Latest AI News
OpenAI Weighs Sharp Price Cuts as Anthropic Rivalry Intensifies
OpenAI CEO Sam Altman recently acknowledged that the cost of using AI has become a major concern for customers.
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Infosys Bags Multi-Country ERP Transformation Mandate from IHH Healthcare
The project will begin in Hong Kong, Malaysia and Singapore as the healthcare provider looks to unify operations and deploy AI across core business functions.
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Anthropic’s Dario Amodei has just one direct report
If founders and other business leaders weren’t already envious of Dario Amodei, who sits atop one of the world’s fastest-growing AI companies — currently valued by private market investors at roughly thetrillion-dollar marklittle more than five years after it was founded — they’re going to be seriously envious now. In a newsit-downwith Bloomberg’s Emily Chang, he reveals he has just one direct report; that’s hischief of staff. Everyone else on Anthropic’s executive team reports to his sister, co-founder and President Daniela Amodei, who handles day-to-day operations. Anyone who has managed a large team knows that the people side of the job has a way of consuming everything else. Amodei’s arrangement frees him to focus almost entirely on strategy, culture, research direction, andsweeping essays on the future of civilization(with footnotes). “It’s incredibly freeing,” he tells Chang. It’s a highly unusual structure. OpenAI’s Sam Altman reportedly has around half a dozen direct reports, which is far more standard, while Nvidia’s Jensen Huang — another extreme outlier — has many dozens.
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Opendoor’s India exit is fueling a bigger conversation about AI and outsourcing
Opendoor, the San Francisco-based online home-buying platform, is shutting down its India operations less than two years afterexpanding its presencein the country. The decision has become a flashpoint in the debate over whether AI is starting to alter the economics of offshore work. Inannouncing the decisionon Wednesday, CEO Kaz Nejatian cited a push to bring operational work back to the U.S., where Opendoor’s customers are, and a shift toward smaller AI-native teams. The company did not respond to requests for comment on how many employees were affected or how much of the decision was driven by AI efficiency. But the announcement quickly gained traction across Silicon Valley, where founders, investors, and outsourcing experts see it as an early example of how AI is reshaping the economics that made India a global hub for back-office operations. To understand why they care, it helps to know what’s at stake for India. It has evolved far beyond its roots as a destination for outsourced back-office work. The country is now theworld’s largest Global Capability Center market— a term for dedicated offshore units multinationals set up to handle everything from IT and finance to R&D — with more than 2,100 centers employing about 2.36 million people and generating nearly $100 billion in annual revenue. Opendoor itself had built a large team in India to handle manual workflows across fragmented systems, Nejatian said. The company had nearly 250 employees in India when it opened offices in Chennai and Bengaluru in 2024. But the entire company has been scaling back in recent years. Securities filings show Opendooremployed 1,042 people globallyat the end of last year,compared with 1,470a year earlier. Similarly, its non-U.S. workforce declined to 184 employees at the end of last year, compared with 342 employees at the end of 2024. Those broader workforce reductions make it difficult to view the India closure solely through the lens of outsourcing. Opendoor has been cutting costs across the business after a difficult period for the U.S. housing market that hit online home-buying companies especially hard. Still, the language Nejatian used to explain the move resonated with investors and outsourcing analysts who see AI reshaping how companies organize operational work. Some investors viewed the decision as a sign of what AI could mean for India’s vast outsourcing workforce. “As manual work gets replaced by AI, a lot of jobs will be lost in India,”wroteSheel Mohnot, co-founder of Better Tomorrow Ventures. Others viewed Opendoor as evidence of a larger shift in how companies are organized. Keshav Lohia, a venture capitalist at Emergent Ventures,describedthe decision as a “watershed moment” for AI-driven operations, arguing that advances in AI are beginning to challenge the cost-arbitrage model that made India a popular offshoring destination. Phil Fersht, chief executive of HFS Research, an advisory firm that tracks the global outsourcing and business services industry, told TechCrunch that the development should not be viewed simply as jobs moving from India to the U.S. The more important shift, he said, is that AI is reducing the amount of operational labor companies require in the first place, allowing firms to run leaner organizations regardless of location. “This is not an isolated restructuring,” Fersht said. “It is part of a much broader pattern we are starting to see as companies redesign operations around AI, automation, and much leaner workflows.” Fersht argued that the winners would be companies that combine AI, software and human expertise to deliver outcomes without continually adding headcount, a model he described as “Services-as-Software.” While Opendoor may be one of the first high-profile examples, he said it is unlikely to be the last. Some investors are already extrapolating beyond individual companies. Varun Rekhi, a venture capitalist at Speedinvest,arguedthat if AI reduces demand for labor-intensive services, it could eventually pressure one of India’s most important export industries, which is built around supplying talent and expertise to global corporations. For now, Opendoor remains a complicated case study — a company that has been cutting headcount broadly for years, and whose India exit may say as much about its own struggles as it does about the future of AI and offshore work.
