bluetooth and Wi-Fi, so you don’t need to worry about running Ethernet wires and can easily connect to Bluetooth gamepads, keyboards, mice, headsets, and other accessories.

We also haven’t priced in peripherals, like webcams, monitors, keyboards, or mice, as we’re assuming most people will re-use what they already have or buy those components separately. If you’re feeling adventurous, you could even make your own DIY keyboard! If you need more guidance, Kimber Streams’ Wirecutter keyboard guides are exhaustive and educational.

Finally, we won’t be including the cost of a Windows license in our cost estimates. You can pay a lot of different prices for Windows—$139 for an official retail license from Microsoft, $120 for an “OEM” license for system builders, or anywhere between $15 and $40 for a product key from shady gray market product key resale sites. Windows 10 keys will also work to activate Windows 11, though Microsoft stopped letting old Windows 7 and Windows 8 keys activate new Windows 10 and 11 installs relatively recently. You could even install Linux, given recent advancements to game compatibility layers!

Ars Technica system guide: Falling prices are more exciting than new parts Read More »

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Nvidia’s AI chips are cheaper to rent in China than US

secondhand channels —

Supply of processors helps Chinese startups advance AI technology despite US restrictions.

Nvidia’s AI chips are cheaper to rent in China than US

VGG | Getty Images

The cost of renting cloud services using Nvidia’s leading artificial intelligence chips is lower in China than in the US, a sign that the advanced processors are easily reaching the Chinese market despite Washington’s export restrictions.

Four small-scale Chinese cloud providers charge local tech groups roughly $6 an hour to use a server with eight Nvidia A100 processors in a base configuration, companies and customers told the Financial Times. Small cloud vendors in the US charge about $10 an hour for the same setup.

The low prices, according to people in the AI and cloud industry, are an indication of plentiful supply of Nvidia chips in China and the circumvention of US measures designed to prevent access to cutting-edge technologies.

The A100 and H100, which is also readily available, are among Nvidia’s most powerful AI accelerators and are used to train the large language models that power AI applications. The Silicon Valley company has been banned from shipping the A100 to China since autumn 2022 and has never been allowed to sell the H100 in the country.

Chip resellers and tech startups said the products were relatively easy to procure. Inventories of the A100 and H100 are openly advertised for sale on Chinese social media and ecommerce sites such as Xiaohongshu and Alibaba’s Taobao, as well as in electronics markets, at slight markups to pricing abroad.

China’s larger cloud operators such as Alibaba and ByteDance, known for their reliability and security, charge double to quadruple the price of smaller local vendors for similar Nvidia A100 servers, according to pricing from the two operators and customers.

After discounts, both Chinese tech giants offer packages for prices comparable to Amazon Web Services, which charges $15 to $32 an hour. Alibaba and ByteDance did not respond to requests for comment.

“The big players have to think about compliance, so they are at a disadvantage. They don’t want to use smuggled chips,” said a Chinese startup founder. “Smaller vendors are less concerned.”

He estimated there were more than 100,000 Nvidia H100 processors in the country based on their widespread availability in the market. The Nvidia chips are each roughly the size of a book, making them relatively easy for smugglers to ferry across borders, undermining Washington’s efforts to limit China’s AI progress.

“We bought our H100s from a company that smuggled them in from Japan,” said a startup founder in the automation field who paid about 500,000 yuan ($70,000) for two cards this year. “They etched off the serial numbers.”

Nvidia said it sold its processors “primarily to well-known partners … who work with us to ensure that all sales comply with US export control rules”.

“Our pre-owned products are available through many second-hand channels,” the company added. “Although we cannot track products after they are sold, if we determine that any customer is violating US export controls, we will take appropriate action.”

The head of a small Chinese cloud vendor said low domestic costs helped offset the higher prices that providers paid for smuggled Nvidia processors. “Engineers are cheap, power is cheap, and competition is fierce,” he said.

In Shenzhen’s Huaqiangbei electronics market, salespeople speaking to the FT quoted the equivalent of $23,000–$30,000 for Nvidia’s H100 plug-in cards. Online sellers quote the equivalent of $31,000–$33,000.

Nvidia charges customers $20,000–$23,000 for H100 chips after recently cutting prices, according to Dylan Patel of SemiAnalysis.

