Latest AI News
Multiverse Computing pushes its compressed AI models into the mainstream
With private company defaults running atupwards of 9.2%— the highest rate in years — VC firm Lux Capital recently advised companies relying on AI to get their compute capacity commitmentsconfirmed in writing. With financial instability rippling through the AI supply chain, Lux warned, a handshake agreement isn’t enough. But there’s another option entirely, which is to stop relying on external compute infrastructure altogether. Smaller AI models that run directly on a user’s own device — no data center, no cloud provider, no counterparty risk — are getting good enough to be worth considering. AndMultiverse Computingis raising its hand. The Spanish startup has so far kept a lower profile than some of its peers, but as demand for AI efficiency grows, this is changing. After compressing models from major AI labs including OpenAI, Meta, DeepSeek and Mistral AI, it has launched both an app that showcases the capabilities of its compressed models and an API portal — a gateway that lets developers access and build with those models — that makes them more widely available. TheCompactifAI app, which shares its name with Multiverse’s quantum-inspired compression technology, is an AI chat tool in the vein of ChatGPT or Mistral’s Le Chat. Ask a question, and the model answers. The difference is that Multiverse embedded Gilda, a model so small that it can run locally and offline, according to the company. For end users, this is a taste of AI on the edge, with data that doesn’t leave their devices and doesn’t require a connection. But there’s a caveat: their mobile devices must have enough RAM and storage. If they don’t — and many older iPhones won’t — the app switches back to cloud-based models via API. The routing between local and cloud processing is handled automatically by a system Multiverse has named Ash Nazg, whose name will ring a bell for Tolkien fans as it references the One Ring inscription in “The Lord of the Rings.” But when the app routes to the cloud, it loses its main privacy edge in the process. These limitations mean that CompactifAI is not quite ready for mass customer adoption yet, although that may never have been the goal. According to data from Sensor Tower, the app hadfewer than 5,000 downloadsin the past month. The real target is businesses. Today, Multiverse is launching aself-serve API portalthat gives developers and enterprises direct access to its compressed models — no AWS Marketplace required. “The CompactifAI API portal [now] gives developers direct access to compressed models with the transparency and control needed to run them in production,” CEO Enrique Lizaso said in a statement. Real-time usage monitoring is one of the key features of the API, and that’s no accident. Alongside the potential advantages of deploying on the edge, lower compute costs are one of the main reasons why enterprises are considering smaller models as an alternative to large language models (LLMs). It also helps that small models are less limited than they used to be. Earlier this week, Mistral updated its small model family with thelaunch of Mistral Small 4, which it says is simultaneously optimized for general chat, coding, agentic tasks and reasoning. The French company alsoreleased Forge, a system that lets enterprises build custom models, including small models for which they can pick the tradeoffs their use cases can best tolerate. Multiverse’s recent results also suggest the gap with LLMs is narrowing. Its latest compressed model,HyperNova 60B 2602, is built on gpt-oss-120b — an OpenAI model whose underlying code is publicly available. The company claims it now deliversfaster responsesat lower cost than the original it was derived from, an advantage that matters particularly for agentic coding workflows, where AI autonomously completes complex, multi-step programming tasks. Making models small enough to operate on mobile devices while still remaining useful is a big challenge.Apple Intelligencesidestepped that issue by combining an on-device model and a cloud model. Multiverse’s CompactifAI app can also route requests to gpt-oss-120b via API, but its main goal is to showcase that local models like Gilda and its future replacements have advantages that go beyond cost savings. For workers in critical fields, a model that can run locally and without connecting to the cloud offers more privacy and resilience. But the bigger value is in the business use cases this can unlock – for instance, embedding AI in drones, satellites, and other settings where connectivity can’t be taken for granted. The company already serves more than 100 global customers including the Bank of Canada, Bosch and Iberdrola, but expanding its customer base could help it unlock more funding. After raising a$215 million Series Blast year, it is nowrumored to be raising a fresh €500 million funding roundat a valuation of more than €1.5 billion.
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How India Became Volkswagen's Command Centre for Software-Defined Vehicles
Embitel, acquired by Volkswagen in 2022, operates on a “GCC Plus” model that blends captive centre capabilities with external market exposure.
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OpenAI Unveils 16MB, 10-Min Model Training Challenge on NVIDIA H100 GPUs
The Model challenge is designed to test the ability to tackle unfamiliar problems with creativity and rigour, OpenAI said.
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Siemens Says Agentic AI Is Early, Doubles Down on Patents
‘Agentic AI is still in its infancy,’ says CTO Peter Koerte, as Siemens expands internal AI platforms and builds a portfolio of over 1,000 AI and data science patents.