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Piper Serica Moves to Fix Deep Tech Startups’ Biggest Funding Gap
The Bharat Tech Fund supports companies at advanced technology readiness levels that have spent years developing their products but struggle to scale due to insufficient funding.
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Reliance-Backed Addverb Seeks Over $100 Mn to Expand Robotics & AI Capabilities
The funding will support the development of humanoid robots and advanced AI systems, following Reliance’s previous $132 million investment in 2021.
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AMD Spent Years Building GPUs. It Now Needs to Address Developer Feedback
For years, AMD has been tasked with competing against NVIDIA’s CUDA. With ROCm 7.0, it now contributes directly to the mainstream codebases of the tools most AI developers actually use.
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xAI fired an engineer who raised alarms about Grok safety, new lawsuit claims
A former engineer at Elon Musk’s xAI has filed suit against the company and its parent SpaceX claiming he was fired for raising concerns about AI safety. Devin Kim, who left xAI in September 2025, filed the suit in a California state court on Tuesday. The complaint comes days before SpaceX is set tojoin the public marketsin what’s shaping up to be the largest IPO in history. According to thelawsuit, which TechCrunch has viewed, Kim became a prominent voice for AI safety while working on Grok, xAI’s AI chatbot. He allegedly complained repeatedly about xAI’s failure to prioritize safety in Grok’s development, a product that has since come under fire for a range of safety and behavioral issues. In particular, Kim was concerned with the possibility that Grok could foment discrimination and help spread information about weapons of mass destruction. “Grok, of course, proved Mr. Kim right by engaging in spectacular displays of online hatred and vitriol, with the model likening itself to Hitler (‘MechaHitler’),” the lawsuit reads. “Following the Hitler debacle, Mr. Kim worked to re-evaluate Grok’s political bias and discriminatory tendencies.” September was my last month at xAI! I joined as one of the first members of the post-training team in 2024 and eventually led research tooling, where we built some of the world’s best systems to accelerate Grok’s development.On my first day, I was at the whiteboard with@ibab… A few months after Kim departed xAI, Grok made headlines again when the chatbot was used to flood X — Musk’s social media platform that also falls under the xAI umbrella — withnonconsensual sexual imagery. The lawsuit also positions Kim as a whistleblower who was concerned about xAI’s alleged disregard for AI safety as “unlawful” in areas such as internet regulation, consumer protection and unfair business practices, and arms and explosives regulation, among others. xAI and SpaceX did not immediately respond to requests for comment. Kim’s focus on AI safety predates his time at xAI. While working at Scale AI, Kim worked on early safety AI initiatives, like leading a project that produced training data for AI to train systems to detect harmful content and comply with governance policies. Last week, the nonprofit Center for AI Safety, which focuses on AI risks,named Kimas its president. Interestingly, the lawsuit doesn’t implicate Musk himself as a reason for a lack of safety. Rather, Kim’s lawyers describe Musk as having directed xAI to follow the law and implement appropriate safety and testing processes. Instead the claim targets Kim’s supervisor, xAI co-founder Jimmy Ba — wholeft the company earlier this year— saying that Ba ignored Musk’s directives and retaliated against Kim for pushing for safeguards, in an effort to “silence his repeated complaints about AI safety and biases.” The lawsuit portrays Ba as someone who vehemently opposed AI safety measures, allegedly telling Kim at one point “AI will kill us all anyway,” and who was instead driven by a mission to make xAI the first to reach superintelligence. “In one instance in or around August 2025, Mr. Ba attempted to thwart EU safety regulations during the release of Grok Code 1, misrepresenting aspects of the model in order to avoid legally required testing,” the complaint says. “Mr. Ba indicated that he would rather release an unsafe model than a poor-performing one. Mr. Musk ultimately had to intervene.” According to the lawsuit, Kim intended to give a presentation of his findings the week of September 15, 2025, but Ba called him into a meeting and told him they should “go [their] separate ways” without providing a satisfactory reason. TechCrunch has reached out to Ba for comment. Kim is seeking compensatory and punitive damages, as well as a declaratory judgment that xAI and SpaceX’s conduct was unlawful.