One data center vendor in China said servers made by Silicon Valley’s Supermicro and fitted with eight H100 chips hit a peak selling price of 3.2 million yuan after the Biden administration tightened export restrictions in October. He said prices had since fallen to 2.5 million yuan as supply constraints eased.

Several people involved in the trade said merchants in Malaysia, Japan, and Indonesia often shipped Supermicro servers or Nvidia processors to Hong Kong before bringing them across the border to Shenzhen.

The black market trade depends on difficult-to-counter workarounds to Washington’s export regulations, experts said.

For example, while subsidiaries of Chinese companies are banned from buying advanced AI chips outside the country, their executives could establish new companies in countries such as Japan or Malaysia to make the purchases.

“It’s hard to completely enforce export controls beyond the US border,” said an American sanctions expert. “That’s why the regulations create obligations for the shipper to look into end users and [the] commerce [department] adds companies believed to be flouting the rules to the [banned] entity list.”

Additional reporting by Michael Acton in San Francisco.

© 2024 The Financial Times Ltd. All rights reserved. Please do not copy and paste FT articles and redistribute by email or post to the web.

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DOJ subpoenas Nvidia in deepening AI antitrust probe, report says

DOJ subpoenas Nvidia in deepening AI antitrust probe, report says

The Department of Justice is reportedly deepening its probe into Nvidia. Officials have moved on from merely questioning competitors to subpoenaing Nvidia and other tech companies for evidence that could substantiate allegations that Nvidia is abusing its “dominant position in AI computing,” Bloomberg reported.

When news of the DOJ’s probe into the trillion-dollar company was first reported in June, Fast Company reported that scrutiny was intensifying merely because Nvidia was estimated to control “as much as 90 percent of the market for chips” capable of powering AI models. Experts told Fast Company that the DOJ probe might even be good for Nvidia’s business, noting that the market barely moved when the probe was first announced.

But the market’s confidence seemed to be shaken a little more on Tuesday, when Nvidia lost a “record-setting $279 billion” in market value following Bloomberg’s report. Nvidia’s losses became “the biggest single-day market-cap decline on record,” TheStreet reported.

People close to the DOJ’s investigation told Bloomberg that the DOJ’s “legally binding requests” require competitors “to provide information” on Nvidia’s suspected anticompetitive behaviors as a “dominant provider of AI processors.”

One concern is that Nvidia may be giving “preferential supply and pricing to customers who use its technology exclusively or buy its complete systems,” sources told Bloomberg. The DOJ is also reportedly probing Nvidia’s acquisition of RunAI—suspecting the deal may lock RunAI customers into using Nvidia chips.

Bloomberg’s report builds on a report last month from The Information that said that Advanced Micro Devices Inc. (AMD) and other Nvidia rivals were questioned by the DOJ—as well as third parties who could shed light on whether Nvidia potentially abused its market dominance in AI chips to pressure customers into buying more products.

According to Bloomberg’s sources, the DOJ is worried that “Nvidia is making it harder to switch to other suppliers and penalizes buyers that don’t exclusively use its artificial intelligence chips.”

In a statement to Bloomberg, Nvidia insisted that “Nvidia wins on merit, as reflected in our benchmark results and value to customers, who can choose whatever solution is best for them.” Additionally, Bloomberg noted that following a chip shortage in 2022, Nvidia CEO Jensen Huang has said that his company strives to prevent stockpiling of Nvidia’s coveted AI chips by prioritizing customers “who can make use of his products in ready-to-go data centers.”

Potential threats to Nvidia’s dominance

Despite the slump in shares, Nvidia’s market dominance seems unlikely to wane any time soon after its stock more than doubled this year. In an SEC filing this year, Nvidia bragged that its “accelerated computing ecosystem is bringing AI to every enterprise” with an “ecosystem” spanning “nearly 5 million developers and 40,000 companies.” Nvidia specifically highlighted that “more than 1,600 generative AI companies are building on Nvidia,” and according to Bloomberg, Nvidia will close out 2024 with more profits than the total sales of its closest competitor, AMD.

After the DOJ’s most recent big win, which successfully proved that Google has a monopoly on search, the DOJ appears intent on getting ahead of any tech companies’ ambitions to seize monopoly power and essentially become the Google of the AI industry. In June, DOJ antitrust chief Jonathan Kanter confirmed to the Financial Times that the DOJ is examining “monopoly choke points and the competitive landscape” in AI beyond just scrutinizing Nvidia.

