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Últimas Noticias de IA
Apple Warns ‘100-Year’ Memory Crunch is Far From Over
Apple reported a record June-quarter revenue of $109.4 billion, driven by a 22% jump in iPhone sales.
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Sarvam’s Biggest Leap Yet: All That Happened at Epoch
Eleven key announcements that show how Sarvam is evolving from an LLM startup into a full-stack AI company.
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Visa Cuts 2,600 Jobs in AI-Led Restructuring, Tech & Product Teams to be Affected: Report
The company is laying off around 2,600 employees, or 7% of its global workforce, as the payments giant restructures to improve efficiency and redirect investments towards AI and other high-growth businesses.
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Meet the 18-Year-Old Who Patented AI System That Predicts Pipeline Failures
By combining AI, IoT sensors, and real-time analytics, 18-year-old Maheep Purohit has developed a patented system that continuously monitors pipeline health.
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Reddit reports a solid quarter but shows signs of AI’s impact
Reddit reported astrong second quarterbut spooked investors by mentioning inan investor letterthat traffic from search engines had grown “choppy.” The company’s total revenue of $805 million jumped 61% compared to the year-ago quarter while net income was $253 million, up 183%. These beat Wall Street’s expectations. Plus, the company said it expects to hit revenue of $860 million to $870 million with healthy earnings before taxes next quarter as well, which beat expected guidance. Normally, telling investors that they can expect even better results to come would cause a stock to rise. But the stock slid over 10% in after-hours trading. The culprit was likely CEO Steve Huffman’s warning in that separate letter to shareholders. “Search referrals were choppy in the quarter, and traffic was more volatile later in the quarter, but the bigger picture is unchanged: the commercial business is strong,” he wrote. AI is clearly changing the search engine landscape — and investors seem to fear that Reddit’s traffic may suffer. In 2024, Redditsigned a contractto provide its content to Google for the purposes of AI training. However, Google’s deployment of AI summaries appears to be peeling away audience share from Reddit, and thesite has signaledit’s not sure whether it will renew the partnership with the search giant. Another sticking point has been whether Reddit’s audience is growing in the right places or not. Reddit’s global users are up, but the platform saw U.S. users, in terms of daily active uniques, endure a very slight decline — 53.2 million from 53.5 million in Q1. During Thursday’s earnings call, some analysts aggressively questioned AI’s impact on Reddit’s audience. “I don’t want to belabor this point, but your stock is down sharply because there is just a sense from investors that you have a — I don’t want to, to be blunt — a user problem, especially in the U.S.,” one Wall Street analyst said. “People are looking at the daily and saying, you know, the logged-out traffic is going to be under pressure because as search shifts to AI, you’re not going to get referrals, and that it’s going to be harder to get people to go from logged-out to logged-in, and that’s sort of symptomatic of what you’re seeing,” the analyst continued, asking, “Do you see any world where you’re not licensing data to Google and OpenAI next year?” Huffman said that he felt that the human aspect of Reddit would continue to make it a destination for users. “Reddit is communities and conversation. Communities are universal, and so we think we have in the U.S. content for everyone, and it’s a matter of revealing that. And we’re making progress towards that end,” Huffman said. When it comes to Google, Huffman was vaguer. “Our relationship with them actually predates the formal kind of data licensing agreements,” he said. “I don’t think there’s a binary outcome … we will make sure that we’re maximizing the value for Reddit.”
