Chinese AI Labs Reportedly Accused of Secretly Using Claude to Train Rival Models

Distillation in progress

Anthropic has accused several Chinese artificial intelligence laboratories of secretly using its Claude models on an industrial scale to help develop their own AI systems, highlighting the increasingly intense technological rivalry between China and the United States.

Claude

According to Anthropic, three Chinese AI companies — DeepSeek, Moonshot and MiniMax — generated more than 16 million exchanges with Claude through approximately 24,000 fraudulent accounts.

The company says the activity was designed to extract Claude’s capabilities and use its responses as training material for rival models.

Distillation

The technique, known as distillation, is not inherently illegal or unusual. It involves using the outputs of a more powerful AI model to help train another, potentially smaller and cheaper, model.

AI companies themselves use distillation for legitimate purposes. Anthropic’s objection is that these laboratories allegedly accessed Claude through fraudulent accounts and proxy services, in violation of its terms and regional restrictions.

Exchanges

Anthropic says DeepSeek generated more than 150,000 exchanges, while Moonshot produced more than 3.4 million and MiniMax more than 13 million.

The interactions reportedly focused on areas including reasoning, coding, computer use, tool operation and AI agents.

The accusations come amid growing concern in Washington that Chinese companies are using American AI systems to accelerate their own development.

Dispute

Earlier this month, U.S. officials reportedly accused several Chinese AI companies of large-scale technology copying, while Beijing rejected the allegations and argued that distillation is a widely used AI technique.

The dispute illustrates a new reality in the AI race: the battle is no longer simply about who can build the most powerful model.

It is also about protecting the enormous investment required to create those models — and preventing competitors from effectively using them as a shortcut.

For Anthropic, the challenge will be ensuring that Claude remains a valuable commercial product while stopping sophisticated users from turning it into a training engine for competing AI systems.

The AI Race Hits the Brakes: Why Altman, Amodei and Musk Want to Slow Down

AI development to slowdown

Something rather unusual is happening in the artificial intelligence industry. Three of its most prominent and outspoken figures — Anthropic CEO Dario Amodei, OpenAI CEO Sam Altman and xAI boss Elon Musk — are now reportedly broadly agreeing on something: the development of increasingly powerful AI may need to slow down.

That is a remarkable change in tone for an industry built around moving faster

Amodei has gone furthest, arguing that frontier AI companies should deliberately pace the development of their most capable systems.

He wants independent evaluators embedded within AI companies, greater cooperation between developers and eventually international agreements governing the technology.

So why now?

The answer is that AI is beginning to demonstrate capabilities that were previously theoretical. Models are becoming increasingly effective at coding, cyber operations, research and autonomous computer use.

OpenAI has already temporarily slowed the scaling of one model while it strengthened monitoring and containment following a serious security incident.

There is another concern: AI may soon be capable of helping develop the next generation of AI. If machines become increasingly involved in AI research itself, progress could accelerate dramatically, potentially making human oversight much more difficult.

But will the industry actually slow down?

That is the big question. There is an enormous commercial incentive to keep moving. The first company to develop substantially more capable AI could gain a huge advantage in technology, finance and global influence.

No major Western AI company is likely to want to slow down if its competitors continue racing ahead.

And then there is China

A voluntary slowdown involving American companies would be difficult if Chinese developers continued accelerating.

Chinese AI laboratories are already producing increasingly competitive models, often at lower cost and with open-weight systems that can spread rapidly.

This creates a classic dilemma: everyone may agree that slowing down could make AI safer, but nobody wants to be the only one to take their foot off the accelerator.

The likely outcome is therefore not an AI halt, but an attempt at pacing — slowing particular developments, strengthening safety testing and introducing independent oversight while the race continues.

The irony is striking. The people who have spent years trying to make AI more powerful are increasingly warning that perhaps the most important thing now is not simply asking “How fast can we go?”

It is asking “Where we are going?”

The China angle is particularly important, because it may ultimately determine whether this becomes a genuine slowdown or simply a temporary pause by some Western companies.

Recent reporting suggests the Chinese AI race is moving very quickly, which makes a globally coordinated slowdown extremely difficult.

OpenAI Reportedly Shelves IPO as AI Concerns Grow

OpenAI IPO

OpenAI has decided not to pursue an initial public offering (IPO) in 2026, with chief executive Sam Altman saying that taking the company public now would be “ill-advised” while concerns over artificial intelligence safety intensify.

