Latest AI News
Zeta Co-Founder Bhavin Turakhia Launches Neo With $30 Mn Personal Bet on Enterprise AI
Neo will roll out Tasket for AI-led task delegation, Friday for AI assistants and agents, Studio for knowledge management, and Drive for human-agent file collaboration.
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US investors will soon get access to SK Hynix, another memory maker riding the AI boom
South Korean memory chipmaker SK Hynix, rival to Samsung and U.S.-basedMicron, is planning to sell nearly 17.8 million shares in a U.S. IPO, the companysaid on Monday. Should its shares sell well (and there’s indication that they will), the company could raise around $28 billion, based on SK Hynix’s closing share price last Friday in Seoul,Bloomberg reports. SK Hynix will be offering American depositary receipts (ADRs), a type of certificate that lets U.S. investors buy a foreign stock without trading directly on an overseas exchange. Each ADR will represent a tenth of a common share. It is expected to price those securities on Thursday and begin trading on Friday. Like Micron, SK Hynix is riding an AI-fueled boom credited to AI in both sales and stock price. Its first-quarter revenues were up nearly 200% over the same quarter last year, it said, and its stock is up about 260% so far this year. This is because systems that run AI are very memory intensive. As hyperscalers like Amazon, Microsoft, Google, and Oracle race to build out so-called AI factories, and as new AI data centers multiply nationwide, demand has outpaced supply, creating a shortage of memory chips — including high-bandwidth memory (HBM), DRAM, and NAND (the different types of chips that store and move data inside AI systems). The situation has been called “RAMageddon.” Apple executives said the shortage is forcing it to raiseprices on Mac computers and iPads. South Korean tech companies, led by SK Hynix and Samsung, have vowedto spend over $550 billionon building out new manufacturing capacity to keep up. That’s actually a risky venture. By the time those facilities are built, memory needs for AI may change, leaving them with more supply than the market wants and, potentially, crashing prices. But for now, Wall Street is looking for another Nvidia, andmemory chipmakers are among the closest optionsthat they have. Micron, the closest U.S. comparison, has shot up nearly 700% over the past year to a more than $1 trillion valuation, fueled by record AI-driven memory demand and revenue.
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The ‘first’ AI-run ransomware attack still needed a human
Last week, researchers at cloud security firm Sysdig said they’d documented the first known case of “agentic ransomware.” It was an extortion operation, dubbed JadePuffer, in which an AI agent — not a human — handled the technical execution of a real-world cyberattack from start to finish. The agent broke into a vulnerable server, stole credentials, moved through the target’s network, encrypted files, and even wrote its own ransom note, adapting to obstacles along the way like a human hacker would. Coverage of the funding described it as run “without any human oversight,” with “no human at the keyboard.” That’s not quite thefullpicture. In aninterviewon Monday with CyberScoop, Sysdig’s Michael Clark, the company’s senior director of threat research, clarified that a human was still very much involved — just not in the technical execution. “A human still set up and pointed the operation and provisioned the infrastructure behind it, the command-and-control server, the staging server used for the stolen data and chose a victim,” Clark said. The credentials used to break into the victim’s database, he added, weren’t harvested by the AI agent itself; someone obtained them separately, through a prior compromise, and handed them to the operation. None of this contradicts Sysdig’s original claim, and the technical details of the attack remain notable on their own — wild, even. The agent got in through a known bug inLangflow, a popular open-source tool for building LLM apps, then moved on to a production MySQL server and exploited another known flaw to gain admin access. It encrypted over 1,300 configuration records and not only left behind a ransom note that it wrote itself but it left a Bitcoin address where the ransom could be sent. Sysdig hasn’t disclosed who was targeted. The techniques were fairly ordinary apparently, what stood out was the speed and transparency involved. The agent fixed a failed login in 31 seconds, narrating its own reasoning in natural-language code comments the whole way. One detail that initially seemed to muddy the picture has since been clarified. Clark had told CyberScoop that Sysdig found “multiple models were used in the attack,” citing harvested keys for OpenAI, Anthropic, DeepSeek, and Gemini — language that left open the question of whether several models actively powered different stages of the intrusion. Asked to clarify, Clark told TechCrunch that those keys were simply part of what the agent stole, not evidence of what was driving it. “The agent swept the Langflow host for anything valuable — provider API keys, cloud credentials, cryptocurrency wallets, and database configs — and those provider keys were part of the loot,” he said via email. “They are indicative of what the attacker considered worth taking, but they do not tell us which model was making the decisions.” On the model actually running JadePuffer, Clark said Sysdig “was not able to identify the specific model driving the agent” and has no visibility into its system prompt or configuration. Microsoft researcher Geoff McDonald’s theory,offered on LinkedInseveral days ago, is worth revisiting in that light. McDonald suspected an open-weight model with safety training stripped out, rather than a frontier model, was behind the attack, based on his own red-teaming experience showing frontier labs’ safety layers hold up well. Sysdig’s own account doesn’t confirm or rule that out. McDonald’s post also warned that ransomware campaigns are now bounded primarily by attacker budget rather than human effort, raising the possibility of “thousands or tens of thousands of simultaneous campaigns.” That concern is a little harder to square with what Clark described Monday. (If a human still has to choose each victim, provision infrastructure, and obtain database credentials for every operation, that’s a bit of a bottleneck, at least.) Either way, Clark told CyberScoop, while Sysdig hasn’t seen the same operation hit other victims yet, given how cheap it is to run an agent, he expects that to change.