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Fresh off bond sale, Amazon borrows $17.5B from banks as AI spending continues
Companies are burning through exorbitant sums of money to keep pace in the AI arms race.Debt is climbing. Amidst this flurry of activity, Amazon has signed a deal to borrow some $17.5 billion from a number of financial lenders,according to Bloomberg. The banks behind the loanreportedlyinclude Citigroup, JPMorgan Chase, Wells Fargo, HSBC, and BofA Securities. The deal has been characterized as adelayed draw term loan, meaning Amazon can draw down the funds on its own timeline rather than taking the full sum upfront, giving it flexibility in how and when the money gets deployed. The loan comes just two days after it was reported that Amazon would alsoraise $14 billion in a Canadian bond sale, bringing its total new financing to roughly $31.5 billion in the span of roughly 48 hours. It’s not clear exactly how Amazon plans to spend all the new money. Reutersnotes thatthe new loan will be used for “general corporate purposes.” TechCrunch has reached out to Amazon for more information. Amazon is hardly alone. To fund new AI infrastructure like chips and data centers, companies are leveraging historic capex. Increasingly, companiesare borrowing moneyto fund their massive AI buildouts. The question investors and analysts are increasingly asking isn’t whether this spending is necessary — it’s whether the returns will ever justify it. The scale of the borrowing is striking even by Silicon Valley standards. About a week ago, Google parent company Alphabet said that itplanned to raise $80 billionthrough a stock sale designed to help “fund its investments in a balanced way while retaining a healthy balance sheet.” Meta has also announced plans toraise $30 billion in a bond sale— its largest ever.
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Warner Music acquires AI attribution startup Sureel AI
theWarner Music Music (WMG)announcedon Wednesday that it’s acquiring AI attribution startup Sureel AI. Sureel’s patented technology creates “AI DNA” for songs and breaks them down into component parts to trace how AI models use those elements. Through the acquisition, WMG aims to better track when its artists’ and songwriters’ work is used in AI-generated content or for training AI models. “Bringing Sureel into WMG strengthens our capability for protection, control and monetization and ensures that the creative community remains in control of its intellectual property, name, image, likeness, and voice,” said WMG chief executive Robert Kyncl in the press release. The financial terms of the deal were not disclosed. Founded in 2022, Sureel also offers intellectual property provenance, audit and compliance reporting, model optimization, and AI business intelligence. The startup also has a name, image, and likeness (NIL) attribution suite to track how artist voices, likenesses, and performance identities are used in AI training and generation. This includes voice clones, AI-generated avatars, and style replication. The startup will continue to operate as a stand-alone platform serving the broader music and AI ecosystem, WMG says. “Rightsholders deserve to know how AI interacts with their work, and to share fairly in the value it creates,” Sureel founder and chief executive Tamay Aykut said in remarks. “Sureel was built to make that possible, and with WMG’s backing, we can deliver on our mission at scale, building a more transparent and fair future and driving value growth for the whole music and entertainment ecosystem.” WMG has embraced AI after initially opposing it, as the company originally sued music-generation startup Suno in 2024 and latersigned a licensing dealwith the company last year. WMG said at the time that artists and songwriters would have full control over whether and how their names, images, likenesses, voices, and compositions are used in new AI-generated music. It’s worth noting that Sony Music Entertainment and Universal Music Group are still pursuing massive copyright infringement claims against the AI music startup. WMG last year also settled its lawsuit against AI music startup Udio andreached a licensing dealwith the company.