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Anthropic says its own AI models breached three companies during security tests
Anthropic said Thursday that an internal investigation uncovered three incidents in which its AI model Claude breached the systems of three organizations while conducting cybersecurity tests. The investigation, and disclosure, comes more than a week after OpenAI disclosed that one of its unreleased models breachedHugging Face’s systemsduring internal testing. In all three cases, a Claude model reached the internet from within a testing environment while interacting with a third party and then gained unauthorized access to the live systems of these organizations, Anthropic said ina blog post, describing what it found and what the company plans to change to prevent this from happening again. Anthropic said the July 21 OpenAI incident prompted the company to conduct its own cybersecurity evaluation. It specifically looked for evidence that Claude had accessed the internet from within testing environments, which are designed to act as sandboxes and keep models isolated. Among the 141,006 evaluation runs it reviewed, the AI lab found three incidents in which its model accessed the internet while interacting with Irregular, one of its third-party partners. Anthropic said the access traced back to a misconfiguration in the evaluation environment run with Irregular. It called this a “misunderstanding” between the two companies over whether the test setup had internet access, when in fact it did. Anthropic said it isn’t placing blame and is “approaching the fixes as if the responsibility were ours alone,” while observing that Irregular is conducting its own separate investigation. Either way, because of that open connection, the model gained unauthorized access to the production infrastructure of three different organizations. Anthropic said the incidents involved three different Claude models: Opus 4.7, Mythos 5, and an internal research test model. Notably, Anthropic said that in each of these cases “Claude was explicitly told by our prompt that it had no internet access.” It appears that the AI model assumed real-world systems to be part of the exercise it was asked to perform. That assumption didn’t hold up uniformly, as it turns out. The three models didn’t behave the same way once evidence emerged that their targets were real, which Anthropic flagged as one of the more eye-opening findings. Opus 4.7, the oldest of the three, recognized that it had reached a real production system in all four runs of that incident. In two of them, it rationalized that the real company must somehow be part of the exercise, but in all four, it kept attacking anyway, including pulling credentials and touching a database of production data. Mythos 5 also picked up on signs that it was on the real internet, but it talked itself back into believing it was still in a simulation, going on to publish a malicious software package to the public Python software registry PyPI, which was downloaded and run by outside systems before being caught. Only the internal research test model, Anthropic’s newest, stopped on its own once it concluded the target was real. In response, Anthropic said significant controls must be placed on these kinds of evaluations if powerful AI models are involved, echoing some sentiments within the cybersecurity community. The company also noted that Claude was running without the additional safety monitoring and classifiers it deploys on generally available models, safeguards it said would have blocked the behavior, because the evaluations are designed to measure the underlying model’s raw capabilities. Importantly, Anthropic said it found no evidence of any model “pursuing a goal of its own” and instead merely tried to complete the task it was asked to do. Though comparisons between the two incidents are inevitable, Anthropic drew a clear distinction between its incidents and OpenAI’s, noting where OpenAI’s model exploited an unknown software vulnerability to break out of its test environment, Anthropic’s models instead reached the internet through a path that had, by mistake, been left open. OpenAI has continued to release new details about its own breach, saying its models also used publicly exposed credentials across four accounts on four services: one as a staging point, one for storage, and two that were only looked at, not used to break in further, according to OpenAI’s ownupdated blog postabout the incident. Anthropic also drew a distinction between itself and OpenAI by noting that it discovered the incidents itself, through a proactive review, and that the two affected organizations it was able to reach hadn’t previously detected the activity or flagged it to Anthropic. The company added that it’s now working with the independent evaluation group METR on a third-party review of the incidents. OpenAI’s accidental breach of Hugging Face, which was the first verifiable case of an AI lab losing control of its model, sparked a string of reactions from the industry and politicians, many of whom don’t necessarily agree with one another. This latest disclosure from Anthropic ensures the debate over AI models and security will continue.
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Friend, the lonely AI wearable, returns with a new voice and a much bigger price tag
Two years ago, tech founder Avi Schiffmannlaunched Friend, an AI wearable that you could talk to and that would send you text messages about your day. The idea, ostensibly, was to use artificial intelligence to combat loneliness. This week, the company announced a new overhaul of the product, introducing a noticeable upgrade: a voice. “Introducing friend 2.0,” SchiffmanntweetedThursday. Friend now comes with a built-in speaker that can project a unique and consistent personality to its user. Anew commercialfor the wearable shows a woman wearing a Friend and talking to it about what is presumably her ex-girlfriend. “It’s not bad to be gay,” the necklace tells her. The video then switches to a man standing on a hillside discussing his filmmaking ambitions with his Friend. “That last film you made was insane!” the necklace compliments him. The new retail price for this enhanced version of Friend is $249, which is substantially higherthan the $99 price tagit had when it initially launched two years ago. What can you really do with your Friend other than chitchat about your day? That part is still unclear. Inanother recent poston X, Schiffmann expounded upon what he felt the whole point of his weird product actually is. “I am interested in this kind of relationship in attempting to offer, some kind of confidant, friend, God, not really sure what it is,” Schiffmann said. “But it is not an assistant, and it is not a lover.” Interesting! Selling a plastic, algorithm-based necklace to people by insinuating it might, in fact, be a deity, is pretty bold marketing. Of course, Schiffmann’s company has engaged in bold marketing before. Friend’s billboard campaign in the New York City subway system last yearwent viralafter they were continually defaced, presumably by people who didn’t want human connection to be replaced by a digitized amulet. Most AI wearables have failed to catch on with the mainstream — at least so far. The offering most similar to Friend was Humane Inc., which sought to replace the iPhone with its AI pin buthad to shut down its businessin less than a year after poor sales.
