Últimas Noticias de IA
OpenAI introduces ‘Ultrafast,’ a new mode that makes GPT-5.6 Sol work at 14x the speed
If you’ve ever found yourself wishing that ChatGPT was a little bit quicker on the uptake, OpenAI seems to be answering your prayers. The AI lab has rolled out a new modecalled Ultrafast, which it says is designed to seriously accelerate the pace at which its latest and most powerful model,GPT-5.6 Sol, accomplishes its work. The company says that Ultrafast can work at 14x the speed of standard processing, delivering up to 750 output tokens — such tokens represent the distinct pieces of text generated by an LLM when it interacts with a human — per second. “Until now, getting real-time speed typically meant choosing a smaller or more specialized model,” the company saidin a blog poston Thursday. “Ultrafast points to progress in a new direction: more useful work per second.” OpenAI’s competitors, like Anthropic, have similarly launched accelerated versions of their models.Claude has fast mode, although it doesn’t deliver the kind of speed that OpenAI is offering here. OpenAI suggests that this high-octane version of GPT 5.6 Sol can be deployed across a number of different corporate workflows, most notably incident response, customer service and support, financial market analysis, and e-commerce, among other relevant areas. Ultrafast, which is currently being released in preview, is being powered by OpenAI’s partnership with chipmaker Cerebras. Currently, that preview is only being made available to a small group of customers, although OpenAI says that it will expand access to the feature as “capacity grows.”
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Apple in talks to pay publishers to provide Siri with current news: report
Apple is in talks to pay publishers to use their content to power the upcoming Siri AI, according to a new report fromThe Wall Street Journal. The tech giant has reached out to publishers in recent months about using their content to provide Siri with access to current news and information. Apple has proposed a variable compensation model that would pay publishers when their content is used, rather than through a fixed licensing fee. This marks a departure from the standard industry practice of guaranteed fees, which are generally tied to broad access to content, rather than a pay-as-you-go model. Apple has considered a nine-figure budget for the payments, the report says. Apple did not immediately respond to TechCrunch’s request for comment. The discussions come as Apple has been working to significantly enhance Siri, years after promising users a smarter and more capable AI assistant. Siri AI is expected to roll out later this year.
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Nvidia’s new $500B plan is risky but brilliant, especially for aging GPUs
Nvidiaannouncedthis week that Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR were willing to commit up to $500 billion to build AI data centers. That eye-popping figure got a lot of the attention, but the bigger story is Nvidia’s effort to create a secondary market for aging GPUs. To convince those big-name financial companies, Nvidia has agreed to guarantee, with its own money, that its chips used as collateral in these deals will retain their value. Many have now commented on howunusual,smart, anddangerousthis plan is. It is all of those things. The bond marketsgot so spookedthat Nvidia CEO Jensen Huangtook to Xandbusiness TVto better explain how Nvidia’s risk would be limited. But underneath the financial maneuvering to fund AI data centers (and keep revenue for Nvidia flowing), is something, perhaps, far more interesting for startups and enterprises: Huang wants to ensure an ecosystem of used AI hardware flourishes, helping sustain demand for Nvidia hardware as it ages. Specifically, Nvidia is promising that if GPUs used as collateral don’t retain their value as expected, the company will cover up to 25% of the difference. So, if a data center owner defaults on a loan and the lender must liquidate, but the chips can’t command the price the books say they should, Nvidia will chip in. The dangerous part for Nvidia is that this creates something financiers call “wrong way” risk. That is, Nvidia’s obligations will grow as demand weakens. Should that happen, its revenues will likely be squeezed as well. Still, the scheme is deliberatelyunlike the comparison to Lucent Technologiesthat some have been making. Lucent was the telecommunications equipment provider that rose and crashed with the dotcom bubble after lending its customers money to buy its wares. The Lucent comparison is a shadow over Nvidia, Huang knows. And not an unfair one. Nvidia definitely has committed billions towards those who buy its chips, including frontier AI labs OpenAI and Anthropic, neoclouds like CoreWeave (the originator of using Nvidia chips as collateral) as well as Nebius, Firmus, and Lambda. And it has been working on another$750 billion worth of circular dealsthis summer, Bloomberg has calculated. “Is this circular financing?” Huang wrote on X about the new scheme. “This initiative is designed to address that concern. We are bringing independent, long-term institutional capital into the AI infrastructure market.” That’s true. Unlike Lucent, Nvidia is getting others to shoulder the bulk of the capital and risk, merely by agreeing to protect a portion of its chips’ value in the future. Should this plan work, Nvidia will have found new sources of money for AI data center builds, after many of the traditional methods have begun to wear thin. For instance, some of the hyperscalers have already taken on a lot of debt (likeOracle), issued new tranchesof equity (Google), and burnedmuch cash (Meta). The situation has become so dicey that Microsoft CEO Satya Nadella recently recommended the book“1873”during his latest earnings call. It’s about the railroad-era financial engineering that crashed the nation’s economy. The risk is that today’s AI boom, where demand far outstrips capacity, doesn’t continue for much longer. Rather than being in the early innings, what if enterprises and consumers temper AI usage? Or new technologies come along to make existing infrastructure more effective and/or all of today’s AI infrastructure obsolete? Then, like so many buggy whips in the face of automobiles (to paraphrase Danny Devito’s Lawrence Garfield), demand dries up and everything crashes. Yet, Huang is arguing that won’t happen by selling a vision of AI as a long-term “investable infrastructure,” as he describes it. That makes his AI servers, which he calls “AI factories” akin to railroads or airlines rather than quickly depreciating assets like PCs. “When needs change, the factory can be used by another customer, another cloud or another operator. This broad ecosystem gives NVIDIA compute a deep market of potential users and offtakers, helping protect residual value,” he promised. In that future, Nvidia cares as much about aging architecture as it does the new chips. And perhaps startups, enterprises, and even researchers will tap into a broader variety of hardware, each tuned to different AI needs, just like they are beginning to pick affordable open-weight models alongside the frontier choices. As the king of AI, Nvidia has the power, and the window of opportunity, to make that happen.