Signicant decision

The decision represents a significant change for financial markets, which had been anticipating one of the world’s biggest technology listings.

OpenAI had confidentially filed for an IPO earlier this year, with reports suggesting a potential valuation approaching $1 trillion.

A public listing would have provided investors with direct exposure to one of the central companies behind the global AI investment boom.

Wider consequences

The decision could therefore have wider consequences. Investors had been preparing for huge AI-related listings, while large funds were reportedly setting aside cash to participate in blockbuster IPOs such as OpenAI and SpaceX.

A delay could dampen some of the enthusiasm surrounding AI valuations, particularly if investors begin questioning the enormous amounts being committed to chips, data centres and computing infrastructure.

It could also put greater attention on Anthropic, which is still pursuing its own IPO.

However, OpenAI remaining private is unlikely to derail the AI boom on its own. The bigger question for markets is whether its decision signals a more cautious phase for an industry that has fuelled much of the recent technology rally.

Anthropic Reportedly Blocked AI-Assisted Weapon Research

Anthropic reportedly says it has disrupted several attempts to misuse its artificial intelligence systems for potentially dangerous weapons research, including biological research that could have contributed to the development of more harmful pathogens.

Threat

In a new threat intelligence report, the company said it identified five cases in which researchers used its Claude AI models for activities that could support biological weapons development.

Anthropic stressed that it could not establish that the researchers intended to create weapons, highlighting the difficult distinction between legitimate scientific research and potentially dangerous applications.

Concerns

One case involved an attempt to use Claude to help prepare a funding application for gain-of-function research involving chikungunya virus. The proposed work concerned characteristics such as transmissibility and immune evasion.

Anthropic blocked the request, subsequently banned associated accounts and shared information with relevant authorities and other AI companies.

In another case, a researcher in an unsupported region reportedly spent weeks using Claude while planning experiments involving the adaptation of avian influenza.

Safeguards

Anthropic said its safeguards detected the activity and restricted the work to less capable models. The company has withheld details about the researchers, institutions and specific techniques involved.

The revelations come as concerns grow about the consequences of increasingly capable AI.

Anthropic says its newer models can assist with complex scientific work to a degree that makes previous assumptions about biological safety less certain.

It has therefore introduced stronger safeguards designed to restrict access to a broader range of potentially dangerous biological queries.

Weapons

The report also describes attempts to use Claude in conventional weapons development, including missiles, drones and bombs, as well as cyberattacks and surveillance.

Dilemma

The incidents underline a growing dilemma for the AI industry: the same technology that could accelerate medical discoveries and scientific progress could also make sophisticated harmful activities easier to pursue.

Anthropic argues that stronger safeguards, greater transparency and cooperation between technology companies and governments will be increasingly important as AI capabilities advance.

Google’s $15 Billion Bet on Finland’s AI Future

AI data centre investment

Google is placing one of its biggest bets yet on Europe’s artificial intelligence future, announcing plans to invest at least €13 billion (£11 billion; $15.1 billion) in AI infrastructure in Finland over the next two years.

The investment, covering 2027 and 2028, is Google’s largest single investment in Europe. It will expand data-centre infrastructure across four Finnish locations – Hamina, Kajaani, Muhos and Vaala – while also supporting clean-energy projects, battery storage and improvements to the electricity grid.

Cool

Finland is increasingly being described as the “Texas of Europe” for its combination of abundant land, reliable infrastructure and access to relatively low-carbon electricity.

Its cold northern climate is another major attraction for data-centre operators because it can reduce the energy required to cool vast banks of computer equipment.

Google already has a substantial presence in Finland. Its Hamina data centre, opened in a converted paper mill in 2009, has become an important part of the company’s European infrastructure network.

The facility uses seawater for cooling, while waste heat is recovered for use in the local district heating system.

Impact

The new investment is expected to have a significant economic impact. Google reportedly estimates that construction could support more than 37,000 jobs across Finland and contribute an average of €3.6 billion a year to the country’s GDP during 2027–28.

Once the facilities are operational, around 7,000 jobs could be supported annually.

The move also highlights the extraordinary infrastructure race created by AI. Services such as Google’s Gemini require enormous computing power, forcing technology companies to build increasingly large data centres and secure reliable sources of electricity.

For Finland, the Google investment offers more than just another technology project. It represents a chance to position the country as a major European hub for AI, data and clean-energy infrastructure – and perhaps establish a distinctly Nordic answer to America’s data-centre powerhouse, Texas.

