最新 AI 资讯
₹40,000-Crore PCB Imports to Be Replaced by Domestic Manufacturing as Jewar Emerges as Electronics Hub: Ashwini Vaishnaw
Jewar is poised to emerge as one of India's leading hubs for electronics and semiconductor manufacturing in the coming years
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Coinbase Cuts AI Spend by Half With Open-Weight Models, Smarter Routing
Coinbase CEO Brian Armstrong said the objective is “not to suppress usage” but to build infrastructure capable of supporting exponential growth in AI workloads while keeping costs under control.
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Madhya Pradesh Premier League Taps Emergent to Bring AI into Cricket Administration
Emergent and Delhigence AI power custom software for Madhya Pradesh Premier League, bringing AI-driven efficiency to cricket administration.
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Ford rehires ‘gray beard’ engineers after AI falls short
Ford executives said they have hired 350 veteran engineers — some of them were former employees, while others had been working at suppliers — after artificial intelligence and automated systems failed to deliver the desired quality level. Bloomberg reportsthe company’s chief operating officer Kumar Galhotra told journalists that Ford had been “relying more and more on automated quality systems” with disappointing results. So the company “brought back technical specialists,” and those specialists “hunt for failure points before a part ever reaches the plant floor.” Charles Poon, Ford’s vice president of vehicle hardware engineering, added, “Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product.” To be clear, this doesn’t mean Ford is abandoning its AI plans entirely. Instead, it’s using the rehired employees — referred to as “gray beard” engineers — to train younger staff and reprogram AI tools. This rehiring seems to be paying off, with Ford anticipating that it will lead to $1 billion in reduced costs this year. The automaker also claimed the top spot among mainstream brands in the JD Power Initial Quality Survey released this week.
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Why Wall Street thinks US memory maker Micron is the next Nvidia
Micron, the Boise, Idaho-based memory chip maker, has captured Wall Street’s heart. Whether the love affair endures will heavily depend on how long the AI-driven supply crunch for memory chips lasts. Micron promises that it has shored up its position for the long term, which would allow it to withstand a sudden drop in demand or overcapacity of supply. And Wall Street has become a believer, helping Micron briefly surpass the market valuation ofMeta and Teslafor the first time on Thursday, though it floated back down by Friday to nearly match them. Specifically Micron closed Friday’s trading with a market cap close to $1.27 trillion, while Meta was at $1.39 trillion and Tesla was at $1.42 trillion. Micron’s stock has soared over 236% in the past month alone, closing Friday at $1,132 a share. In comparison, it spent years upon years before mid-2025 at below $100 a share. It’s a dizzying rise for a company that most consumers associated with the tiny memory cards that, back in the day, were commonly needed to boost PCs, smartphones, or other device storage. Wall Street isn’t sweating over that product line. Micron is benefiting from the AI data center buildout boom that has created a shortage of system memory chips, both DRAM and NAND, which Micron makes, particularly High-Bandwidth Memory (HBM). A single AI server requires magnitudes more memory than a laptop. AI system makers like Nvidia, as well as the hyperscalers building their own systems, are buying up large quantities of memory, such as Microsoft, Amazon AWS, Google, Meta and Oracle. This is forcing all the other companies who need memory to hoard it as well, from PC makers like Dell and HP, to other kinds of device makers. This lack of supply, which has been dubbedRAMageddon, is predicted to persistinto 2027. And it’s already driving up the price of consumer electronics like Apple products and Xbox consoles. With the whole tech industry clamoring for more memory, Micron’s delivered blockbuster third-quarter earnings last week. Revenue quadrupled year-over-year to $41.45 billion, and profits skyrocketed from $1.88 billion to $28.2 billion over the same period. Micron also provided a positive outlook, forecasting fourth-quarter revenue of between $49 billion and $51 billion. And Wall Street, which has been eager to find more public AI-related companies that may do as well as Nvidia, became even more enamored. The historic problem for memory chip makers like Micron and Samsung is that building out manufacturing facilities to increase capacity is a time-consuming, expensive endeavor. And demand often falls just as companies can increase capacity, creating a glut and subsequent price drop. Micron got ahead of any AI bust chatter by emphasizing a series of long-term supply agreements, including with Nvidia and AI labAnthropic, that would presumably protect it. The company said in its earnings presentation that it has signed 16 strategic customer agreements across the data center, consumer, and auto market segments, which it expects tofundamentally transform its business model. That seemed to convince a number of analysts that this company could be another long-term, profitable investment. In a research note, William Blair tech analyst Sebastien Naji noted demand growth continues to outpace the rate that new cleanroom space can come online. “Given the strong likelihood of continued ASP growth in the coming quarters and improving revenue visibility thanks to a rapidly expanding set of long-term agreements (SCAs) with key customers, we see potential for more durable earnings growth and reiterate our Outperform rating,” Naji wrote. Whether Micron really can sustain itself for long-term without a bust cycle remains to be seen. But for a brief moment on Thursday, this U.S. company was more valuable than some of the industry’s giants.
