OpenAI expands developer tools with Windsurf purchase

OpenAI, the creator of ChatGPT, is reportedly set to acquire Windsurf, an AI-powered coding assistant formerly known as Codeium, for $3 billion, according to Bloomberg. If confirmed, it would be OpenAI’s largest acquisition to date.

The deal is still pending closure, but it follows recent investment talks Windsurf held with major backers such as General Catalyst and Kleiner Perkins, valuing the startup at the same amount.

Windsurf was last valued at $1.25 billion in 2024 after a $150 million funding round. Instead of raising more capital independently, the company now appears poised to join OpenAI, which is looking to bolster its suite of developer tools within ChatGPT.

The acquisition reflects OpenAI’s efforts to remain competitive in the fast-evolving AI coding landscape, following earlier purchases like Rockset and Multi last year.

OpenAI also revealed it would scale back a planned restructuring, abandoning its proposal to become a for-profit entity.

The decision comes amid growing scrutiny and legal challenges, including a high-profile lawsuit from Elon Musk, who accused the firm of drifting from its founding mission to develop AI that serves humanity.

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Nvidia opens new quantum research centre in Boston

Nvidia has unveiled plans to open the Nvidia Accelerated Quantum Research Center (NVAQC) in Boston, a facility set to bridge quantum computing and AI supercomputing.

Expected to begin operations later this year, the centre aims to accelerate the shift from experimental to practical quantum computing.

Rather than treating quantum hardware as a standalone endeavour, Nvidia intends to integrate it with existing AI-driven systems, believing this combination could unlock solutions to problems unsolvable by today’s machines.

Quantum computing—much like AI in its early stages—fits naturally with Nvidia’s core strength: parallel processing. Instead of continuing to rely on traditional serial computing, the company has long embraced parallelism through its GPU technology and CUDA software platform.

Nvidia’s success in transforming GPUs from graphics engines into tools for scientific and commercial applications began with its bold decision to make CUDA available across all its products, even at the cost of short-term profit margins.

Nvidia now sees quantum error correction as the next major challenge. Current quantum computers, operating with between fifty and one hundred qubits, face a high error rate due to environmental ‘noise.’

Achieving truly useful systems will require a million qubits or more, most of which will be used for error correction. Instead of depending solely on traditional methods, Nvidia plans to use AI to develop scalable solutions capable of correcting errors in real time.

The Boston-based NVAQC will serve as a testing ground for these innovations. Harvard, MIT, and quantum startups like Quantinuum and QuEra will collaborate with Nvidia’s quantum team to train AI models for error correction and test them using Nvidia’s top-tier supercomputers.

By doing so, Nvidia hopes to make quantum computing not just viable, but powerful and practical at scale.

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New AI app offers early support for parents of neurodivergent children

A new app called Hazel, developed by Bristol-based company Spicy Minds, offers parents a powerful tool to understand better and support their neurodivergent children while waiting for formal diagnoses. Using AI, the app runs a series of tests and then provides personalised strategies tailored to everyday challenges like school routines or holidays.

While it doesn’t replace a medical diagnosis, Hazel aims to fill a critical gap for families stuck in long waiting queues. Spicy Minds CEO Ben Cosh emphasised the need for quicker support, noting that many families wait years before receiving an autism diagnosis through the UK’s NHS.

‘Parents shouldn’t have to wait years to understand their child’s needs and get practical support,’ he said.

In Bristol alone, around 7,000 children are currently on waiting lists for an autism assessment, a number that continues to rise. Parents like Nicola Bennett, who waited five years for her son’s diagnosis, believe the app could be life-changing.

She praised Hazel for offering real-time guidance for managing sensory needs and daily planning—tools she wished she’d had much earlier. She also suggested integrating links to local support groups and services to make the app even more impactful.

By helping reduce stress and giving families a head start on understanding neurodiversity, Hazel represents a meaningful step toward more accessible, tech-driven support for parents navigating a complex and often delayed healthcare system.

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Google’s Gemini AI completes Pokémon Blue with a little help

Google’s cutting-edge AI model, Gemini 2.5 Pro, has made headlines by completing the 1996 classic video game Pokémon Blue. While Google didn’t achieve the feat directly, it was orchestrated by Joel Z, an independent software engineer who created a livestream called Gemini Plays Pokémon.