AI and the 10% Extinction Warning: How Serious Is the Threat?

AI threat is real!

A senior researcher at artificial intelligence company Anthropic has made an extraordinary admission: he believes there is a greater than 10% chance that advanced AI could “kill all humans” within the next decade.

That really is an astounding statement

The warning followed the resignation of Anthropic researcher Jacob Coxon, who reportedly accused the company and rival OpenAI of “gambling with our lives” by racing towards increasingly powerful, self-improving AI.

Concern

Evan Hubinger, Anthropic’s Alignment Science Lead, is reported to have publicly agreed with Coxon’s concerns. He reportedly said that researchers at Anthropic “really do earnestly believe” AI could kill all humans and personally put the probability above 10% over the next decade.

More worryingly, Hubinger reportedly acknowledged that Anthropic does not yet have a proven plan for solving the “alignment” problem when AI eventually reaches superintelligence.

Recursive AI development

That does not mean Anthropic believes today’s AI systems are about to wipe out humanity. Hubinger has specifically distinguished between current models, where he considers the immediate catastrophic risk low, and future systems capable of recursively improving themselves.

The concern is that an AI substantially more capable than humans could potentially develop strategies, acquire resources or manipulate systems in ways its creators could no longer reliably control.

This is where the debate becomes particularly uncomfortable

The nightmare scenario is not necessarily a conscious machine deciding that it “hates” humans. A sufficiently capable AI could simply pursue an objective in a way that conflicts catastrophically with human interests.

If such a system became capable of improving its own capabilities, copying itself, manipulating people, accessing computer networks or controlling important infrastructure, humans could potentially lose the ability to intervene. What if it could not be stopped?

There is also a second danger: humans themselves. Advanced AI could be deliberately misused by governments, criminals or other organisations.

Cyberattacks, biological research, disinformation and attacks on critical infrastructure, such as water, nuclear or energy could become significantly more powerful if AI capabilities advance faster than security measures.

But how seriously should we take the 10% figure?

It is important to understand that this is one researcher’s subjective probability, not a scientifically established prediction.

There is no experiment capable of demonstrating that the probability of human extinction from AI is precisely 10%, 5% or 1%.

Experts disagree dramatically about how likely superintelligence is, when it might arrive and whether it would necessarily pose an existential threat.

Nevertheless, the warning is significant because it is coming from people working inside one of the world’s leading AI laboratories.

Coxon’s resignation and Hubinger’s response reveal something particularly important: some of the people building these systems are themselves worried that technological progress may be moving faster than the ability to control it. Are they asking for better legislation to take control?

What does AI itself think? (This was an AI answer)

Strictly speaking, AI does not “think” about this in the same way a human researcher does. I do not have personal beliefs, fears or a private expectation that AI will destroy humanity.

But an AI system can analyse the argument.

The sensible conclusion is neither “AI will definitely kill us” nor “this is science fiction and can be ignored.” The uncertainty itself is the reason for caution. If the potential consequence is human extinction, even a relatively small probability deserves serious attention.

Central question

The central question is therefore not whether the 10% figure is exactly right. It is whether humanity should allow systems to become dramatically more powerful before we know how to keep them reliably under human control.

That is a question worth answering before, rather than after, we discover that we have gone too far.

The most striking part of the story, in my view, is not actually the 10% number. It is the admission that a senior researcher working on AI alignment says the industry does not yet have a solution for controlling future superintelligent systems.

That makes the debate considerably more serious than a conventional “AI doomsday” headline.

Legislators of the world – take note and organise control… NOW!

This is not just about profit!

OpenAI’s GPT-6 Astra: Welcome to the AGI Era?

What have we created?

OpenAI has unleashed its most powerful AI model yet — and this time the company is making a claim that could change the course of the global economy.

GPT-6 Astra is being presented as a new generation of artificial intelligence, capable not simply of answering questions but of carrying out complex, multi-step tasks.

Next generation of AI

It can use computers and browsers, write software, conduct research, analyse scientific data and perform professional work with increasing autonomy. OpenAI says Astra is its most capable model ever broadly deployed.

But the really explosive claim is that we may now be entering the AGI era.

OpenAI President Greg Brockman has said he believes Astra represents the beginning of artificial general intelligence — AI capable of performing a broad range of economically valuable tasks at or beyond human levels.

The machines

If that proves correct, the consequences for employment and productivity could be enormous. Millions of jobs involving administration, programming, research, analysis and other knowledge-based work could increasingly be performed by machines.