According to Kanter, the DOJ is scrutinizing all aspects of the AI industry—”everything from computing power and the data used to train large language models, to cloud service providers, engineering talent and access to essential hardware such as graphics processing unit chips.” But in particular, the DOJ appears concerned that GPUs like Nvidia’s advanced AI chips remain a “scarce resource.” Kanter told the Financial Times that an “intervention” in “real time” to block a potential monopoly could be “the most meaningful intervention” and the least “invasive” as the AI industry grows.

DOJ subpoenas Nvidia in deepening AI antitrust probe, report says Read More »

nvidia-is-ditching-dedicated-g-sync-modules-to-push-back-against-freesync’s-ubiquity

Nvidia is ditching dedicated G-Sync modules to push back against FreeSync’s ubiquity

sync or swim —

But G-Sync will still require specific G-Sync-capable MediaTek scaler chips.

Nvidia is ditching dedicated G-Sync modules to push back against FreeSync’s ubiquity

Nvidia

Back in 2013, Nvidia introduced a new technology called G-Sync to eliminate screen tearing and stuttering effects and reduce input lag when playing PC games. The company accomplished this by tying your display’s refresh rate to the actual frame rate of the game you were playing, and similar variable refresh-rate (VRR) technology has become a mainstay even in budget monitors and TVs today.

The issue for Nvidia is that G-Sync isn’t what has been driving most of that adoption. G-Sync has always required extra dedicated hardware inside of displays, increasing the costs for both users and monitor manufacturers. The VRR technology in most low-end to mid-range screens these days is usually some version of the royalty-free AMD FreeSync or the similar VESA Adaptive-Sync standard, both of which provide G-Sync’s most important features without requiring extra hardware. Nvidia more or less acknowledged that the free-to-use, cheap-to-implement VRR technologies had won in 2019 when it announced its “G-Sync Compatible” certification tier for FreeSync monitors. The list of G-Sync Compatible screens now vastly outnumbers the list of G-Sync and G-Sync Ultimate screens.

Today, Nvidia is announcing a change that’s meant to keep G-Sync alive as its own separate technology while eliminating the requirement for expensive additional hardware. Nvidia says it’s partnering with chipmaker MediaTek to build G-Sync capabilities directly into scaler chips that MediaTek is creating for upcoming monitors. G-Sync modules ordinarily replace these scaler chips, but they’re entirely separate boards with expensive FPGA chips and dedicated RAM.

These new MediaTek scalers will support all the same features that current dedicated G-Sync modules do. Nvidia says that three G-Sync monitors with MediaTek scaler chips inside will launch “later this year”: the Asus ROG Swift PG27AQNR, the Acer Predator XB273U F5, and the AOC AGON PRO AG276QSG2. These are all 27-inch 1440p displays with maximum refresh rates of 360 Hz.

As of this writing, none of these companies has announced pricing for these displays—the current Asus PG27AQN has a traditional G-Sync module and a 360 Hz refresh rate and currently goes for around $800, so we’d hope for the new version to be significantly cheaper to make good on Nvidia’s claim that the MediaTek chips will reduce costs (or, if they do reduce costs, whether monitor makers are willing to pass those savings on to consumers).

For most people most of the time, there won’t be an appreciable difference between a “true” G-Sync monitor and one that uses FreeSync or Adaptive-Sync, but there are still a few fringe benefits. G-Sync monitors support a refresh rate between 1 and the maximum refresh rate of the monitor, whereas FreeSync and Adaptive-Sync stop working on most displays when the frame rate drops below 40 or 48 frames per second. All G-Sync monitors also support “variable overdrive” technology to help eliminate display ghosting, and the new MediaTek-powered displays will support the recent “G-Sync Pulsar” feature to reduce blur.

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amd-signs-$4.9-billion-deal-to-challenge-nvidia’s-ai-infrastructure-lead

AMD signs $4.9 billion deal to challenge Nvidia’s AI infrastructure lead

chip wars —

Company hopes acquisition of ZT Systems will accelerate adoption of its data center chips.

Visitors walk past the AMD booth at the 2024 Mobile World Congress

AMD has agreed to buy artificial intelligence infrastructure group ZT Systems in a $4.9 billion cash and stock transaction, extending a run of AI investments by the chip company as it seeks to challenge market leader Nvidia.