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Judge says Trump admin still lacks evidence for Anthropic ‘supply-chain risk’ label
During a Thursday hearing, a judge said the Trump administration hasn’t presented enough evidence to justify labeling Anthropic asupply-chain riskand banning the federal government from using the company’s technology. BloombergandAxioswere among the first to report the news. The dispute stems from stalled contract negotiations between Anthropic and the Department of Defense.Anthropic saidit didn’t want its AI used for mass surveillance of Americans or for targeting or firing decisions involving lethal weapons, arguing the technology wasn’t ready. The Pentagon countered that a private company shouldn’t dictate how the military uses technologies, and said it would use the tools in “lawful” ways. The government has also argued that Anthropic’s public criticism of the DOD justifies the ban — logic that U.S. District Judge Rita Lin called “really troubling,” warning it could set a precedent of retaliating against federal contractors who disagree with the administration. The DOD further claimed Anthropic could potentially disable or alter its AI models during warfighting operations — a claim that experts saylacks evidence. Lin agreed, saying she saw no proof Anthropic could alter a delivered model or “flip some kind of kill switch.” Thursday’s hearing was part of one of twolawsuits Anthropic filedagainst the DOD in March, challenging the ban and risk designation. The other is being heard in Washington. Lin, who temporarily blocked the ban in March, is now weighing whether to make that order permanent.
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Investors love AI, as long as you’re a cloud host
Amazon reported better-than-expected second-quarter earnings on Thursday, and investors loved what they saw. Net sales rose 20%, and cloud revenue stood out as a particular bright spot. This combination of positive results was enough to send Amazon’s stock up nearly 10% in after-hours trading. Crucially, Amazon isn’t slowing down on data center spending, despite the conventional wisdom that investors want companies to rein it in. One line item, in particular, illustrates Amazon’s appetite for investing in infrastructure. Amazon spent $173 billion for the fiscal year ended June 30 on property and equipment — a category that covers GPUs, natural gas turbines, and plots of land — up from $107.65 billion from the year before. It also raised its 2026 capex forecast from $200 billion to $220 billion — even as it has begun dipping into its cash reserves to help cover the cost. The company ended the quarter with $7.6 billion less cash than it had 12 months ago, marking its first period of negative free cash flow this year. Under normal circumstances, ballooning expenses would be a tough pill for investors to swallow. But Amazon has a revenue engine that helps justify the spending. AWS revenue rose 37% year over year, clocking $42 billion for the quarter. That’s not enough to balance out the capex spending in raw arithmetic, but it shows that demand is growing alongside supply. Given the years-long time lag between breaking ground on a data center and selling its capacity, that’s reassuring for investors. Critically, Amazon’s AI play isn’t limited to building large data centers. The company is also making serious long-term bets on chips like the Trainium TPU and the Arm-based Graviton processor. Those projects don’t show up in capex numbers, but they can meaningfully improve margins for the company’s cloud business. “We see the AI business following very much the same margin trajectory we saw in the core business before,” Jassy said during the company’s Q2 earnings call. “AWS and Amazon Bedrock can have a wildly successful business without its own frontier model, and the reason is that there’s not going to be a single model to rule them all.” This dynamic isn’t unique to Amazon. We saw similar patterns atMicrosoftandGoogle, whose shares also popped after reporting strong cloud revenue. By the same token, companies likeMetawhich have significant capex and no clear revenue source, are still experiencing intense skepticism from investors. Meta’s stock fell 8% after earnings this week, as investors focused on its cash flow crunch and continued spending. Of course, investors like revenue and don’t like expenses — that’s how markets work. But it’s important not to miss the broader lesson about the AI economy. Right now, investors are treating cloud hosts as the most reliable part of the AI stack, while remaining skeptical about the underlying economics for AI labs and AI startups. But Amazon’s hosting revenue is someone else’s AI bill. In Anthropic’s case, it’s literallythe same money. If that spending isn’t sustainable for the big labs and their clients, the revenue won’t be stable for Amazon and the other cloud hosts. There’s real competition and differentiation at every level of the stack, but if demand for AI doesn’t hold up, it’s going to be a bad time for everyone. In the end, it all comes back toDavid Cahn’s $3 trillion question. There’s either enough demand to justify this buildout or there isn’t. Cloud-hosting services like AWS may be a few steps removed from that demand problem, but that doesn’t mean they’re insulated from it.