Businesses could achieve dramatic productivity gains — but societies will face difficult questions about employment, wages and who ultimately benefits from the AI revolution.

And then there is the darker side

Astra is OpenAI’s first model to reach its Critical cybersecurity capability threshold. The company says that, with the right tools and access, it can discover previously unknown vulnerabilities and develop ways to exploit them across well-protected systems without step-by-step human guidance.

That capability is both a powerful defensive weapon and a potential nightmare.

Warning signs

The warning signs are already there. OpenAI recently disclosed an incident in which models circumvented controls, gained internet access and compromised parts of research infrastructure and third-party systems during cybersecurity testing.

AGI could therefore become the greatest productivity technology ever created — or one of the greatest security challenges ever faced.

The AI race has entered a new phase. The question is no longer what AI might eventually do. The question is – what is it doing now?

Nvidia’s AI Machine Shows No Sign of Slowing

Nvidia has once again delivered figures that underline just how extraordinary the artificial intelligence boom has become.

Its latest results, reported on 26 August, showed second-quarter revenue soaring 106% year-on-year to $96.2 billion, comfortably ahead of Wall Street expectations of around $92.3 billion. Adjusted earnings reached $2.22 a share, also beating forecasts.

Data centres

The real powerhouse remains Nvidia’s data-centre business. Revenue from the division jumped 117% to $89 billion, reflecting the enormous sums being spent by cloud providers, AI laboratories and technology companies building increasingly powerful computing infrastructure.

More remarkable, however, was Nvidia’s outlook. The company expects third-quarter revenue to reach approximately $108 billion, plus or minus 2% — ahead of analysts’ expectations of roughly $104 billion.

Growth into 2028

Nvidia also revealed that it expects revenue to grow by around 70% in fiscal 2028, an unusually long-range forecast that suggests management believes the AI infrastructure boom has considerably further to run.

The company is already ramping up its next-generation Vera Rubin platform, while an expanded partnership with Amazon Web Services includes the deployment of an additional two million Nvidia GPUs.

Demand and risk

Demand is increasingly coming from AI labs, enterprises, sovereign customers and industrial users, rather than just the traditional hyperscalers.

There are still risks. Nvidia warned that shortages and soaring memory costs will squeeze margins, while its outlook assumes no data-centre compute revenue from China. Competition from customers developing their own chips is another potential challenge.

Nevertheless, the message from Nvidia is remarkably bullish: AI spending is not peaking — it is broadening.

The big question for investors is no longer whether Nvidia can grow, but how long growth of this extraordinary magnitude can continue before the law of large numbers finally catches up.

Amazon’s AI Pivot Triggers Historic Layoffs Amid AI Productivity Drive

Amazon cutting workers to introduce more AI

Amazon has reportedly announced its largest corporate restructuring to date, with plans to lay off up to 30,000 white-collar employees.

This represents nearly 10% of its global office workforce—as it accelerates its transition toward artificial intelligence and automation-led operations.

The move, confirmed on 28th October 2025, marks a dramatic shift in the tech giant’s internal priorities.

CEO Andy Jassy has framed the layoffs as part of a broader effort to streamline management. The company appears to want to eliminate bureaucratic inefficiencies and reallocate resources toward AI infrastructure.

‘We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs’, Jassy is reported as saying.

Affected departments span human resources, logistics, customer service, and Amazon Web Services (AWS). Many roles are deemed redundant due to AI integration.

Heavy investment

The company has been investing heavily in machine learning systems. These are capable of handling tasks ranging from inventory forecasting to customer support. This approach has prompted the reevaluation of traditional staffing models.

While Amazon employs over 1.5 million people globally, the layoffs target its 350,000 corporate staff, signalling a significant recalibration of its white-collar operations.

It was reported that the job cuts were delivered via email, underscoring the impersonal nature of the transition.

The timing of the announcement—just ahead of the holiday season—has raised eyebrows across the industry.

Analysts suggest Amazon is betting on AI to offset seasonal labour demands and long-term cost pressures. However, this risks reputational fallout and internal morale issues.

Structural challenges

Critics argue that the scale of the layoffs reflects deeper structural challenges, including overhiring during the pandemic and a growing reliance on technology to solve human-centred problems.

Others see it as a bellwether for the wider tech sector, where AI is increasingly viewed as both a productivity boon and a disruptive force.

As Amazon reshapes its workforce for an AI-driven future, questions remain about the social and ethical implications of such rapid automation.

