Latest AI News
Anthropic & OpenAI Partner with Private Equity Firms to Scale Enterprise AI Deployment
The companies will help enterprises deploy their tools across different businesses.
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Krutrim Cloud Hits ₹300 Crore Revenue After Quitting AI Chips & Foundational Models
Krutrim said it has become financially self-sustaining and does not require immediate external funding, including from its founder.
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Shekhar Kapur Joins Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi to Connect Cinema & AI
Kapur’s new role highlights how filmmakers and artists are increasingly shaping conversations around AI’s future and its creative potential.
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Blue Machines AI Brings Multilingual Voice Automation to Aditya Birla Capital
With voice agents now active across key businesses of Aditya Birla Capital, Blue Machines AI is pushing automation deeper into the customer lifecycle from acquisition to support.
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MathCo partners with Google Cloud to push ‘workflow native AI’ adoption
MathCo has partnered with Google Cloud to help enterprises move beyond isolated AI use cases and embed intelligence directly into end-to-end workflows.
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Deeptech or Deep Hype? Decoding Uttar Pradesh’s Roadmap Post Puch AI
With GCC and startup policies armed with incentives, Uttar Pradesh hopes to sprint to the front of deeptech innovation. But its startup ecosystem still shows signs of structural immaturity.
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Karnataka Pioneers SpaceTech Centre of Excellence to Boost Commercial Innovation
The Centre is designed to bridge the gap between research and real-world applications by enabling the commercialisation of space technologies.
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As workers worry about AI, Nvidia’s Jensen Huang says AI is ‘creating an enormous number of jobs’
When it comes to the specter of AI’s labor-displacing potential, Jensen Huang thinks that the American worker has nothing to fear. Duringa conversationMonday night with MSNBC’s Becky Quick hosted by the Milken Institute — an economic policy think tank, the jovial Nvidia CEO said that AI was an industrial-scale generator of jobs, not the harbinger of mass unemployment that so-called “AI doomers” have often accused it of being. A number of different topics were broached during the talk, but a central theme that kept coming back was the ongoing economic anxiety surrounding the AI industry and whether it was something Americans should be legitimately worried about. At one point Quick noted: “This is happening so quickly. Is there a bigger dislocation than we’ve seen in the past that leads to greater inequality? And what do we do about that?” Throughout the night, Huang struck an optimistic note. “AI creates jobs,” Huang asserted during the discussion, adding that “AI is [the] United States’ best opportunity to re-industrialize” itself. Huang noted that the AI industry is powered by a new breed of industrial factories—the kinds producing the hardware that acts as critical infrastructure for the AI business. (Huang’s company notably sells a lot of that hardware.) Those factories necessarily need workers, as does the rest of the blossoming AI industry. Just because a specific task is automated, that doesn’t mean that a person’s entire job is going to be replaced, Huang reasoned. People who believe this “misunderstand that the purpose of a job and the task of a job are related” but not ultimately the same thing, he said. In other words, Huang’s argument is that even when AI takes over a discrete task within a role, the broader function that employee serves in an organization is likely to remain. Relatedly, Huang was critical of people who allege AI will dominate humanity or that it will wipe out huge sectors of the economy. “My greatest concern is that we scare…people—all the people that we’re telling these science fiction stories to, to the point where AI is so unpopular in the United States, or people are so afraid of it, that they don’t actually engage it,” he said. Ironically, much of the “doomer” rhetoric has been generatedby the AI industry itself, and critics maintain that such hyperbole has been used as a marketing gimmick designed to gin up buzz and excitement for products that aren’t anywhere near the capabilities that such rhetoric suggests. It remains to be seen what kind of long-term impact AI will have on the overall economy. That said, reputable financial and academic organizations have suggested that asmuch as 15% percent of jobsin the U.S. will be eliminated over the next several years as a result of AI.
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Misleading CVs are Forcing AI Hiring to Rethink How Talent is Identified & Evaluated
Because historical hiring was itself biased—favouring certain schools, companies, and demographics—the AI reproduces those biases at scale.