The California-based group said the acquisition would help accelerate the adoption of its Instinct line of AI data center chips, which compete with Nvidia’s popular graphics processing units (GPUs).

ZT Systems, a private company founded three decades ago, builds custom computing infrastructure for the biggest AI “hyperscalers.” While the company does not disclose its customers, the hyperscalers include the likes of Microsoft, Meta, and Amazon.

The deal marks AMD’s biggest acquisition since it bought Xilinx for $35 billion in 2022.

“It brings a thousand world-class design engineers into our team, it allows us to develop silicon and systems in parallel and, most importantly, get the newest AI infrastructure up and running in data centers as fast as possible,” AMD’s chief executive Lisa Su told the Financial Times.

“It really helps us deploy our technology much faster because this is what our customers are telling us [they need],” Su added.

The transaction is expected to close in the first half of 2025, subject to regulatory approval, after which New Jersey-based ZT Systems will be folded into AMD’s data center business group. The $4.9bn valuation includes up to $400mn contingent on “certain post-closing milestones.”

Citi and Latham & Watkins are advising AMD, while ZT Systems has retained Goldman Sachs and Paul, Weiss.

The move comes as AMD seeks to break Nvidia’s stranglehold on the AI data center chip market, which earlier this year saw Nvidia temporarily become the world’s most valuable company as big tech companies pour billions of dollars into its chips to train and deploy powerful new AI models.

Part of Nvidia’s success stems from its “systems” approach to the AI chip market, offering end-to-end computing infrastructure that includes pre-packaged server racks, networking equipment, and software tools to make it easier for developers to build AI applications on its chips.

AMD’s acquisition shows the chipmaker building out its own “systems” offering. The company rolled out its MI300 line of AI chips last year, and says it will launch its next-generation MI350 chip in 2025 to compete with Nvidia’s new Blackwell line of GPUs.

In May, Microsoft was one of the first AI hyperscalers to adopt the MI300, building it into its Azure cloud platform to run AI models such as OpenAI’s GPT-4. AMD’s quarterly revenue for the chips surpassed $1 billion for the first time in the three months to June 30.

But while AMD has feted the MI300 as its fastest-ever product ramp, its data center revenue still represented a fraction of the $22.6 billion that Nvidia’s data center business raked in for the quarter to the end of April.

In March, ZT Systems announced a partnership with Nvidia to build custom AI infrastructure using its Blackwell chips. “I think we certainly believe ZT as part of AMD will significantly accelerate the adoption of AMD AI solutions,” Su said, but “we have customer commitments and we are certainly going to honour those”.

Su added that she expected regulators’ review of the deal to focus on the US and Europe.

In addition to increasing its research and development spending, AMD says it has invested more than $1 billion over the past year to expand its AI hardware and software ecosystem.

In July the company announced it was acquiring Finnish AI start-up Silo AI for $665 million, the largest acquisition of a privately held AI startup in Europe in a decade.

© 2024 The Financial Times Ltd. All rights reserved. Please do not copy and paste FT articles and redistribute by email or post to the web.

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Your 10-year-old graphics card can run Dragon Age: The Veilguard

Still kicking —

2014’s Nvidia GTX 970 is still a “minimum requirements” workhorse.

At this rate, it might be the only graphics card you'll ever need?

Enlarge / At this rate, it might be the only graphics card you’ll ever need?

When Dragon Age: Inquisition came out nearly 10 years ago, PC players could have invested $329 (~$435 in today’s dollars) in a brand-new GTX 970 graphics card to make the game look as good as possible on their high-end gaming rig. Surprisingly enough, that very same 2014 graphics card will still be able to run follow-up Dragon Age: The Veilguard (previously known as Dreadwolf) when it launches on October 31. If you’re using AMD cards, an even older Radeon R9 that you purchased back in 2013 will be able to run the game.

Veilguard‘s minimum specs are just the latest to show the workmanlike endurance of the humble GTX 970, which is currently available used on Newegg for as low as $140. Relatively recent big-budget PC releases like Baldur’s Gate 3 and Call of Duty: Modern Warfare 3 both use the old card (or the less powerful follow-up variant, the GTX 960) as their “minimum requirement” benchmark.

Not every big-budget PC game these days is so forgiving with its minimum specs, though. When Cyberpunk 2077 and Doom: Eternal launched in 2020, they both asked players to be sporting at least a GTX 1060, which had come out around four years prior.