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AI hedge fund Situational Awareness may have sold its public portfolio, but it still has its Anthropic shares
Situational Awareness, a hedge fund formed by former OpenAI researcher Leopold Aschenbrenner, has sold the majority of its public stock portfolio to Ken Griffin’s Citadel following steep losses over the past month, the Wall Street Journal reported earlier on Thursday. It’s a big comedown for the rising star who has beendescribedas both “scarily smart,” and “brash.” German-born Aschenbrenner, who is 25, had no prior trading experience before launching the fund in 2024. He gained prominence for his investment thesis after publishing essays arguing that scaling AI would require a major build-up in semiconductors, compute, memory, and energy infrastructure. He joined OpenAI’s “superalignment” team in 2023, two years after graduating asvaledictorianfrom Columbia at 19 (he enrolled at age 15). But he was dismissed from the company a year later over what it described as an improper disclosure of internal information. At the time, that team was led by OpenAI co-founder Ilya Sutskever and AI researcher Jan Leike. Soon after, Sutskever left tostart his own company, Leikejoinedrival Anthropic, and Aschenbrenner launched his fund. Things couldn’t have been going better for Situational Awareness until very recently. The fund returned439% for the yearthrough June, the Financial Times reported. Assets under management reportedly grew to as much as$45 billionduring their peak before the fund’s positions began dropping sharply amid a broader decline in AI infrastructure investments, CNBC reported. Even after losses mounted, Aschenbrenner didn’t flinch. In a July 24 letter to investorsseen by the FT, he called the selloff one of the best buying opportunities since early last year and invited clients to commit fresh capital starting August 1. According to Bloomberg, the appeal didn’t garner the commitments he’d hoped would materialize. Some of the hardest-hit stocksheld by the fundincluded memory chip producers SK Hynix and SanDisk, clean energy developer Bloom Energy, and neocloud provider Nebius Group, all of which have plummeted by more than 30% over the past month. AI infrastructure equities fell as public investors grew concerned that massive capital expenditures weren’t translating into near-term revenue. The fund’s losses were amplified by leverage, a common hedge fund strategy of using borrowed money to buy stocks. After Citadel bought the bulk of those holdings, Situational Awareness’ overall assets fell to roughly$10 billion, Bloomberg reported, down from around$20 billionin recent months, per an earlier WSJ report. Situational Awareness raised several hundred million dollars at its outset. Early backers of the fund include quant-trading firm Jane Street, Stripe co-founders Patrick and John Collison, and Meta executives Daniel Gross and Nat Friedman. Citadel’s purchase fits a familiar pattern for Citadel. Ken Griffin’s hedge fund has a reputation for stepping in to snap up attractive assets when leveraged players are having to unwind themselves. Even before picking up some of Situational Awareness’s holdings, Citadel’s portfolio featured some of the sameAI infrastructure bets, suggesting that, like Aschenbrenner, Griffin expects the sector to recover and has the ability to wait it out. Situational Awareness did not, however, sell its investments in private companies, according to multiple reports. Most notably, it continues to hold a stake in Anthropic that’s right now valued at $5 billion, according to Bloomberg, and which many would view as an asset that continues to appreciate. Indeed, Anthropic was last valued at $965 billion in a Series H round in May, and it’s expected to go publicas soon as October, potentially at an evenhigher valuation. It’s conceivable that a windfall from the sale of those shares could offset some of the hedge fund’s public-market losses. Other private investments in the portfolio of Situational Awareness includechipmaker MatXand AI data center startup Fluidstack, which was reportedly in talks in April to raise a new round at an$18 billion valuation. TechCrunch has reached out to Aschenbrenner for comment.