Despite being unaffiliated with the tech giant, Joel’s project has drawn enthusiastic support from Google executives, including CEO Sundar Pichai, who celebrated the victory on social media. The challenge of beating a game like Pokémon Blue has become an informal benchmark for testing the reasoning and adaptability of large language models.

Earlier this year, AI company Anthropic revealed its Claude model was making strides in a similar title, Pokémon Red, but has yet to complete it. While comparisons between the two AIs are inevitable, Joel Z clarified that such evaluations are flawed due to differences in tools, data access, and gameplay frameworks.

To play the game, Gemini relied on a complex system called an ‘agent harness,’ which feeds the model visual and contextual information from the game and translates its decisions into gameplay actions. Joel admits to making occasional interventions to improve Gemini’s reasoning but insists these did not include cheats or explicit hints. Instead, his guidance was limited to refining the model’s problem-solving capabilities.

The project remains a work in progress, and Joel continues to enhance the framework behind Gemini’s gameplay. While it may not be an official benchmark for AI performance, the achievement is a playful demonstration of how far AI systems have come in tackling creative and unexpected challenges.

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Apple partners with Anthropic on AI coding tool

Apple is reportedly collaborating with Anthropic, a startup backed by Amazon, to develop a new AI-powered coding platform called ‘vibe coding’, according to Bloomberg.

The platform will use Anthropic’s Claude Sonnet model to write, edit, and test code on behalf of programmers, updating Apple’s existing Xcode software instead of launching an entirely separate tool.

‘Vibe coding’ refers to a growing trend in AI development where intelligent agents generate code autonomously instead of relying on manual programming. Apple is said to be testing the system internally for now, with no confirmed decision on whether it will become publicly available.

The move comes as tech firms race to lead in generative AI. While Apple previously introduced a similar tool, Swift Assist, it was never released to developers amid concerns from engineers about possible slowdowns in app creation.

Apple and Anthropic have not commented publicly on the reported collaboration.

With rivals like OpenAI pushing ahead—reportedly negotiating a $3 billion acquisition of coding assistant Windsurf—Apple is equipping its devices with more advanced chips and AI features, including ChatGPT integration, to compete in the rapidly evolving landscape instead of falling behind.

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AI to boost India’s media and entertainment sector

AI could boost revenues by 10% and reduce costs by 15% for media and entertainment firms, according to a report by EY, unveiled during the first WAVES Summit.

The report, A Studio Called India, outlines how AI is reshaping the global media landscape—transforming everything from content creation and personalisation to monetisation and distribution.

India, already a global leader in content production and IT, is well-positioned to lead this AI-driven shift.

EY highlighted India’s unique combination of technical skill, creative depth, and a rapidly expanding AI ecosystem, which positions it as a critical hub in the evolving media value chain instead of remaining just an outsourcing destination.

Indian companies are increasingly using generative AI for tasks like campaign optimisation, audience targeting, automated dubbing, and voice cloning.

These tools enable faster localisation of international content and allow global studios to scale up multi-language releases without sacrificing cultural authenticity or narrative integrity.

With 2.8 million people directly employed and around 10 million in indirect roles, India’s media sector is growing rapidly, driven by digital platforms, government support, and rising demand for AI-enhanced content services.

EY concluded that India offers foreign investors a powerful combination of creative scale, cost advantage, and favourable policies instead of regulatory barriers.

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Musk says AI should replace federal jobs

Elon Musk has suggested that AI should replace many federal government workers, criticising the US administration as bloated and inefficient.

Speaking privately at the Milken Institute Global Conference in Beverly Hills, Musk argued AI could perform government tasks faster and with greater accuracy, ultimately saving taxpayers money.

His remarks coincided with the winding down of his controversial volunteer role leading the Department of Government Efficiency (DOGE), an initiative born under Donald Trump’s presidency.

Musk spent over 100 days embedded in the White House, even setting up a small office in the West Wing. Despite joking about its minimal view and sleeping in the Lincoln Bedroom, he claimed his work had major impacts — including rooting out fraud and slashing federal budgets.

Musk said DOGE was responsible for cutting $160 billion in government spending, although no formal evidence has been released to support that figure.

The programme has sparked intense backlash. Thousands of federal employees were reportedly dismissed or resigned during the DOGE audits, prompting lawsuits and allegations of illegal firings.