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This Sports Tech Startup Feeds 'Post-Match Analysis' Into Live Games
SportVot uses computer vision, cloud infra, and edge computing to make live sports broadcasting and analytics accessible to grassroots tournaments.
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Can AI End Monsoon Guesswork on Indian Farms?
Language is the primary barrier to significant adoption of AI at scale.
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Microsoft Pauses Automatic Rollout of Microsoft 365 Copilot App on Windows
Microsoft has temporarily stopped the automatic rollout of the Microsoft 365 Copilot app on Windows devices with Microsoft 365 desktop apps. The move comes as the company adjusts its approach to integrating AI features more broadly across Windows and its productivity ecosystem. While Copilot has been a key part of Microsoft's recent software strategy, the latest update suggests a more cautious rollout. The company has not confirmed when the automatic installation process will resume.
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North American Scientists Win 2025 Turing Award for Quantum Cryptography
Charles H Bennett and Gilles Brassard were recognised for introducing quantum mechanics to process and transmit information
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Amazon Offers Kiro for Free to Students Amid Questions Over Quality
As per reports, several current and former employees described Kiro as unreliable in practice.
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Meta is having trouble with rogue AI agents
An AI agent went rogue at Meta, exposing sensitive company and user data to employees who did not have permission to access it. Per an incident report, which was viewed and reported on byThe Information, a Meta employee posted on an internal forum asking for help with a technical question — which is a standard action. However, another engineer asked an AI agent to help analyze the question, and the agent ended up posting a response without asking the engineer for permission to share it. Meta confirmed the incident to The Information. As it turns out, the AI agent did not give good advice. The employee who asked the question ended up taking actions based on the agent’s guidance, which inadvertently made massive amounts of company and user-related data available to engineers, who were not authorized to access it, for two hours. Meta deemed the incident a “Sev 1,” which is the second-highest level of severity in the company’s internal system for measuring security issues. Rogue AI agents have already posed a problem at Meta. Summer Yue, a safety and alignment director at Meta Superintelligence,posted on X last monthdescribing how her OpenClaw agent ended up deleting her entire inbox, even though she told it to confirm with her before taking any action. Still, Meta seems bullish on the potential for agentic AI. Just last week, Meta boughtMoltbook, a Reddit-like social media site for OpenClaw agents to communicate with one another.
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Nvidia is quietly building a multibillion-dollar behemoth to rival its chips business
Nvidia CEO Jensen Huang was years ahead of the market when he pushed the company to start tinkering withbuilding AI-specific chips back in 2010, more than a decade before the current buzz around AI. A similar move in 2020 — doubling down on data center networking with a strategic acquisition — has led to one of the company’s most lucrative and quickly growing divisions, but with little fanfare. In just a few years, Nvidia’s networking business, designed to connect data centers, has grown into the company’s second-largest revenue driver behind compute. Last quarter, it reported $11 billion in revenue, a year-over-year increase of 267%, and brought in more than $31 billion for the full year, according to Nvidia’smost recent earnings. Driven by growth in AI processing, the division includes tech like NVLink, which powers communication between GPUs on a data center rack; Nvidia InfiniBand Switches, an in-network computing platform;Spectrum-X, the ethernet platform for AI networking; and co-packaged optics switches, among others. Together, Nvidia’s networking business includes all the tech needed for building an “AI factory,” a data center designed for training AI models. Kevin Cook, a senior equity strategist at Zacks Investment research, told TechCrunch that Nvidia’s networking business is one of the most impressive new segments from the company. “[Nvidia’s networking business] reports $11 billion for the quarter; that number is greater than Cisco’s networking business, almost as big as the full-year estimates,” Cook said, adding it does in one quarter what Cisco’s business does in a year. And yet — the business segment doesn’t draw the same attention as the company’s chip business, which is significantly larger. It also doesn’t get as much fanfare as the company’s gaming business, it’s original bread-and-butter business, which is nearly three times smaller. The origin of Nvidia’s networking business comes from Mellanox, a networking company founded in Israel in 1999 thatNvidia acquired in 2020 for $7 billion. Kevin Deierling is a senior vice president of networking at Nvidia. He joined the company through the acquisition of Mellanox. Deierling told TechCrunch that people not knowing about Nvidia’s networking business could be his fault for doing a bad job of marketing it — but he doesn’t like that answer. “People think of networking as just, ‘I got a printer, and I need to connect to it,’” Deierling said. “Jensen said this the first day when he acquired us, he said the data center is the new unit of computing. Networking is a