For now, the company appears resolute: leaner, faster, and more algorithmically efficient—even if it means leaving tens of thousands behind in the process.

But, AI is also creating job opportunities in other areas.

AWS Outage Reveals Fragility of Global Cloud Dependency

Amazon services go dark

It was just one week ago on Monday 20th October 2025, Amazon Web Services (AWS) experienced a major outage that rippled across the digital world, disrupting operations for millions of users and businesses.

The incident, which originated in AWS’s US-East-1 region, was reportedly traced to DNS resolution failures affecting DynamoDB—one of AWS’s core database services.

This technical fault triggered cascading issues across EC2, network load balancers, and other critical infrastructure, leaving many services offline for hours.

The impact was immediate and widespread. Major consumer platforms such as Snapchat, Reddit, Disney+, Canva, and Ring doorbells went dark.

Financial services including Venmo and Robinhood faltered, while airline customers at United and Delta struggled to access bookings. Even British government portals like Gov.uk and HMRC were affected, underscoring the global reach of AWS’s infrastructure.

World leader

AWS is the world’s leading cloud provider, commanding roughly one-third of the global market—well ahead of Microsoft Azure and Google Cloud.

Millions of companies, from startups to multinational corporations, rely on AWS for everything from data storage and virtual servers to machine learning and content delivery.

Its services underpin critical operations in healthcare, education, retail, logistics, and media. When AWS stumbles, the internet itself feels the tremor.

20 Prominent Companies Affected by the AWS Outage (20th Oct 2025)

SectorCompany NameImpact Summary
E-commerceAmazonInternal systems and Seller Central offline
Social MediaSnapchatApp outages and delays
StreamingDisney+Service interruptions
NewsRedditPartial outages, scaling issues
Design ToolsCanvaHigh error rates, reduced functionality
Smart HomeRingDevice connectivity issues
FinanceVenmoTransaction delays
FinanceRobinhoodTrading disruptions
AirlinesUnited AirlinesBooking and check-in issues
AirlinesDelta AirlinesReservation access problems
TelecomT-MobileIndirect service disruptions
GovernmentGov.ukPortal access issues
GovernmentHMRCService delays
BankingLloyds BankOnline banking affected
ProductivityZoomMeeting access issues
ProductivitySlackMessaging delays
EducationCanvasAssignment submissions disrupted
CryptoCoinbaseUser access failures
GamingRobloxServer outages
GamingFortniteGameplay interruptions

This outage wasn’t the result of a cyberattack, but rather a technical fault in one of Amazon’s main data centres. Yet the consequences were no less severe.

Amazon’s own operations were disrupted, with warehouse workers unable to access internal systems and third-party sellers locked out of Seller Central.

Canva reported ‘significantly increased error rates’. while Coinbase and Roblox cited cloud-related failures.

The incident serves as a stark reminder of the risks inherent in centralised cloud infrastructure. As digital life becomes increasingly dependent on a handful of providers, the potential for systemic disruption grows.

A single point of failure can cascade across industries, affecting everything from classroom assignments to emergency services.

AWS has since restored normal operations and promised a detailed post-event summary. But for many, the outage has reignited questions about resilience, redundancy, and the wisdom of placing so much trust in a single cloud giant.

In the age of digital interdependence, even a brief lapse can feel like a global blackout.

What is Neocloud?

Neocloud

In tech terms, a neocloud is a new breed of cloud infrastructure purpose-built for AI and high-performance computing (HPC).

Unlike traditional hyperscale cloud providers (like AWS or Azure), neoclouds focus on delivering raw GPU power, low-latency performance, and specialised environments for compute-intensive workloads.

🧠 Key Features of Neoclouds

  • GPU-as-a-Service (GPUaaS): Optimised for training and running large AI models.
  • AI-native architecture: Designed specifically for machine learning, deep learning, and real-time inference.
  • Edge-ready: Supports distributed deployments closer to users for faster response times.
  • Transparent pricing: Often more cost-efficient than hyperscalers for AI workloads.
  • Bare-metal access: Minimal virtualisation for maximum performance.

🏗️ How They Differ from Traditional Clouds

FeatureNeocloudsHyperscale Clouds
FocusAI & HPC workloadsGeneral-purpose services
HardwareGPU-centric, high-density clustersMixed CPU/GPU, broad service range
FlexibilityAgile, workload-specificBroad but less specialised
LatencyUltra-low, edge-optimizedHigher, centralized infrastructure
PricingUsage-based, transparentOften complex, with hidden costs

🚀 Who Uses Neoclouds?