For a bit of context, the GTX 970 was used as the “recommended” baseline spec for the mid-range “Oculus Ready” PCs needed to power the then-new Rift VR headset when it launched in 2016. Today, a $500 Meta Quest 3 headset gives you much better graphical performance in a self-contained portable package, no gaming PC required.

Veilguard players sticking with a GTX 970 shouldn’t expect to get the best graphical experience, of course. EA suggests an RTX 2070 (circa 2018) or a Radeon RX 5700Xt (circa 2019) to run the game at “recommended” specs. And you’ll need at least 16 GB of RAM and 100 GB of storage space.

Since work on Veilguard began in earnest in 2015, the game has suffered a string of high-profile staff departures: Creative Director Mike Laidlaw left in 2017; Executive Producer Mark Darrah and BioWare General Manager Casey Hudson left in late 2020; Senior Creative Director Matt Goldman left in late 2021; replacement Executive Producer Christian Daley left in early 2022; and producer Mac Walters left in early 2023.

The full requirements for Dragon Age: The Veilguard are as follows.

Minimum Requirements

OS: Windows 10/11 64-bit

Processor: Intel Core i5-8400 / AMD Ryzen 3 3300X(see notes)

Memory: 16GB

Graphics: Nvidia GTX 970/1650 / AMD Radeon R9 290X

DirectX: Version 12

Storage: 100GB available space

Additional Notes: SSD preferred, HDD supported; AMD CPUs on Windows 11 require AGESA V2 1.2.0.7

Recommended Requirements

OS: Windows 10/11 64-bit

Processor: Intel Core i9-9900K / AMD Ryzen 7 3700X (see notes)

Memory: 16GB

Graphics: Nvidia RTX 2070 / AMD Radeon RX 5700XT

DirectX: Version 12

Storage: 100GB SSD available space

Additional Notes: SSD required; AMD CPUs on Windows 11 require AGESA V2 1.2.0.7

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us-probes-nvidia’s-acquisition-of-israeli-ai-startup

US probes Nvidia’s acquisition of Israeli AI startup

“monopoly choke points” —

Justice Department has increased scrutiny of the chipmaker’s power in the emerging sector.

US probes Nvidia’s acquisition of Israeli AI startup

Getty Images

The US Department of Justice is investigating Nvidia’s acquisition of Run:ai, an Israeli artificial intelligence startup, for potential antitrust violations, said a person familiar with discussions the government agency has had with third parties.

The DoJ has asked market participants about the competitive impact of the transaction, which Nvidia announced in April. The price was not disclosed but a report from TechCrunch estimated it at $700 million.

The scope of the probe remains unclear, the person said. But the DoJ has inquired about matters including whether the deal could quash emerging competition in the up-and-coming sector and entrench Nvidia’s dominant market position.

Nvidia on Thursday said the company “wins on merit” and “scrupulously adher[es] to all laws.”

“We’ll continue to support aspiring innovators in every industry and market and are happy to provide any information regulators need,” it added.

Run:ai did not immediately respond to a request for comment. The DoJ declined to comment.

The investigation comes as US regulators and enforcers have heightened scrutiny of anti-competitive behavior in AI, particularly where it dovetails with big tech groups such as Nvidia.

Jonathan Kanter, head of the DoJ’s antitrust division, told the Financial Times in June that he was examining “monopoly choke points” in areas including the data used to train large language models as well as access to essential hardware such as graphics processing unit chips. He added that the GPUs needed to train LLMs had become a “scarce resource.”

Nvidia dominates sales of the most advanced GPUs. Run:ai, which had an existing collaboration with the tech giant, has developed a platform that optimizes the use of GPUs.

As part of the probe, which was first reported by Politico, the DoJ is seeking information on how Nvidia decides the allocation of its chips, the person said.

Government lawyers are also inquiring about Nvidia’s software platform, Cuda, which enables chips originally designed for graphics to speed up AI applications and is seen by industry figures as one of Nvidia’s most critical tools.

The DoJ and the US Federal Trade Commission, a competition regulator, in June reached an agreement that divided antitrust oversight of critical AI players. The DoJ will spearhead probes into Nvidia, while the FTC will oversee the assessment of Microsoft and OpenAI, the startup behind ChatGPT.

© 2024 The Financial Times Ltd. All rights reserved. Please do not copy and paste FT articles and redistribute by email or post to the web.