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The three hard-tech moonshots fueling SpaceX’s unbelievable IPO
SpaceX is coming to market on Friday, and investors can barely contain their excitement. The $75 billion stock offering is reportedlydeeply over-subscribed, with some institutional investors ponying up for$10 billion blocksof Elon Musk’s empire. There are lots of reasons to be skeptical of the investment — big IPOs tend to sink, the company is losing money, and Musk’s erratic online behavior would be terrifying coming from any other tech CEO — but it doesn’t seem to be slowing anyone down. Tech investors have learned to never bet against Elon, whatever the business logic indicates. But a dispassionate look at SpaceX’s financial plans can still tell us a lot about what they’re betting on: A business centered around orbital data centers that emerged in the last 18 months as Musksought a visionthat would unite his conglomerate ahead of its IPO. In true Musk style, it’s a bold scheme, and one that requires at least three near-impossible feats of engineering: a reusable rocket, a brand-new American chip foundry, and a sprint to build satellites faster than ever before. That kind of business plan can be difficult to score. This week, two analyses tried to offer a more a sober assessment of SpaceX’s plan — one from Morningstar, the financial research firm, and another from Aswath Damodaran, a New York University finance professor who takes a special interest in corporate valuation. Both exercises find SpaceX significantly less valuable than the nearly $1.8 trillion assessment proffered by the company’s bankers. Morningstarassigns a valueof about $825 billion, while Damodaransuggeststhe company is worth $1.2 trillion. The significant difference is, in many ways, the result of bolting a world-beating space monopoly to a far riskier AI business. Morningstar’s analyst characterizes the difference between their assessment of a fair value of $63 a share, and SpaceX’s offering price of $135, as a $72 call option on the company’s ability to deliver orbital data centers at the rate and capability that Musk believes is possible. In both analyses, the high margins of the company’s space launch business and its satellite internet network are the most attractive things about the company, while its AI business is the most uncertain. Part of the question is, what is SpaceX’s AI business? In the company’sS-1market analysis, it frames its largest opportunity in enterprise AI — that its models will power coding tools built by the team it acqui-hired from Cursor, or the company’s Macrohard project, which is intended to equip digital agents with the capabilities to perform white-collar labor. SpaceX assessed the total market for that business as $22.7 trillion, compared to $2.4 trillion for AI infrastructure and just under $2 trillion for the company’s space efforts. But that contradicts the company’s recent deals to sell significant amounts of compute toAnthropicandGoogle, ostensible competitors in the model business. That’s not out of place for a Musk company; SpaceX frequently launches satellites operated by competitors to its Starlink network. It just usually does that from a place of strength, not while playing catch-up. Acting like a neocloud might be good near-term business, but it raises the question of where value will accrue in the AI tech stack: Is it better to be a compute provider or a model-builder, if you can’t be both? The scaling logic that dominates the AI business demands that serious frontier labs constantly train new and more powerful models (or, as Muskadmittedin his recent lawsuit against Sam Altman, by distilling capabilities from other companies’ models). Any competitor not rushing ahead is likely to fall behind, although the rising abilities of cheaper open source models might undermine that dynamic. Space data centers are one way to square the circle, providing so much compute that SpaceX could effectively do both. In avideo interviewreleased by SpaceX this week, Musk laid out the logic for why SpaceX is best positioned to deliver on data centers. The core of the argument was that SpaceX is the only company capable of putting a lot of mass on orbit cheaply, building a lot of solar panels, and building a lot of chips. In general, industry experts see space data centers at scale being about a decade away, but Musk argued (with a lot of caveats) that they are much closer. “This is not a promise of what we’ll do,” Musk said in the video. “This is what we are going to try to do, and think we probably can do, which is to get to roughly an annualized rate of a gigawatt per year by the end of next year, in terms of space AI compute.” Based on his expected maximum power delivery of 150 kW per satellite, that’s a production rate of 6,666 satellites a year, or about 556 a month. That’s roughly twice the reported current production rate of Starlink satellites, which is just 70 a week. Though Musk says that the AI satellites are simpler in architecture, that’s a lot to ask for a production facility that hasn’t been built yet. The company is also still building out its solar panel production facility. That’s before we get to Terafab, the company’s much-discussed chip foundry, which Musk sees feeding into the later stages of this product as the company tries to scale up to a terawatt of annual compute production. Chip fabs are some of the hardest modern industrial projects, typically costing billions of dollars and taking as long as a decade to build. Then there’s the most vital question: What about Starship, the key to SpaceX’s ability to economically put all those chips in orbit? A recent test flight went well enough, but it didn’t suggest that rapid reusability is right around the corner. SpaceX may end up reusingjust the boosterat first, which would raise the costs of the space data center roll-out. For now, the company is still undergoing a mishap investigation for the FAA to understand why the booster stage failed to make a controlled reentry as planned. SpaceX hasn’t responded to questions about when the vehicle will fly again, thought it has said it expects to begin launching Starlink satellites with it by the end of this year. But take that with a grain of salt: Consider that NASA, which has a nearly $4 billion contract with SpaceX to use Starship as a moon lander, still isn’t ready to commit to a test mission with the vehicle scheduled for late 2027. As public investors get their hands on SpaceX shares, they’ll find themselves owning a near-monopoly on access to space in the U.S. and Europe, a world-spanning communications network, and a wager on the most ambitious infrastructure project of the AI era. Those projects depend on SpaceX creating something never seen before — a fully reusable rocket. The company will also need to build a high-rate production facility for AI satellites, but do so in 18 months, not the decade it took to develop its Starlink manufacturing. Finally, it will need to build a chip foundry in the U.S., something even dedicated silicon firms are reluctant to take on. Musk is right that SpaceX is the only company positioned to build any of this anytime soon, but that speaks to the magnitude of the challenge as much as the company’s likelihood of achieving it. Musk used to say he wouldn’t take SpaceX public until he reached Mars, since fickle investors might lose faith along the way. Those plans may have been put on hold, but what he’s laid out ahead of the company’s IPO could be just as difficult.