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Dating Apps are Hardcoded to Match Looks. Wavelength's AI Wants to Fix That
Rejecting traditional swipe-based algorithms, Wavelength uses conversational AI to match people based on personality and behavioural insights.
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SoftBank’s CEO isn’t the only one with questions about Elon Musk’s orbital data center hype
Not everyone is buyingElon Musk’s vision for orbital data centers. Masayoshi Son, the founder and CEO of Softbank,argued at a recent shareholder meetingthat building data centers in space won’t do much to cut costs and will take too long when “in the battle for AI, the next few years will be far more important than what might happen a decade or so from now.” On the latest episode ofTechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I discussed Son’s remarks as part of a broader discussion that includedOpenAI’s plans for custom chips, chipmakerGroq’s new $650 million funding, and much more. Kirsten noted that it’s “very ironic” that Son is playing the skeptic here, given SoftBank’s “long history of wild bets.” Sean, meanwhile, said that when Musk talks about “making a constellation of satellites — satellites that need to be replaced every few years as well — to make up an ‘orbital data center,’” he’s just “guaranteeing that much more business” for SpaceX. Keep reading for a preview of our conversation, edited for length and clarity. Sean O’Kane:Listen, neo-clouds are the new oil, and everybody who wants to make money is pivoting to a neo-cloud. I’m proud to announce that TechCrunch is now a neo-cloud, give us all your money. I mean, this is the thing you do. It seems like there are so many players that are compute constrained, so anybody who has a shot at being able to lease out that compute is taking it, whether that’s Groq, a company that was semi-hollowed out by Nvidia, or Allbirds, which went into bankruptcy and and emerged from it as a new neo-cloud provider instead of selling shoes — Tim Fernholz didan interview with the new CEO of of that new effortthat I would definitely recommend people go read. Or whether you’re SpaceX, where your idea was: I’m gonna build an AI platform that’s gonna have an addressable market the size of U.S. GDP, but before we get there, we’ll just rent out our compute. And we saw this continue to happen with SpaceX, where it’s not as big as the deals that they’ve struck with Google or Anthropic, butthey just signed another deal, [their] first post IPO deal, to rent out compute to another smaller player. They’re continuing down that road. You know, I can see this being a business for Groq in the near term. The question with all of these is how durable is it in the long term. Anthony Ha:If we’re talking about SpaceX and their AI business and data center business, we also have to talk about these comments that Masayoshi Son, the CEO of SoftBank, made recently, where he basically said:What is the point of data centers in space?Which is a question we’ve asked on this show. And it speaks to, again, this sense in the industry of being really, really compute constrained — they need to build as many data centers as possible, [and] there’s all kinds of reasons why that is proving to be challenging here on Earth, so maybe space is the answer. But I think Son makes some pretty fair points about: All this stuff we’re talking about, even if it all works — and the costs are going to be very, very serious to make it work — this is not happening for years and years and years, so this is not a solution to any immediate problem, as far the current need for data centers goes. Kirsten Korosec:I just want to point out that SoftBank has a long history of making wild bets. I think it says something when Son comes up and asks the question that a lot of people have asked. I mean, there are a lot of VCs and founders [who] have been swept up into the idea of orbital data centers and it seems like suddenly everyone’s on board. When just a couple of years ago, I think, if someone had mentioned that, it would get slapped down a little bit. So I do think it’s an important part of the process that someone who has a pretty high profile is asking that question. But it is very ironic to me thatheis the one asking it, because if you look athis pitch deck, they’ve thrown a lot of money at some pretty bold ideas. Sean:WeWork! Listen, we’re going to be saying this for a lot over the next couple years. The idea of putting these things in space is going to be an interesting engineering challenge and certainly an interesting economic challenge. Anthony, what you said is definitely right to a certain extent. Elon Musk is a person who hates red tape and you know, there are no NIMBYs in space so of course he’s going to try and do that. To me, it comes down to: The business as it stands now for SpaceX, especially its launch business, is just overwhelmingly reliant on Starlink. The reason that they are 80 or 90% of the launch market globally is not just because they’ve done all these things that are better than pretty much every other launch provider around the globe, it’s also because they have Starlink that is driving up that number. If you remove Starlink from the