lot more than just moving the smaller amounts of data between a compute node; it’s actually a foundation.” While Deierling said he didn’t really understand why Huang bought the company when he did — he gets it now. Having a networking business alongside its GPU business allows the company to sell its chips with the tech that they work best with. “When Jensen bought Mellanox in 2020, he saw that was the missing piece to make GPUs a complete package,” Cook, the Zack’s analyst, said. Deierling added that he thinks another aspect of Nvidia’s networking success is that it only sells the tech as a full-stack solution, as opposed to individual components, and it doesn’t actually sell the tech itself, but rather through its partners. “I can’t think of other companies that have [the] full-stack capabilities that we have,” Deierling said. “We are really different. We build the full compute stack, fully integrated stack, and then we go to market through all of our partners.” Nvidia just announced a whole new slew ofupdates to its networking systemduring Huang’s keynote address on March 16 at the company’s annualNvidia GTC technology conference. The company launched the Nvidia Rubin platform, which includes six new chips to power an “AI supercomputer.” Nvidia also announced a new Nvidia Inference Context Memory Storage platform and more efficient Nvidia Spectrum-X Ethernet Photonics switches, among other products. “It’s no longer a peripheral to connect the printer, some other slow I/O device,” Deierling said about networking. “It’s fundamental to the computer. In the old days, we had what was called the back lining inside the computer. Today, the network is the back lining of the AI factory, and it’s super important.”
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Nothing CEO Carl Pei says smartphone apps will disappear as AI agents take their place
Carl Pei, co-founder and CEO ofNothing, is imagining a future beyond the iPhone — and it’s a device powered by AI agents, not running apps. “In terms of AI in software, I think people should understand that apps are going to disappear,” said Pei, whose consumer electronics brand makesunique smartphonesand other accessories. “So, if you’re a founder or a startup and your app is like where the core value lies, that will be disrupted whether you like it or not.” Pei made these comments during aninterviewat the SXSW conference in Austin on Wednesday. The founder has talked about an AI-first device before, as this vision helped the company close its $200 million Series C funding roundlast year. At the time, Nothing was pitching the idea of a new kind of smartphone using AI and personalization technology that’s accurate enough for its users to not feel they had to go behind the AI and double-check its output. At SXSW, Pei expanded on his vision for the AI-first device and the steps needed to get there. The initial step, which is being tested by some companies today, is an AI feature that can execute a command on the users’ behalf, like booking flights or hotels. Pei, however, dismissed this step as being “super boring.” The next step is where things could get more interesting, as the AI begins to learn a user’s intentions long-term. For instance, if you wanted to be healthier, the device could give you nudges to help you accomplish your goals. “I think it gets even more powerful when it starts surfacing suggestions for you; you don’t have to manually come up with an idea…when the system knows us so well, it will come up with things that we don’t even [know] we wanted,” Pei explained, comparing this concept to something like ChatGPT’s memory feature. In describing how he pictured an AI-first smartphone, Pei said it would be a device that would do things for you without needing to be commanded to. “The current way we use phones is very old-school. It’s pre-iPhone…there used to be Palm Pilots and PDAs back in the day. And if you think about the user experience, it’s still very similar,” Pei said. “You have lock screens, home screens, apps. You browse different apps. Each app is like a full-screen thing. There’s some kind of app store that allows you to download more apps. So it hasn’t really changed for like, 20 years.” This frustrated him because the technology consumers are using has evolved quite a bit, but the products we use have not. Even simple tasks have us jumping through multiple steps, he explained. “It’s very hard to get things done on a phone,” Pei said. “Let’s say we want to grab coffee. That’s an intention. But to execute that intention, we have to go through so many different steps and so many different apps. It’s probably like four apps to grab coffee with somebody — some messaging app, some kind of maps, Uber, calendar.” He continued: “I think the future of smartphones or operating systems should just be: ‘I know you very well, and if I know your intention, I just do it for you,’ instead of having to go through all the apps manually.” “It should just do it through AI,” he said. This also means devices would have an interface that’s not focused on apps for humans to navigate, but would instead feature an interface designed for the AI agent to use. That doesn’t mean apps are going away in the near-term, Pei cautioned. Nothing’s own operating system even allows users to vibe code their own mini apps today. But eventually, the AI will need to be able to use the “app” in a frictionless way, not trying to mimic human touch on the smartphones by moving through menus and tapping options. “That’s not the future. The future is not the agent using a human interface. You need to create an interface for the agent to use. I think that’s the more future-proof way of doing it,” Pei said.
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