Latest news with #OpenAI
CNA
13 minutes ago
- Business
- CNA
Oracle to invest $3 billion in AI, cloud expansion in Germany, Netherlands
Oracle will invest $3 billion over the next five years in artificial intelligence and cloud infrastructure in Germany and the Netherlands to meet upbeat demand, the company said in separate statements on Tuesday. The cloud service provider plans to allocate $2 billion to Germany and $1 billion to the Netherlands. Major technology firms have poured tens of billions of dollars into developing AI infrastructure following the success of OpenAI's ChatGPT. Oracle, whose cloud offerings support companies in building AI infrastructure, has seen its shares surge about 38 per cent so far this year. In June, the company raised its annual revenue forecast, driven by strong demand for its AI-related cloud services.
Hans India
42 minutes ago
- Business
- Hans India
Meta's Prometheus AI Supercluster Set to Go Live by 2026, Zuckerberg Ramps Up AI Push
Meta is making a major leap forward in artificial intelligence, with CEO Mark Zuckerberg announcing that the company's first AI data supercluster—Prometheus—will be operational by 2026. This bold move underscores Meta's deepening commitment to competing at the highest level in the generative AI space, where it faces strong rivals like OpenAI and Google. In a detailed post on Facebook, Zuckerberg revealed that Meta is not only accelerating its infrastructure build-out but also investing hundreds of billions of dollars in compute, talent, and long-term AI research. Prometheus is just the beginning. The company is simultaneously developing Hyperion, a future-ready system that will eventually scale to 5 gigawatts, placing it among the most powerful AI clusters globally. In a notable departure from tradition, Meta is speeding up construction timelines by assembling temporary data centers in tents, reminiscent of Elon Musk's "tent factory" strategy during Tesla's Model 3 rush in 2018. This unusual approach, first reported by SemiAnalysis and later acknowledged by Zuckerberg, reflects the company's urgency to get AI systems online faster—even if it means sacrificing some stability during peak summer conditions. Zuckerberg also spotlighted Meta Superintelligence Labs, a newly established division that he says will offer 'industry-leading levels of compute and by far the greatest compute per researcher.' This lab is part of a broader effort to build what he calls 'the most elite and talent-dense team in the industry.' Reports suggest that the lukewarm response to Meta's Llama 4 AI model earlier this year prompted a strategic overhaul. Determined to turn things around, Meta has launched an aggressive hiring spree—reportedly offering $100 million+ compensation packages to top AI researchers—and recently poured $14 billion into Scale AI, aiming to secure access to high-quality datasets that can fuel future model development. Though the use of tents and prefab cooling units may seem unconventional for data centers, the company is leaning into fast deployment over perfection. By taking these bold steps, Meta is signaling that it's not just trying to catch up in the AI race—it plans to lead it.
Telegraph
42 minutes ago
- Business
- Telegraph
Zuckerberg to spend billions on ‘Manhattan-sized' data centres
Mark Zuckerberg 's Meta is preparing to spend billions of dollars building 'Manhattan-sized' data centres to supercharge its artificial intelligence (AI) technology. The social media giant's first one-gigawatt (GW) data centre mega-project, dubbed Prometheus after the Greek titan, will come online next year with plans for 'multiple more titan clusters', the Facebook founder said. These one gigawatt (GW) data centres will consume more power than about 750,000 standard homes. Mr Zuckerberg said the company was planning to construct another, larger 5GW data centre, called Hyperion, 'over several years'. Meta's data centres will power the company's AI technology as it seeks to gain an edge over rivals including OpenAI, Google and Elon Musk's xAI. OpenAI is planning to spend about $500bn (£372bn) on its own Stargate data centre project. Silicon Valley giants have been buying up powerful computer processors and constructing new data centres in an effort to create and power so-called artificial general intelligence. To power this new AI infrastructure, they have been hunting out new energy sources amid an arms race to conquer the sector. In a post on the Meta-owned social media platform Threads, Mr Zuckerberg said he was planning to 'invest hundreds of billions of dollars' into computing to build superintelligence. He said Meta would be the first tech giant to bring a new 1GW data centre online. 'Just one of these covers a significant part of the footprint of Manhattan,' he said. Facebook told investors in May it planned to spend up to $72bn this year alone to fuel its data centre expansion plans. The Prometheus data centre is under construction in New Albany, Ohio, while its Hyperion site is planned for Louisiana. Technology analyst firm Semianalysis said Meta had started building a natural gas plant in Ohio 'when the local power grid couldn't keep up' with its plans. Mr Zuckerberg has been betting tens of billions of dollars on Meta's AI efforts after its attempts to gain ground on OpenAI, the developer of ChatGPT, fell flat. Earlier this year, the company delayed launching its latest new AI product, internally dubbed Behemoth. The Meta chief executive has personally embarked on a hiring blitz of AI experts and executives, allegedly offering bonuses of more than $100m to some new joiners.