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Microsoft kills off unsuccessful AI features while merging its separate Copilot apps
Two years ago,Microsoft described AIas a “generational shift” in technology that it wanted to lead. Today, the company is merging its Copilot-branded consumer and business apps, and ditching a number of unsuccessful AI features. As initially reported byGeekWireand detailed inMicrosoft’s support documentation, the tech giant will combine the functionality of its consumer-facing Copilot app and the more business-oriented Microsoft 365 Copilot app. The move is both an acknowledgement that personal and professional uses of AI often overlap, and that Microsoft’s prior strategy was too complicated to make Copilot a viable competitor to the likes of ChatGPT, Claude, and Gemini. It also follows a broader consolidation in the AI app space that has seen ClaudemergingCowork into Chat; OpenAI merging its agentic featureOperator into ChatGPT; and Google addingspecialized capabilitiesto its Gemini app, like the combination of deep research and web browsing. According to Microsoft, consumers will lose access to Group Chats, AI-generated podcasts in Copilot, Copilot Labs experimental features, and Deep Research, by August 18, 2026. For paying professional users,Researcherwill offer a replacement for the latter, at least. The company will alsoditchitsgoofy animated character for Copilot, named Mico, a floating blob that felt likean AI-ified version of Clippy. Other features may temporarily disappear during the transition, Microsoft warns, and files generated by the standalone Copilot app will be migrated to OneDrive. While the company says the goal is to make Copilot a “simpler, more cohesive experience,” it’s also an admission that Copilot has lost its way. In July,The Informationreported that Microsoft EVP Jacob Andreou, who oversees Copilot, said in an internal memo that the app needed to earn “the right to exist” in its customers’ lives, which required moving on from features that didn’t work.
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How Two Indian Startups Are Replacing Paper With Digital Trust
Two founders digitise critical transactions, using data, regulation, and AI to replace trust with verifiable proof.
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Google Gemini Expands Connected Apps With OpenTable, Ticketmaster and More
Google is expanding the range of third-party apps and services that can connect to Gemini, allowing users to handle more tasks through the AI assistant. The new integrations cover productivity, creativity, local services, entertainment, music, home, health and lifestyle. The rollout will add tools such as Granola, Otter.ai, Wix, Fever, GetYourGuide, Localiza, OpenTable, Ticketmaster, iHeartRadio, Pandora, Angi, Thumbtack and Zocdoc over the coming weeks. Google has also shared new figures showing how people are using Gemini across platforms.
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CloudSEK Identifies AI Supply Chain Exposure Affecting More Than 2,500 Organisations
Cybersecurity firm CloudSek has identified an AI supply-chain attack on LiteLLM that affected more than 2,500 organisations. The incident, which reportedly occurred in March this year, seems to have potentially exposed around 4,34,000 automated software development pipelines. The attack reportedly exposed data of many leading tech brands, including Microsoft, X, Amazon, Cisco, Samsung and Salesforce.
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Google’s Age Signals Could Protect Kids But Raise New Privacy Questions
Google is giving apps access to users’ age signals, raising questions over data minimisation, profiling and the limits of platform-led child safety.
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Chandra’s Exit Brings a Rare Moment of Uncertainty for Tata Group
N Chandrasekaran’s exit has unsettled investors at a critical juncture for the Tata Group, raising fresh questions over succession, capital allocation and the conglomerate’s future direction.
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L&T's Vyoma.AI Lands NVIDIA 10K-GPU Deal
L&T will deploy a 10,000-GPU NVIDIA B300 AI Factory at Vyoma.AI's gigawatt-scale Chennai data centre campus to support Together AI's AI Native Cloud platform.
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CodeRabbit Raises $143 Mn as AI Coding Agents Generate More Code
The company is expanding beyond AI code reviews with tools that prioritise changes, explain large pull requests and monitor software for security risks.
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SpaceXAI Launches Grok 4.6 to Take On GPT-5.6 and Fable 5
The company says the model can handle multi-step research, coding and app-building tasks while checking and refining its own work along the way.
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