equation, they would be closer to — I don’t know, maybe 20% or 30% of the launch market, or 40%, but it certainly wouldn’t be 90%. And when you talk about making a constellation of satellites — satellites that need to be replaced every few years as well — to make up an “orbital data center,” quote unquote, you’re just guaranteeing that much more business for your launch business. And I just can’t stop myself from coming back to that point. Kirsten:I want to really quickly say that [SpaceX’s] other big business is renting out their compute, by the way. So back to the chip conversation. We’ve come full circle. Anthony:One of the other themes that may run through this episode is this idea oftalking your own book. This is not a new phenomenon. Executives at tech companies, or any other company, what they’re predicting for the future is ultimately the future that is going to be advantageous to their business. But I think it’s something that’s just always worth remembering when we’re having these conversations about big AI companies, because it is this moment of incredible uncertainty, and we’re all wondering: What does the job market look like in the future? What effect is this going to have on the environment? What are the skills I need to learn? All these AI CEOs or AI investors, they all have thoughts on that. And it’s not that they’re wrong or that they are being deliberately misleading, but in each case, there’s an asterisk to these predictions. In Musk’s case, he’s talking about something that would be very good for SpaceX’s business. In SoftBank’s case, they arevery, very heavily invested in data center projectshere on Earth. Sam Altman is the other notable figure who’srolled his eyes a bitat the orbital data center idea — and again, he and Elon Musk obviously havea long and complicated history together. All of which is to say that there’s just no objective, impartial observers here. It’s all these people with baggage and tremendous amounts of money at stake.
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Apple Vision Pro exec is reportedly leaving for OpenAI
Paul Meade, the Apple vice president in charge of the Vision Pro headset, is leaving the company to join OpenAI’s hardware team,according to Bloomberg’s Mark Gurman. Meade also reportedly led the development of the AI-powered smart glasses thatApple plans to launch next year. The costly Vision Pro was not a hit, but Apple is hoping that more affordable smart glasses willhelp it compete with wearable devices from Meta. Gurman frames this departure as a byproduct ofJohn Ternus’ imminent elevation to Apple CEO, and of Ternus’ decision to shake up the hardware engineering team, which left some of the company’s vice presidents feeling like they’d been demoted. OpenAI, meanwhile, is already working with Apple’s former chief design officer Jony Ive on an AI device that CEO Sam Altman has claimed will bemore peaceful and calm than an iPhone, though reports last fall suggested the company wasstruggling to get the details right. TechCrunch has reached out to Apple and OpenAI for comment.
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Asian AI startups launch Mythos-like models as Anthropic’s export ban drags on
On Wednesday, Chinese cybersecurity firm 360reportedlyunveiled Tulongfeng, an AI tool it says can go head-to-head with Anthropic’s Mythos. That’s the cybersecurity-focused AI model that is reportedly so powerful, the Trump Administrationhas currently banned it and its more restricted version, Fable 5, from the hands of non-Americans. Earlier the same week Sakana AI, a Tokyo-based AI startuplaunched Fugu, a model named after the Japanese word for blowfish. The company says this frontier AI model “stands shoulder-to-shoulder with leading models like Anthropic’s Fable 5 and Mythos Preview.” It is also designed for agents, with an ability to orchestrate access to other models though their APIs. The two new Asian model products come as the U.S. government’s ban drags on. It’sorder that prevents Anthropicfrom global access to Mythos and Fable occurred two weeks ago. A spokesperson at Sakana AI told TechCrunch that release of its new model was “entirely coincidental,” yet that hasn’t stopped it from capitalizing on the moment. It’s website advertises “delivering frontier capability without the risk of export controls.” “Sakana Fugu is something we have been building since last year — the research behind it was presented at ICLR this spring, and it reflects an approach that is central to how we deliver frontier-level value at Sakana AI. We were confident in the product on its own merits; the timing simply happened to coincide with a moment that brought it more attention than we expected,” the spokesperson said about launching during the Mythos/Fable export ban. Sakana, co-founded in 2023by former Google researchers Ren Ito, Llion Jones and David Ha, makes affordable generative AI models that work well with small datasets and are optimized for the Japanese language and culture. While the company is targeting Fugu at Japanese businesses and government agencies looking to reduce their exposure to tightening export controls, it isn’t yet proclaiming a lasting shift away from U.S. AI in Asia. “U.S. models