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OpenAI’s cozy partner Cerebras is on track for a blockbuster IPO
In the long-running saga that is Cerebras Systems’ IPO, the finish line is finally in sight. The AI chipmakersaidon Monday that it is preparing to sell 28 million shares at $115 to $125 a share. This would raise $3.5 billion and give it a $26.6 billion market cap at the high end. That would be a nice bump in just a couple of months for the late investors who piled into its$1 billion Series Hat a $23 billion valuation in February. It would also be a boon to OpenAI and a few of its executives. Should Cerebras pull off an initial public offering at or above the high end, this will be the largest tech IPO of 2026 so far. It could also prove the appetite for even bigger blockbuster offerings in the wings, like SpaceX and possibly OpenAI and Anthropic. Cerebras offers an AI-specific chip called the Wafer-Scale Engine 3 that challenges GPU-based AI chips. Cerebras says its chip is faster for inference while using less power than such competitors. Inference is the compute needed to process user prompts. A long list of top-name investors stands to gain from a healthy IPO. Rick Gerson’s Alpha Wave; Benchmark (via partner Eric Vishria); Lior Susan’s Eclipse; Fidelity; and Foundation Capital (via partner Steve Vassallo) are its largest shareholders with more than a 5% stake, accordingto the company’s SEC filing. The company says its list of investors also includes 1789 Capital, Abu Dhabi Growth Fund, Abu Dhabi’s G42, Altimeter, AMD, Atreides Management, Coatue, Moore Strategic Ventures, Tiger Global, Valor Equity Partners, and VY Capital. Plus, Cerebras names onits websitea long list of angel investors, too. These include OpenAI founder and CEO Sam Altman, OpenAI founder and president Greg Brockman, former OpenAI chief scientist (now founder of his own AI startup) Ilya Sutskever, OpenAI board member and Quora CEO Adam D’Angelo, Sun Microsystems and Arista co-founder Andy Bechtolsheim, Intel CEO Lip-Bu Tan, and several other tech luminaries. While Sam Altman’s stake wasn’t large enough to disclose in the SEC filings, he was quoted in its S-1. That’s because Cerebras’ relationship with OpenAI is even more noteworthy than its angel investors. This relationship was even presentedas evidence by Elon Musk in his lawsuit with OpenAI.OpenAI had at one point considered acquiring Cerebras, according to legal filings by Musk’s attorneys that claim he was unaware of all of the OpenAI execs’ personal investments in the company. That deal never happened, but OpenAI did become one of Cerebras’ largest customers. In fact, in December, OpenAI loaned Cerebras $1 billion, secured by warrants that allow OpenAI to buy over 33 million shares, the S-1 discloses. So while OpenAI is not a large shareholder now, it could become one. Cerebras had hoped to go public in 2024 but was delayed due to a federal review of an investment from Abu Dhabi-based cloud provider G42, which was (and still is, the chip company says) a major customer. That IPO attempt was ultimately shelved. A year later, Cerebras sought to raise more cash. In September,it raised$1.1 billion at an $8.1 billion post-money valuation led by Fidelity and Atreides. A few months later, Cerebras signed its new multi-year agreement worth morethan $10 billionwith OpenAI that included the loan and warrants. In February, it raised the $1 billion Series H, its last mega round. Should investors eat up the IPO, then OpenAI and its executives stand to gain in more ways than one. That seems likely. Banks are already fielding $10 billion worth of orders for the $3.5 billion worth of shares on offer,Bloomberg reports.That kind of demand indicates that the company will likely price its shares even higher than this announced range, raising even more cash for itself and more value for its investors.
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Elon Musk’s only AI expert witness at the OpenAI trial fears an AGI arms race
When do we take AI doomers seriously? That’s a key subtext of Elon Musk’s attempt to shut down OpenAI’s for-profit AI business. His attorneys argue that the organization was set up as a charity focused on AI safety and lost its way in pursuit of lucre. To prove that, they cite old emails and statements from the organization’s founders about the need for a public-spirited counterweight to Google DeepMind. Today, they called the only expert witness to speak directly to AI technology: Stuart Russell, a University of California, Berkeley computer science professor who has studied AI for decades. His job was to offer background on AI and establish that this technology is dangerous enough to worry about. Russell signed anopen letterin March 2023 calling for a six-month pause in AI research. In a sign of the contradictions here, Musk also signed the same letter, even as he was launching xAI, his own for-profit AI lab. Russell told jurors and Judge Yvonne Gonzalez Rogers that there were a variety of risks associated with the development of AI, ranging from cybersecurity threats to problems with misalignment and the winner-take-all nature of developing artificial general intelligence (AGI). Ultimately, he said that there was a tension between the pursuit of AGI and safety. Russell’s larger concerns about the existential threats of unconstrained AI didn’t get aired in open court after objections from OpenAI’s attorneys led the judge to limit Russell’s testimony. But Russell has long been a critic of the arms-race dynamic created by frontier labs around the globe competing to reach AGI first and called for governments to regulate the field more tightly. OpenAI’s attorneys spent their cross-examination establishing that Russell wasn’t directly evaluating the organization’s corporate structure or its specific safety policies. But this reporter (as well as the judge and the jurors) will be weighing how much value to put on the relationship between corporate greed and AI safety concerns. Virtually every one of the OpenAI founders have strenuously warned about the risks of AI, while also emphasizing the benefits, attempting to build AI as fast as possible — and hatching plans for AI-focused for-profit enterprises they would control. From the outside, a clear issue here is the growing realization inside OpenAI after its founding that the organization simply needed more compute spend if it was to succeed. That money could only come from for-profit investors. The founding team’s fear of AGI in the hands of a single organization pushed them to seek the capital that ultimately tore the team apart, creating the arms race we know today — and bringing us to this lawsuit. The same dynamic is already playing out at a national level: Senator Bernie Sanders’ push for a lawimposing a moratoriumon data center construction echoes AI fears enunciated by Elon Musk, Sam Altman, Geoffrey Hinton, and others. Hodan Omaar, who works at the trade organization the Center for Data Innovation, objected to Sanders citing their fears without their hopes, telling TechCrunch that “it is unclear why the public should discount everything tech billionaires say except when their words can be recruited to fill gaps in a precarious argument.” Now, both sides of the case are asking the court to do just that: take part of Altman’s and Musk’s arguments seriously, but discount the parts that are less useful for their legal argument. Correction: The article was updated to correct the name of Stuart Russell, University of California, Berkeley computer science professor.
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Image AI models now drive app growth, beating chatbot upgrades
Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures. This marks a shift from earlier days, when the release ofnew modelspowering theconversational experiencesdrove more demand, alongside the new features like avoice chat interface. For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models,Appfiguresfound. For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of theGemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed. Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction ofits GPT-4o image model in Marchof last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out. Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after itsSeptember 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.) Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue. Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only $181,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release. Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue. Among the three, only ChatGPT turned the increased attention into actual dollars. OpenAI’s 4o image-generation model led to an estimated $70 million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said. The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern. While DeepSeek R1 drove 28 million downloads afterits January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model.
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