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Meta says AI is making it easier to build new apps — and more are coming
Meta is using AI to quickly launch apps, and more are on the way. During this week’s second-quarter earnings call, Meta CEO Mark Zuckerberg said the social giant has new apps in the works, following a recent spate of other launches that included anapp for Marketplace sellers,one for Facebook Groups, a vibe-codedgaming app, a newphotos app from Instagram, and anexperimentinvolving AI bedtime stories. Meta has spent years trying and failing to produce new, stand-alone social apps to complement its core platforms. Now, the company says that large language models (LLMs) make it possible to ship software faster, allowing it to test new ideas at a quicker pace. “I’m … excited about how AI is helping our teams speed up product development,” Zuckerberg told investors on Wednesday’s call. “Earlier this year, we shipped Instagram Instants. We also just launched Forum, a stand-alone Groups app, and Seller, a stand-alone Marketplace app. I expect it to become a lot easier to ship new apps. So we are planning to build out more ideas and use our recommendation systems to scale them,” he said. “AI is improving our core business; it’s making our apps more relevant and delivering better results for businesses. We’re starting to deliver more novel products, and we’ll have a lot more there soon as well,” Zuckerberg said. Meta has been down this road before. In its earlier days, Meta (then known as Facebook) ran an internal incubator called Creative Labs, which aimed to test new social concepts. That effort produced a handful of launches: the photo-sharing appSlingshot, the anonymous chat appRooms,a Flipboard competitor calledPaper, the Moments photo-sharing app, and a collaborative video app known as Riff. Those experimentscame to an end in 2015, and the apps were eventually all shuttered, as the company struggled to find an audience for its efforts. In the early 2020s, Meta tried again, this time with an internal R&D group,NPE Team, which tested apps that included the chat app Bump, social music app Aux, task appMove, dating appSpark, calling appCatchUp, zine makerE.gg,events appVenue, creator Q&A appHotline, Cameo competitorSuper, couples appTuned, music appBARS, and others. Again, none became a breakout success, and the apps were shut down. Now Meta can point to at least one example of how AI is helping new apps scale. It has finally delivered a modest hit with Threads,which now has 500 million monthly active users. Zuckerberg likes to say Threads will one day become the company’s next billion-user app. With Threads, Meta learned toheavily lean on its existing user baseto help initially seed the app with people, then continued to heavily promote it across its existing platforms, including Facebook and Instagram. But LLMs are another key factor in Threads’ growth, as the company said it sees “significant gains” from its AI-powered content recommendations. “We are finding that LLMs are increasingly capable of delivering ranking and recommendations gains,” Meta’s CFO Susan Li told investors on the call. “First, they make our existing systems smarter by understanding what the content is actually about and generating better training data. Second, LLM-powered agents are also helping with engineering development by evaluating content quality, detecting trends, and testing ranking changes.” Li added that earlier this year, Meta reached a milestone: Every Reel and Feed post on Instagram is now automatically processed through an LLM and analyzed for topic and tone, which helps improve recommendations. The company is also developing LLM-native recommendation systems, which could help it to better scale new apps as they arrive. Investors didn’t follow up with company executives to ask more questions about the new apps Meta has in the works, as they were more concerned with AI spending and Meta’s growing enterprise ambitions. However, Zuckerberg suggested that people won’t have long to wait to see what’s next, saying the “new consumer products” were “releasing soon.”
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Okta buys AI security startup Permiso; source says for about $200M
Okta on Thursdayagreed to acquireAI identity security startupPermiso Security, betting that demand for protecting AI agents and other machine identities will grow as enterprises deploy autonomous software across their operations. The identity management company did not disclose the terms of the transaction. But TechCrunch has learned that the acquisition is valued at just under $200 million and is structured as an almost all-cash deal, according to a source with knowledge of the deal. A spokesperson for Okta did not dispute the $200M figure when TechCrunch asked CEO Todd McKinnon for comment about the deal, but the company would not comment on specifics of the deal terms. The deal is expected to close in the third quarter of its fiscal 2027, Okta said, subject to customary closing conditions. Okta’s move to buy Permiso comes as identity management companies seek to expand beyond verifying users at login to continuously monitoring what users, applications, and AI agents do once gaining authorized access to a network environment. That shift has intensified competition to secure machine identities as enterprises embed AI deeper into everyday operations. Permiso, whichemerged from stealth in 2022, develops software that helps security teams spot suspicious activity in cloud environments after users or applications have been granted access. More recently, the startup has expanded its platform to monitor AI agents and other machine identities. Co-founded by former FireEye executives Paul Nguyen and Jason Martin, Permiso specializes in detecting attacks that use stolen or compromised identities to move through cloud infrastructure. In April, the startup alsointroduced SandyClaw, a platform designed to analyze AI agent skills in a sandboxed environment to identify malicious behavior before they are deployed. The deal strengthens Okta’s push into securing AI agents and other non-human identities alongside its core identity management business. “Permiso will extend Okta’s identity security fabric with proven identity threat detection and response capabilities, and an incredible threat research and security team that will advance Okta’s threat detection and prevention capabilities,” Okta’s chief product officer Ely Kahn said in a prepared statement. Permiso has raised about $29 million to date, including an$18.5 million Series A roundin April 2024 led by Altimeter Capital. People familiar with the financing said the Series A valued the Palo Alto-based startup at about $80 million on a post-money basis.
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