Critics say the sweeping cuts have left the US less prepared for emergencies and reduced its global influence, allowing China to expand its reach. Protesters have targeted Tesla in response, leading Trump to defend Musk and condemn the attacks.

Although scaling back his involvement in Washington, Musk isn’t leaving entirely. He will now spend only one or two days a week on government affairs, returning more of his focus to Tesla amid flagging sales and investor pressure.

Despite the chaos, DOGE has inspired new political groups in Congress, blurring the line between satire and policy. Musk himself finds it all surreal, asking, ‘Are we in a simulation here?’

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Chefs quietly embrace AI in the kitchen

At this year’s Michelin Guide awards in France, AI sparked nearly as much conversation as the stars themselves.

Paris-based chef Matan Zaken, of the one-star restaurant Nhome, said AI dominated discussions among chefs, even though many are hesitant to admit they already rely on tools like ChatGPT for inspiration and recipe development.

Zaken openly embraces AI in his kitchen, using platforms like ChatGPT Premium to generate ingredient pairings—such as peanuts and wild garlic—that he might not have considered otherwise. Instead of starting with traditional tastings, he now consults vast databases of food imagery and chemical profiles.

In a recent collaboration with the digital collective Obvious Art, AI-generated food photos came first, and Zaken created dishes to match them.

Still, not everyone is sold on AI’s place in haute cuisine. Some top chefs insist that no algorithm can replace the human palate or creativity honed by years of training.

Philippe Etchebest, who just earned a second Michelin star, argued that while AI may be helpful elsewhere, it has no place in the artistry of the kitchen. Others worry it strays too far from the culinary traditions rooted in local produce and craftsmanship.

Many chefs, however, seem more open to using AI behind the scenes. From managing kitchen rotas to predicting ingredient costs or carbon footprints, phone apps like Menu and Fullsoon are gaining popularity.

Experts believe molecular databases and cookbook analysis could revolutionise flavour pairing and food presentation, while robots might one day take over laborious prep work—peeling potatoes included.

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New Zealand central bank warns of AI risks

The Reserve Bank of New Zealand has warned that the swift uptake of AI in the financial sector could pose a threat to financial stability.

A report released on Monday highlighted how errors in AI systems, data privacy breaches and potential market distortions might magnify existing vulnerabilities instead of simply streamlining operations.

The central bank also expressed concern over the increasing dependence on a handful of third-party AI providers, which could lead to market concentration instead of healthy competition.

A reliance like this, it said, could create new avenues for systemic risk and make the financial system more susceptible to cyber-attacks.

Despite the caution, the report acknowledged that AI is bringing tangible advantages, such as greater modelling accuracy, improved risk management and increased productivity. It also noted that AI could help strengthen cyber resilience rather than weaken it.

The analysis was published just ahead of the central bank’s twice-yearly Financial Stability Report, scheduled for release on Wednesday.

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Google admits using opted-out content for AI training

Google has admitted in court that it can use website content to train AI features in its search products, even when publishers have opted out of such training.

Although Google offers a way for sites to block their data from being used by its AI lab, DeepMind, the company confirmed that its broader search division can still use that data for AI-powered tools like AI Overviews.

An initiative like this has raised concern among publishers who seek reduced traffic as Google’s AI summarises answers directly at the top of search results, diverting users from clicking through to original sources.

Eli Collins, a vice-president at Google DeepMind, acknowledged during a Washington antitrust trial that Google’s search team could train AI using data from websites that had explicitly opted out.

The only way for publishers to fully prevent their content from being used in this way is by opting out of being indexed by Google Search altogether—something that would effectively make them invisible on the web.

Google’s approach relies on the robots.txt file, a standard that tells search bots whether they are allowed to crawl a site.

The trial is part of a broader effort by the US Department of Justice to address Google’s dominance in the search market, which a judge previously ruled had been unlawfully maintained.

The DOJ is now asking the court to impose major changes, including forcing Google to sell its Chrome browser and stop paying to be the default search engine on other devices. These changes would also apply to Google’s AI products, which the DOJ argues benefit from its monopoly.

Testimony also revealed internal discussions at Google about how using extensive search data, such as user session logs and search rankings, could significantly enhance its AI models.

Although no model was confirmed to have been built using that data, court documents showed that top executives like DeepMind CEO Demis Hassabis had expressed interest in doing so.

Google’s lawyers have argued that competitors in AI remain strong, with many relying on direct data partnerships instead of web scraping.

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