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ai’s-future-in-grave-danger-from-nvidia’s-chokehold-on-chips,-groups-warn

AI’s future in grave danger from Nvidia’s chokehold on chips, groups warn

Controlling “the world’s computing destiny” —

Anti-monopoly groups want DOJ to probe Nvidia’s AI chip bundling, alleged price-fixing.

AI’s future in grave danger from Nvidia’s chokehold on chips, groups warn

Sen. Elizabeth Warren (D-Mass.) has joined progressive groups—including Demand Progress, Open Markets Institute, and the Tech Oversight Project—pressuring the US Department of Justice to investigate Nvidia’s dominance in the AI chip market due to alleged antitrust concerns, Reuters reported.

In a letter to the DOJ’s chief antitrust enforcer, Jonathan Kanter, groups demanding more Big Tech oversight raised alarms that Nvidia’s top rivals apparently “are struggling to gain traction” because “Nvidia’s near-absolute dominance of the market is difficult to counter” and “funders are wary of backing its rivals.”

Nvidia is currently “the world’s most valuable public company,” their letter said, worth more than $3 trillion after taking near-total control of the high-performance AI chip market. Particularly “astonishing,” the letter said, was Nvidia’s dominance in the market for GPU accelerator chips, which are at the heart of today’s leading AI. Groups urged Kanter to probe Nvidia’s business practices to ensure that rivals aren’t permanently blocked from competing.

According to the advocacy groups that strongly oppose Big Tech monopolies, Nvidia “now holds an 80 percent overall global market share in GPU chips and a 98 percent share in the data center market.” This “puts it in a position to crowd out competitors and set global pricing and the terms of trade,” the letter warned.

Earlier this year, inside sources reported that the DOJ and the Federal Trade Commission reached a deal where the DOJ would probe Nvidia’s alleged anti-competitive behavior in the booming AI industry, and the FTC would probe OpenAI and Microsoft. But there has been no official Nvidia probe announced, prompting progressive groups to push harder for the DOJ to recognize what they view as a “dire danger to the open market” that “well deserves DOJ scrutiny.”

Ultimately, the advocacy groups told Kanter that they fear Nvidia wielding “control over the world’s computing destiny,” noting that Nvidia’s cloud computing data centers don’t just power “Big Tech’s consumer products” but also “underpin every aspect of contemporary society, including the financial system, logistics, healthcare, and defense.”

They claimed that Nvidia is “leveraging” its “scarce chips” to force customers to buy its “chips, networking, and programming software as a package.” Such bundling and “price-fixing,” their letter warned, appear to be “the same kinds of anti-competitive tactics that the courts, in response to actions brought by the Department of Justice against other companies, have found to be illegal” and could perhaps “stifle innovation.”

Although data from TechInsights suggested that Nvidia’s chip shortage and cost actually helped companies like AMD and Intel sell chips in 2023, both Nvidia rivals reported losses in market share earlier this year, Yahoo Finance reported.

Perhaps most closely monitoring Nvidia’s dominance, France antitrust authorities launched an investigation into Nvidia last month over antitrust concerns, the letter said, “making it the first enforcer to act against the computer chip maker,” Reuters reported.

Since then, the European Union and the United Kingdom, as well as the US, have heightened scrutiny, but their seeming lag to follow through with an official investigation may only embolden Nvidia, as the company allegedly “believes its market behavior is above the law,” the progressive groups wrote. Suspicious behavior includes allegations that “Nvidia has continued to sell chips to Chinese customers and provide them computing access” despite a “Department of Commerce ban on trading with Chinese companies due to national security and human rights concerns.”

“Its chips have been confirmed to be reaching blacklisted Chinese entities,” their letter warned, citing a Wall Street Journal report.

Nvidia’s dominance apparently impacts everyone involved with AI. According to the letter, Nvidia seemingly “determining who receives inventory from a limited supply, setting premium pricing, and contractually blocking customers from doing business with competitors” is “alarming” the entire AI industry. That includes “both small companies (who find their supply choked off) and the Big Tech AI giants.”

Kanter will likely be receptive to the letter. In June, Fast Company reported that Kanter told an audience at an AI conference that there are “structures and trends in AI that should give us pause.” He further suggested that any technology that “relies on massive amounts of data and computing power” can “give already dominant firms a substantial advantage,” according to Fast Company’s summary of his remarks.

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