remain important to Asia,” the spokesperson said, a view consistent with remarks co-founder Ren Ito made atthe G7 summit in Evianlast week, where AI access and export controls were one of the central topics. “We’d characterize the current moment in those terms rather than as a permanent realignment toward any one set of players.” Sakana co-founderRen Itoelaborated on that view in an op-ed published in the Project Syndicate last week. He urged the US federal government, that consider that its “first priority should be to preserve access,” for America’s closest allies, and argued that “AI should not become a technology that is hoarded; it should be one that is developed together.” David Ha, co-founder and CEO of Sakana, described Fugu as more than just a land grab during a vulnerable moment for a US competitors. It is designed to coordinate agent usage among many models. “Orchestration Models are the next frontier, beyond bigger models,”he wrote on X.Relying on a single provider for national infrastructure, he argued, is a risk the recent export controls made impossible to ignore. “Access to top models can disappear overnight,” he wrote. “Collective intelligence is the practical hedge against this concentration of power.” While Tokyo-based Sakana positioned Fugu as a hedge strategy, a way to preserve access to frontier AI, not replace it, China’s 360 wasn’t hedging. The Chinese firmreportedlyunveiled two AI security tools. Tulongfeng is designed to automatically discover software vulnerabilities, and Yitianzhen is built to automate cyber defence and incident response. The product launch, however, came with a message. According to Reuters, 360’s founder Zhou Hongyi described vulnerability-finding AI as a national strategic asset, and flagged what he called the risk of “one-way transparency”, a situation in which some actors could access advanced vulnerability-detection capabilities while others could not. Anthropic had been on a historic growth trajectory. The US AI lab saidits run-rate revenue crossed $47 billionin May 2026. How much of that depends on Asian enterprise customers is not publicly known. But in the weeks since the export order took effect, at least two companies, one in Tokyo, one in Beijing, have stepped into the space it left behind. Even if US companies could win back trust should this ban ever end, local alternatives, trained to better understand local language and nuance, are already filling the gap. 360 did not respond to a request for comment.
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The fittest founder in the room got cancer. Here’s how he used AI to fight back.
Conno Christou doesn’t leave things to chance. He tracks his sleep with a Whoop band, cross-references it with an Oura ring, and gets nearly 100 biomarkers checked every year. He had been doing the annual bloodwork for four consecutive years, following the protocols of longevity researchers like Peter Attia and Rhonda Patrick. He was optimizing his supplements, his circadian rhythm, his protein intake. At 35, building his second company, he was as dialed-in on the latest in health research as anyone he knew. His last checkup, in 2025, was green across the board. “It was the best I’d had in years,” he says. Then, after a workout, his arm swelled. He didn’t think much of it at first. A week passed before he saw a doctor, who found two blood clots in his veins and scheduled surgery. But the pre-op exams changed everything. A doctor walked back into the room and told him the procedure wasn’t happening. “We see an 11-by-11-by-8 centimeter mass behind your sternum,” the doctor said. A biopsy confirmed what Christou had never before even contemplated. He had an aggressive, fast-growing form of non-Hodgkin’s lymphoma — a rare diagnosis affecting roughly one in 420,000 people, caused by a random genetic mutation with no connection to lifestyle, diet, or stress. The tumor had only existed for about three months. In three more weeks, it would have reached stage four. “Lucky in my unluckiness,” Christou told this editor this week from his home in Athens, where he lives part time. “It was only found because I went in for something else entirely.” What followed was an education in the limits of the medical system, and in what a determined patient can do about that with tools now available. His first oncologist, a renowned specialist, recommended the lighter of two available chemotherapy regimens. Christou booked his first infusion three days out. Then, the night before, he sought a second opinion. That second doctor didn’t hesitate. He recommended the harder regimen — continuous in-hospital infusion, cycling every three weeks across six months — citing Christou’s specific pathology. The lighter treatment carried roughly a 60% success rate for his presentation. The aggressive one brought that number to around 85%. Two world-class doctors. Diametrically opposite recommendations. “As founders, we hold the wheel,” Christou says of the propensity of many people to accept what they are told — and why more should not. “You hear many things. You don’t have to follow the first advice.” He didn’t opt to just follow the advice of the second physician, either. Over the next two days, he gathered 12 