OpenAI and AMD strike 6GW GPU deal to power next-generation AI infrastructure

AMD and OpenAI have announced a strategic partnership to deploy up to six gigawatts of AMD GPUs, marking one of the largest AI compute collaborations.

The multi-year agreement will begin with the rollout of one gigawatt of AMD Instinct MI450 GPUs in the second half of 2026, with further deployments planned across future AMD generations.

A deal that deepens a long-standing relationship between the two companies began with AMD’s MI300X and MI350X series.

OpenAI will adopt AMD as a core strategic compute partner, integrating its technology into large-scale AI systems and jointly optimising product roadmaps to support next-generation AI workloads.

To strengthen alignment, AMD has issued OpenAI a warrant for up to 160 million shares, with tranches vesting as the partnership achieves deployment and share-price milestones. AMD expects the collaboration to deliver tens of billions in revenue and boost its non-GAAP earnings per share.

AMD CEO Dr Lisa Su called the deal ‘a true win-win’ for both companies, while OpenAI’s Sam Altman said the partnership will ‘accelerate progress and bring advanced AI benefits to everyone faster’.

The collaboration positions AMD as a leading hardware supplier in the race to build global-scale AI infrastructure.

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Italy passes Europe’s first national AI law

Italy has become the first EU country to pass a national AI law, introducing detailed rules to govern the development and use of AI technologies across key sectors such as health, work, and justice.

The law, approved by the Senate on 17 September and in effect on 10 October, defines new national authorities responsible for oversight, including the Agency for Digital Italy and the National Cybersecurity Agency. Both bodies will supervise compliance, security, and responsible use of AI systems.

In healthcare, the law simplifies data-sharing for scientific research by allowing the secondary use of anonymised or pseudonymised patient data. New rules also ensure transparency and consent when AI is used by minors under 14.

The law introduces criminal penalties for those who use AI-generated images or videos to cause harm or deception. The Italian approach combines regulation with innovation, seeking to protect citizens while promoting responsible growth in AI development.

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AI-designed proteins surpass nature in genome editing

Researchers in Barcelona have developed synthetic proteins using generative AI that outperform natural ones at editing the human genome. The breakthrough, published in Nature Biotechnology, could transform treatments for cancer and rare genetic diseases.

The team from Integra Therapeutics, UPF and the CRG screened over 31,000 eukaryotic genomes, identifying more than 13,000 previously unknown PiggyBac transposase sequences. Experimental tests revealed ten active variants, two matching or exceeding current lab-optimised versions.

In the next phase, scientists trained a protein large language model on the newly discovered sequences to create entirely new proteins with improved genome-editing precision. The AI-generated enzymes worked efficiently in human T cells and proved compatible with Integra’s FiCAT gene-editing platform.

The Spanish researchers say the approach shows AI can expand biology’s own toolkit. By understanding the molecular ‘grammar’ of proteins, the model produced novel sequences that remain structurally and functionally sound.

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OpenAI backs policy push for Europe’s AI uptake

OpenAI and Allied for Startups have released Hacktivate AI, a set of 20 ideas to speed up AI adoption across Europe ahead of the Commission’s Apply AI Strategy.

The report emerged from a Brussels policy hackathon with 65 participants from EU bodies, governments, enterprises and startups, proposing measures such as an Individual AI Learning Account, an AI Champions Network for SMEs, a European GovAI Hub and relentless harmonisation.

OpenAI highlights strong European demand and uneven workplace uptake, citing sector gaps and the need for targeted support, while pointing to initiatives like OpenAI Academy to widen skills.

Broader policy momentum is building, with the EU preparing an Apply AI Strategy to boost homegrown tools and cut dependencies, reinforcing the push for practical deployment across public services and industry.

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A new AI strategy by the EU to cut reliance on the US and China

The EU is preparing to unveil a new strategy to reduce reliance on American and Chinese technology by accelerating the growth of homegrown AI.

The ‘Apply AI strategy’, set to be presented by the EU tech chief Henna Virkkunen, positions AI as a strategic asset essential for the bloc’s competitiveness, security and resilience.

According to draft documents, the plan will prioritise adopting European-made AI tools across healthcare, defence and manufacturing.

Public administrations are expected to play a central role by integrating open-source EU AI systems, providing a market for local start-ups and reducing dependence on foreign platforms. The Commission has pledged €1bn from existing financing programmes to support the initiative.

Brussels has warned that foreign control of the ‘AI stack’ (the hardware and software that underpin advanced systems) could be ‘weaponised’ by state and non-state actors.

These concerns have intensified following Europe’s continued dependence on American tech infrastructure. Meanwhile, China’s rapid progress in AI has further raised fears that the Union risks losing influence in shaping the technology’s future.

Several high-potential AI firms have already been hosted by the EU, including France’s Mistral and Germany’s Helsing. However, they rely heavily on overseas suppliers for software, hardware, and critical minerals.

The Commission wants to accelerate the deployment of European AI-enabled defence tools, such as command-and-control systems, which remain dependent on NATO and US providers. The strategy also outlines investment in sovereign frontier models for areas like space defence.

President Ursula von der Leyen said the bloc aims to ‘speed up AI adoption across the board’ to ensure it does not miss the transformative wave.

Brussels hopes to carve out a more substantial global role in the next phase of technological competition by reframing AI as an industrial sovereignty and security instrument.