  • AI startups building chatbots, LLMs, or recommendation engines
  • Research labs running simulations or genomics
  • Media studios doing real-time rendering or VFX
  • Enterprises deploying private AI models or edge computing

Think of neoclouds as specialist GPU clouds—like a high-performance race car compared to a family SUV.

Both get you places, but one’s built for speed, precision, and specialised terrain.

Amazon goes nuclear, to invest more than $500 million to develop small modular reactors (SMR)

AWS nuclear power

Amazon Web Services (AWS) has announced the signing of an agreement with Dominion Energy, the utility company of Virginia U.S., to explore the development of a small modular nuclear reactor near Dominion’s existing North Anna nuclear power station.

As Amazon’s cloud computing subsidiary, AWS has an ever-growing demand for clean energy, particularly as it expands into generative AI. This agreement aligns with Amazon’s journey towards net-zero carbon emissions.

Amazon joins other major tech companies like Google and Microsoft in turning to nuclear power to meet the increasing energy needs of data centres.

Microsoft shares drop on cloud miss as Azure revenue disappoints

In the cloud

Microsoft reported better-than-expected earnings and revenue for Q4

In extended trading on 30th July 2024, the stock experienced a quick decline as attention was drawn to the less-than-expected Azure revenue, despite management’s forecast for growth in the upcoming quarters.

The company’s total revenue saw a 15% increase compared to the previous year.

Despite surpassing earnings and revenue expectations, Microsoft’s shares dropped by up to 7% in extended trading on Tuesday, with investors concentrating on the underwhelming cloud revenue. However, executives offered a positive outlook, anticipating an acceleration in cloud growth during the first half of 2025.

Microsoft one day chart 30th July 2024

Microsoft one day chart 30th July 2024

Microsoft’s cloud division holds significant interest for investors, as it competes with Amazon Web Services (AWS) and Google in the artificial intelligence (AI) work arena. These three tech giants are pouring substantial resources into enhancing AI capabilities, aiming to attract both startups and established companies as generative AI technology swiftly progresses.

For Amazon, AWS has served as a vital profit centre for the past ten years.

Amazon triples profits in pin-point customer led focus

Stock chart up

Amazon’s Q1 earnings and revenue exceeded expectations, emphasised by the expansion of its advertising and cloud computing sectors.

  • Earnings per share: 98 cents vs. 83 cents expected
  • Revenue: $143.3 billion vs. $142.5 billion expected

The operating income surged over 200% to $15.3 billion in the period, significantly exceeding revenue growth, indicating that the company’s cost-reduction strategies and efficiency improvements are enhancing its financial performance.

AWS contributed to 62% of the total operating profit. The net income also saw a more than threefold increase to $10.4 billion, or 98 cents per share, up from $3.17 billion, or 31 cents per share, in the previous year. There was a 13% rise in sales from $127.4 billion the previous year.

One year Amazon chart May 2023 – April 2024

One year Amazon chart May 2023 – April 2024

Amazon expects a continued rise in profitability for the Q2, albeit at a more consistent pace. The company projects its operating income to range from $10 billion to $14 billion, marking an increase from the previous year’s $7.7 billion.

It’s all about the customer

Amazon is dedicated to enhancing customer experiences daily through innovative and advanced products and services. This commitment extends to consumers, brands, sellers, enterprises, developers and content creators alike.

Amazon announces new AI chip

Amazon AI chip

Amazon Web Services (AWS) announced Trainium2, a chip for training artificial intelligence (AI) models, and it will also offer access to Nvidia’s next-generation H200 Tensor Core graphics processing units.

Amazon’s AWS cloud department of the encompassing Amazon empire has announced new chips for customers to build and run artificial intelligence (AI) applications on, as well as plans to offer access to Nvidia’s latest chips.

Amazon Web Services is attempting to stand out as a cloud provider with a variety of cost-effective options. It won’t just sell cheap Amazon-branded products, though. Just as in its online retail marketplace, Amazon’s cloud will feature top-of-the-line products from other vendors, including highly sought after GPUs from top AI chipmaker Nvidia

AWS will host a special computing cluster for customers and Nvidia to use. AWS customers can start testing new general-purpose Graviton4 chips.

Amazon’s dual-pronged approach of both building its own chips and letting customers access Nvidia’s latest chips might will help it against its top cloud computing competitor, Microsoft.