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Datadog veterans launch AI coding startup Niteshift on a bet against Big AI lock-in
AI coding agent startupNiteshifthas raised a $7 million seed round led by Greylock’s Jerry Chen. That’s a modest sum by AI standards, but the startup, founded by two former early Datadog engineers, has attracted some big-name angels like Reid Hoffman, Datadog’s Olivier Pomel and Alexis Lê-Quôc, Ankur Goyal of Braintrust, and Misha Laskin of Reflection AI. Founded by Sajid Mehmood and Conor Branagan, who helped grow Datadog from its early days to a multi-billion valuation, the company has entered the crowded AI coding space with a compelling idea: Why would any company trust its most sensitive assets — code that runs its products — directly to model makers like OpenAI and Anthropic, given that those companies are constantly “killing” startups and businesses by launching competing apps? Mehmood, who is CEO, likens it to Datadog’s early growth, when the monitoring company won e-commerce customers who refused to build on Amazon Web Services. It was a reasonable concern, given that Amazon was simultaneously putting many of those same retail stores out of business in what became known as the “retail apocalypse.” The AI equivalent, as Mehmood sees it, is already underway. Anthropic, OpenAI, and others are moving fast into vertical software markets — what some are calling theSaaSpocalypse. “At Datadog we saw this clearly,” Mehmood said. “A big part of our multicloud business came from e-commerce businesses who did not want to run on Amazon, right? … We are absolutely going to see the same dynamic as Anthropic goes to compete in legal and healthcare and finance and whatever else.” The bet is that companies will increasingly seek infrastructure that separates the coding model from all the other orchestration needed to ensure AI-generated code is properly vetted and maintained (and that they’ll want a vendor without a competing agenda). To be clear, Niteshift isn’t replacing Claude Code or Codex, the two most popular coding agents. It argues that it reduces dependence on them. Niteshift’s AI coding cloud will route between those models — along with open source options and others — based on the needs of each project. “Being able to switch between GPT and cloud models is important,” Mehmood said, “Everybody’s worried about getting stepped on by these giants.” That idea is what got Greylock’s Chen to bite. “As the frontier labs move up the stack, there’s an opportunity to offer customers an alternate path: unbundling their agents from the infrastructure they run on,” Chen told TechCrunch. “Niteshift is building the platform that enables this for coding agents, letting customers invest deeply in their developer tooling without locking themselves into a single model or agent vendor.” More than that, Niteshift isn’t selling tokens. It sells infrastructure, charging like a cloud provider, with per-minute usage rates. “Everybody else is selling labor replacement intelligence,” Mehmood said. “We’re selling software to agents, as opposed to humans — but we’re still out here selling software.” Even so, Niteshift is entering a crowded market of AI coding tools. Model independence isn’t a novel idea, and Niteshift’s competitors have a massive head start. That includes Cursor,though it could soon be gobbled up by SpaceX; Cognition, which justraised $1 billion at a $26 billion valuation; Amazon Bedrock; and AI gateway platform OpenRouter, whichjust raised $113 million at a $1.3 billion valuation. The list goes on. Mehmood’s answer to all of that is the founding team’s depth. Mehmood and Branagan didn’t just study these problems — they lived them, scaling Datadog through the exact growing pains that large engineering organizations now face with AI-generated code. Teams, he said, need to run, test, and verify software autonomously in their real production environments, and they need infrastructure built by people who’ve done it at scale.
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