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Labour market remains stable despite rapid AI adoption

Surveys show persistent anxiety about AI-driven job losses. Nearly three years after ChatGPT’s launch, labour data indicate that these fears have not materialised. Researchers examined shifts in the US occupational mix since late 2022, comparing them to earlier technological transitions.

Their analysis found that shifts in job composition have been modest, resembling the gradual changes seen during the rise of computers and the internet. The overall pace of occupational change has not accelerated substantially, suggesting that widespread job losses due to AI have not yet occurred.

Industry-level data shows limited impact. High-exposure sectors, such as Information and Professional Services, have seen shifts, but many predate the introduction of ChatGPT. Overall, labour market volatility remains below the levels of historical periods of major change.

To better gauge AI’s impact, the study compared OpenAI’s exposure data with Anthropic’s usage data from Claude. The two show limited correlation, indicating that high exposure does not always imply widespread use, especially outside of software and quantitative roles.

Researchers caution that significant labour effects may take longer to emerge, as seen with past technologies. They argue that transparent, comprehensive usage data from major AI providers will be essential to monitor real impacts over time.

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Jaguar Land Rover begins gradual restart after major cyber-attack

Jaguar Land Rover (JLR) is beginning to restart production after a severe cyber-attack forced the company to shut down factories across several countries. Operations will restart at Wolverhampton, with other sites like Solihull and Halewood reopening gradually in the coming weeks.

The attack, which occurred at the end of August, halted manufacturing and paralysed the carmaker’s IT systems.

The disruption has caused significant financial strain across JLR’s supply chain, with many small businesses facing weeks without income. The government has offered a £1.5 billion loan guarantee to support suppliers, but industry leaders warn the assistance does not go far enough.

Evtec Group chairman David Roberts called the policy ‘toothless’, saying companies still struggle to cover labour and payroll costs after six weeks of zero revenue.

Experts believe recovery will take time, as restarting industrial production involves complex processes that cannot resume instantly. Former Aston Martin boss Andy Palmer warned that some suppliers may not survive the prolonged halt, risking further disruption.

JLR has confirmed its recovery programme is ‘firmly underway’ and that its global parts logistics centre is returning to normal operations, yet full production may remain weeks away.

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Bezos predicts gigantic gains from the current AI investment bubble

Jeff Bezos has acknowledged that an ‘AI bubble’ is underway but believes its long-term impact will be overwhelmingly positive.

Speaking at Italian Tech Week in Turin, the Amazon founder described it as an ‘industrial bubble’ rather than a purely financial.

He argued that the intense competition and heavy investment will ultimately leave society better off, even if many projects fail. ‘When the dust settles and you see who the winners are, societies benefit from those investors,’ he said, adding that the benefits of AI will be ‘gigantic’.

Bezos’s comments come amid surging spending by Big Tech on AI chips and data centres. Citigroup forecasts that investment will exceed $2.8 trillion by 2029.

OpenAI, Meta, Microsoft, Google and others are pouring billions into infrastructure, with projects like OpenAI’s $500 billion Stargate initiative and Meta’s $29 billion capital raise for AI data centres.

Industry leaders, including Sam Altman of OpenAI, warned of an AI bubble. Yet many argue that, unlike the dot-com era, today’s market is anchored by Nvidia and OpenAI, whose products form the backbone of AI development.

The challenge for tech giants will be finding ways to recover vast investments while sustaining rapid growth.

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AI industry faces recalibration as Altman delays AGI

OpenAI CEO Sam Altman has again adjusted his timeline for achieving artificial general intelligence (AGI). After earlier forecasts for 2023 and 2025, Altman suggests 2030 as a more realistic milestone. The move reflects mounting pressure and shifting expectations in the AI sector.

OpenAI’s public projections come amid challenging financials. Despite a valuation near $500 billion, the company reportedly lost $5 billion last year on $3.7 billion in revenue. Investors remain drawn to ambitious claims of AGI, despite widespread scepticism. Predictions now span from 2026 to 2060.

Experts question whether AGI is feasible under current large language model (LLM) architectures. They point out that LLMs rely on probabilistic patterns in text, lack lived experience, and cannot develop human judgement or intuition from data alone.

Another point of critique is that text-based models cannot fully capture embodied expertise. Fields like law, medicine, or skilled trades depend on hands-on training, tacit knowledge, and real-world context, where AI remains fundamentally limited.

As investors and commentators calibrate expectations, the AI industry may face a reckoning. Altman’s shifting forecasts underscore how hype and uncertainty continue to shape the race toward perceived machine-level intelligence.

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Frontier firms reshape work with AI integration

Forward-thinking companies, known as Frontier Firms, are reshaping business by integrating AI deeply into their operations. US employees’ adoption of AI tools has doubled in two years, reflecting a rapid shift.

These firms are not just experimenting but are setting new standards by redesigning workflows to leverage AI, particularly in software development. The impacts are spreading to sales, service, finance, and marketing. Three distinct patterns define this transformation.

The first, human + AI assistant, pairs individuals with AI to eliminate repetitive tasks, allowing developers to focus on design and quality.

The second, human-agent teams, integrate AI as digital workers in workflows for tasks like code testing and compliance, boosting efficiency.

The third, human-led, agent-operated pattern sees AI managing entire processes like automated release pipelines, with humans setting goals and intervening only when needed.

These patterns do not follow a linear path but appear simultaneously across different business functions. A single team might use AI to draft code, test it collaboratively, and automate releases in one day.

As these practices compound, they accelerate innovation and scale. Leaders must embrace these changes to stay competitive, as AI-driven workflows are poised to transform industries beyond software development.

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