India Today
an hour ago
- Business
- India Today
After Google hired its Indian-origin CEO Varun Mohan, Windsurf gets acquired by Cognition: Story in 5 points
In a fast-moving twist in the world of AI startups, Windsurf, the coding-focused AI firm once set for a blockbuster acquisition by OpenAI, is now at the centre of a different kind of deal. While OpenAI's $3 billion acquisition bid quietly collapsed, Google has swooped in to secure key talent from Windsurf, including its Indian-origin CEO, Varun Mohan. At the same time, Cognition Labs, the team behind the AI coding agent Devin, has now officially acquired Windsurf. Here is the full story in five key $3 billion Windsurf deal sinksEarlier this year, OpenAI appeared close to acquiring Windsurf, a promising startup which was focused on AI coding tools. Reports suggested a potential $3 billion deal was in the works. However the exclusivity period for the offer expired without a deal being finalised. According to reports by The Verge and The Wall Street Journal, tensions reportedly emerged due to overlapping access between OpenAI's tech and Microsoft, which may have complicated the acquisition. By the time the OpenAI offer lapsed, Windsurf was already in discussion with others. Google pulls off a 'reverse acquihire'Soon after OpenAI's bid fell through, Google DeepMind moved swiftly to bring Windsurf's top leadership into its fold, without buying the company outright. Among those joining DeepMind are Windsurf's CEO Varun Mohan, co-founder Douglas Chen, and a group of senior AI researchers. Instead of a full acquisition, Google is paying $2.4 billion in licensing fees to access some of Windsurf's technology under non-exclusive terms. This means Google gets the talent and the tech but Windsurf remains an independent entity, free to work with other leadership changes, but operations continue With Varun Mohan and Douglas Chen exiting Google, Windsurf's head of business, Jeff Wang, has been appointed interim CEO. Graham Moreno, the company's VP of global sales, has stepped into the role of president. Despite the high-profile departures, around 250 employees are staying on at Windsurf. In a statement, Wang reassured clients that the company will continue to focus on enterprise AI coding tools and product innovation. 'We aren't going anywhere,' he said in a social media post. Cognition Labs acquires Windsurf after Google's talent scoopThe plot thickened further when, shortly after Google secured Windsurf's top brass, AI startup Cognition Labs announced its acquisition of Windsurf. Known for creating the AI software engineer Devin, Cognition is led by Scott Wu, a rising name in the AI coding space. While the financial details were not disclosed, the move gives Cognition access to Windsurf's remaining team and infrastructure, allowing it to scale its developer tools further, even as the startup's founders and original leadership now work at delighted to share that Windsurf is being acquired by Cognition. Our world-class team will be joining forces with the iconic company that created Devin, the world's first autonomous software engineering agent. Our users and customers will remain in steady hands and enjoy better product innovation than ever. And finally, Windsurf's unique IP will also become integrated into Cognition, helping the joint team continue to push the frontier of AI coding capabilitiesWindsurf blog post AI's war for talent intensifiesThe Windsurf saga is the latest example of how Big Tech is racing to corner the market in AI talent and tools – using strategic hires and licensing deals rather than full acquisitions. Google's move mirrors similar 'acquihire-style' plays by Microsoft and Meta in recent months. These deals, which avoid giving companies controlling stakes, often sidestep antitrust scrutiny. But one thing is clear: in this AI arms race, talent is the real prize.- Ends
Axios
an hour ago
- Business
- Axios
AI's elusive coding speedup
A surprising new study finding that AI tools can reduce programmers' productivity is upending assumptions about the technology's world-changing potential. Why it matters: Software runs our civilization, and AI is already transforming the business of making it — but no one really knows whether AI will decimate programming jobs, or turn every coder into a miracle worker, or both. Driving the news: The study by METR, a nonprofit independent research outfit, looked at experienced programmers working on large, established open-source projects. It found that these developers believed that using AI tools helped them perform 20% faster — but they actually worked 19% slower. The study appears rigorous and well-designed, but it's small (only 16 programmers participated, completing 246 tasks). Zoom out: For decades, industry visionaries have dreamed of a holy grail called "natural language programming" that would allow people to instruct computers using everyday speech, without needing to write code. As large language models' coding prowess became evident, it appeared this milestone had been achieved. "The hottest new programming language is English," declared AI guru (and OpenAI cofounder) Andrej Karpathy on X early in 2023, soon after ChatGPT's launch. In February, Karpathy also coined the term "vibe-coding" — meaning the quick creation of rough-code prototypes for new projects by just telling your favorite AI to whip up something from scratch. The most fervent believers in software's AI-written future say that human beings will do less and less programming, and engineers will turn into some combination of project manager, specifications-refiner and quality-checker. Either that, or they'll be unemployed. Zoom in: AI-driven coding tends to be more valuable in building new systems from the ground up than in extending or refining existing systems, particularly when they're big. While innovative new products get the biggest buzz and make the largest fortunes, the bulk of software work in most industries consists of more mundane maintenance labor. Anything that makes such work more efficient could save enormous amounts of time and money. Yes, but: This is where the METR study found AI actually slowed experienced programmers down. One key factor was that human developers found AI-generated code unreliable and ended up devoting extra time to reviewing, testing and fixing it. "One developer notes that he 'wasted at least an hour first trying to [solve a specific issue] with AI' before eventually reverting all code changes and just implementing it without AI assistance," the study says. Between the lines: The study authors note that AI coding tools are improving at a rapid enough rate that their findings could soon be obsolete. They also warn against generalizing too broadly from their findings and note the many counter-examples of organizations and projects that have made productivity gains with coding tools. One notable caution that's inescapable from the study's findings: Don't trust self-reporting of productivity outcomes. We're not always the best judges of our own efficiency. Another is that it's relatively easy to measure productivity in terms of "task completion" but very hard to assess total added value in software-making. Thousands of completed tickets can be meaningless — if, for instance, a program is about to be discontinued. Meanwhile, one big new insight can change everything in ways no productivity metric can capture. The big picture: The software community is divided over whether to view the advent of AI coding with excitement or dread.