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You can now customize Siri’s pace and expressivity in the latest iOS 27 beta
With the latest iOS 27 developer beta, Apple is giving testers an early look at one of the upcoming improvements toits AI-powered Siri: the ability to adjust how quickly and expressively the AI assistant speaks. In iOS 27 beta 3, out today, Apple has enabled the voice controls for “Pace” and “Expressivity” that were previously labeled as “Coming soon” in the first developer beta releases. The update is part of Apple’s broader effort to make Siri feel more natural and personal, as it rebuilds the assistant around generative AI. Like ChatGPT and others offering voice AI assistants, letting users customize how the AI sounds is an important aspect in helping connect people with the new technology. However, ChatGPT’s voice-customization options allow users to go even further, as the ability to adjust the AI’s warmth and enthusiasmwasrolledout in December 2025, alongside options to configure the base style and tone. The latter lets users adjust OpenAI’s assistant to be more friendly, professional, candid, or quirky, among other styles. This is reflected not only in how ChatGPT speaks, but also in how it presents information to the user. You can customize Siri’s voice in iOS 27 beta 3pic.twitter.com/qFV8L1e7di First introduced atApple’s Worldwide Developers Conference(WWDC 26) in June, Siri’s voice controls let users personalize their Siri experience beyond just choosing a male- or female-sounding assistant. Now beta testers will be able to switch between a range of voices with different accents, and then use sliders to change how slowly or quickly Siri speaks and how much human-like emotion its voice conveys. As you make the adjustments, Siri will practice saying some common things, like “You have one new message,” so you can get a sense of how the different voices sound. The AI version of Siri is deeply integrated across the updated version of iOS, where it will allow iPhone owners to start conversations by speaking, swiping down from the Dynamic Island at the top of the screen and typing, tapping on the phone’s side button, or even by using the brand-new stand-alone Siri app. Other, more minor updates are also rolling out with iOS 27 beta 3, including anupdatedReminders app icon. (We should note some people on X are also reporting losing access to the new Siri after updating, or seeing their phone again begin indexing their data — typically, the first step in optimizing Siri AI for search.)
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Vercel CEO Guillermo Rauch on the fight to split off models from agents
Known for its cloud infrastructure that allows developers to deploy agents without managing servers,Vercelhas quietly become one of the most central companies in AI software. The company currently sees 6 million deployments a day, half of them triggered by coding agents, and more than 1 trillion tokens flow throughthe company’s AI gatewaydaily. After the company’s ShipNYC conference last week, we sat down with Vercel CEO Guillermo Rauch for his take on this moment in AI, and how platform companies like Vercel end up competing with major labs. Here’s a lightly edited transcript. It feels like there’s a different energy in the community this year, fewer pilot programs and more focus on how to make things work well in practice. I’m sure you’ve seen that a lot with clients, but I’m curious what that journey has looked like within Vercel. Last year was about prototyping. The sky’s the limit, unleash the agents, everyone can build, and so on. We did that, and we learned a lot because we had hundreds of agents organically developed and deployed within the company, and then you started getting into the realities of agents in production, and some of the challenges. The biggest lesson for me was the home-run use cases, the two killer apps of agents. One is the coding agent, of course. That’s driving a lot of the token utilization in the world, but when you produce so much software, you need somewhere to put it. The second killer app of agents is the internal agent that helps you run the company. The challenge there is, how do you securely access data? How do you audit what the agent is doing? How do you get a trail of all of the tool calls and access controls that the agent had to incur in order to get a job done? To solve that, we came up with this framework called Eve, where you can lay out an agents’ instructions and skills in natural language. And another tool is Vercel Sandbox, where you put the agent in a little cage. It can have the freedom still to express its intelligence, but then you can apply policy on what data it can access and what data can leave the sandbox. What sort of problems does that help you avoid? For [the] sandbox, the biggest advantage is data control. A real risk of AI that I always think about is, when you get a coding IDE like Devin or Cursor, if you’re in the wrong setting, they may train on your entire codebase. I remember talking to the president of Airbus about this. You have decades of wealth of very specific C++ code for aerospace engineering. Someone comes in and installs the wrong developer tool and boom, all the code goes out to the cloud for training. I’m curious to hear more about that second killer use case. We all know about coding agents, but what does an internal corporate agent look like in practice? So, there’s a sales rep sitting out there [in Vercel’s office]. She works on install base. Her job is to grow existing accounts. The bottleneck for people like her has not been her creativity, intelligence, ability to build relationships, it’s been data. “I don’t understand what