opinions in total — drawing on his professional network, reaching out to hematologists and oncologists in the US and abroad, calling in every favor he could. Eleven to one voted in favor of the harder path. He took it. The decision, he says, didn’t feel brave so much as logical. He was already a data-driven person, and now the stakes felt existential to him. Over six months of treatment, Christou approached chemotherapy the way he approached building a company, as a marathon of sprints — each of them with a finite cycle and each week filled with data points. He had done a mandatory 25-month military service in Cyprus at age 18 and he borrowed from that experience, too. He was going to be a good soldier, he told himself. Trust the process. Six cycles. Get through it. He wore his Whoop throughout, and found it remarkably accurate at predicting the days his immune system would bottom out, sometimes flagging them before symptoms arrived. He kept a symptom journal using voice transcription, logging every shift, every side effect, every medication and counter-medication. He narrowed his focus to three variables: sleep, nutrition, and, first and foremost, psychology. (“It moves the needle more than anything,” said Christou. “I never asked ‘why me’ — not once. That question has no useful answer.”) He fed all of it — blood results, scan data, wearable output, journal entries — into Claude. He’s far from alone in turning to chatbots for medical guidance. Apublic opinion pollreleased in March found that a third of American adults now use them for health information and advice. Thestoriesaccumulating online suggest that for some patients, AI is delivering what the system couldn’t. Experts urge caution; Danielle Bitterman, clinical lead for data science and AI at Mass General Brigham, has told the New York Times in recent months that general-purpose chatbots arefrequently wrongand “have not been thoroughly evaluated” for personalized diagnoses. Christou doesn’t disagree. “It didn’t replace the doctors,” he says, but it “helped me ask the right questions.” For a condition as rare as his — one an oncologist might see once a year — access to a model that had absorbed the full body of medical literature was, he says, simply not the same as a Google search. The model proved critical at the end of treatment. His final PET scan — the imaging used to detect active disease — came back ambiguous. His oncologist began discussing a second line of therapy, potentially radiotherapy, near his heart and lungs. It was an alarming development. Christou again did his homework. He read that for this specific lymphoma, the false-positive rate on end-of-treatment PET scans is around 60% — a statistic that still astonishes him. “It’s 2026,” he says. “Sixty percent.” He fed all three of his PET scans and his MRI into Claude, which flagged a known but easily overlooked phenomenon: in patients under 40 recovering from this type of lymphoma, the thymus gland can reactivate after chemotherapy, showing up on imaging as what appears to be active disease. Given his age, his specific scan characteristics, the model put the probability of that explanation at roughly 90%. He sought three more opinions. The fourth doctor confirmed it: thymus rebound. There was no active disease. No radiotherapy was needed. He was clear. Christou is still unfolding what the last year has meant, for his health, how he works, and how he thinks about time. He built Keragon, his current company, before any of this happened; it’s an AI-powered platform that helps medical practices automate their administrative operations. But going through the system as a patient has given him new perspective. He watched nurses and doctors buried under tasks that had nothing to do with care. He received the same chemotherapy protocol as an 80-year-old woman, the side effects managed through a cascading chain of additional drugs, each causing problems of their own. He says he’s certain that we will look back at this era of treatment and cringe. He takes Sundays off now, mostly. He tries to be present — at lunch with friends, at home with his dog, in conversations that might once have felt like a distraction from work. A VC friend told him something years ago that he said he kept replaying during treatment: Be happy now. He says it’s among the hardest things to do and yet he finally appreciates its importance. He says he’d be happy to talk to anyone going through something similar to share notes, compare experiences. He seems to means it. “It’s not happening in 10 years,” he says of what AI can already do for patients willing to use it. “It’s happening today.”
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When AI Walks the Fashion Runway
AI is replacing cameras with prompts, shrinking production timelines from days to hours. For fashion brands, it's a breakthrough. For thousands of creative professionals, it's a reckoning.
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OpenAI Launches GPT-5.6 as US Government Clears Anthropic’s Mythos 5 Return
Both companies are phasing access to their latest AI models while working with Washington on a framework for deploying increasingly capable systems.
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