accounts are growing faster. Give me the five accounts that have added the most seats in the last two weeks, so that I can prioritize my work.” She couldn’t ask that question in the past. She needed to wait until a Q1 project for a new sales dashboard completed. We were in that bottleneck for years at Vercel, and it was really frustrating because on the R&D side, we’re the fastest-moving company in the world. But on the sales engine, the Salesforce engineering [side], I was so incompetent. I had never opened Salesforce in my life when I started. Now I feel like I can actually have impact across the entire company, because Eve can be used for our customer-facing agents and can be used to improve productivity. Same technology, it’s just APIs. Agents are forcing companies to open up, and that will have dramatic long-term implications. So many of these SaaS giants build their entire kingdoms on trapping your data, and that’s incompatible with agents. How do you see client relationships with the big AI labs changing? Last year there were a lot of people picking one lab partner — saying they would build everything on OpenAI or Anthropic. Now they’re saying, I understand how this all works — model, harness, data platform, sandbox, gateway — every piece is plug and play. You can use OpenAI, you can use Anthropic, or you can use Gemini. We’re seeing a lot of growth of Gemini, even though it’s not on the news as much, because people are optimizing for production now. The reality is, when you’re optimizing for production, you start looking at a price/performance, and Gemini models have awesome price/performance characteristics. You also bring in open models, so DeepSeek and GLM-5.2 are taking off. The data doesn’t lie. There are places where you’re in direct competition with the labs too, right? Just the other week, OpenAI released a new set of tools that publish directly to the web without having to leave the OpenAI enclave. It’s a natural next step for them to host little websites. And it’s a great opening for us, because now people will think of ChatGPT as a tool for making websites. And then if they keep asking the model questions about web hosting, the model recommends us. But you’re right, as the models or platforms add more capabilities, they come in direct competition with the infrastructure platforms that already exist. I really think at this point we’re deciding on whether the model and the agent are going to be coupled. Do you get all your intelligence from one place? Or do you get a module or a library or a building block from one provider, and then you build on top of it. That’s more like software engineering has always been, and that’s really what we’re bringing to market. We’re going to be the AWS of this generation, so obviously we’re fighting for a world of open protocols.
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Reddit is using LLMs to solve a problem LLMs largely created
It’s easier than ever for bad actors to spew spam across the internet as powerful large language models (LLMs) become effortlessly accessible. If you’ve spent about 10 minutes on the internet in the last few years, you will know that this means spam and bot content have become an even bigger problem than they already were. Reddit says itdeveloped toolswith LLMs to cut down on spam, much of which was created with LLMs in the first place. It’s a bit ironic, but in the AI era, platforms have no choice but to fight fire with fire. According to the platform, Redditblocks23 million spam views per day and catches about 25,000 new spam posts and comments each day. Social platforms have been building automated spam reduction tools for years, but Reddit says these updated tools are catching spam at a higher rate. “We leverage LLMs to catch the highly subtle, coordinated patterns of fake behavior and artificial hype that older systems once missed,” a Redditblog postsays. The company claims it reduced users’ exposure to spam by 20% from January to March compared with the prior three months. Platforms like YouTube, Meta, and Instagram allow users to post AI-generated content so long as they disclose it, and TikTok is going as far as letting userstoggle how muchAI-generated content they want to see. If platforms are able to detect AI-generated content faster, that also means that they have the potential to flag violative content like hate speech more quickly. But platform experts have continuallyreminded usthat AI content moderation must be paired with human moderation to get the mosteffective results.
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Microsoft lays off nearly 5,000 employees across Xbox, commercial sales
Microsoft cut around 4,800 roles, or 2.1% of its global workforce, on Monday — the latest in aseries of layoffsthat’sstoking fearsthat AI will replace people at companies. The layoffs will hit Xbox and commercial sales the hardest, with Xbox losing 1,600 staffers today, according to memos shared with Microsoft’s staff. Here’s a snippet from amemofrom Amy Coleman, EVP and chief people officer: Our business is changing because the world around it is changing. The way technology is built, deployed, and used is transforming faster than at any point in my time here. Our customers’ needs are shifting, the business models that serve them are shifting, and that means the work itself — what we do, where we focus, and how we’re organized — has to transform too. Companies don’t get to choose whether their industry changes; they only get to choose whether they change with it. That means we will need to adjust resources and roles and shift how we operate so we can have the greatest impact for our customers. Coleman stressed that the roles being eliminated today “are not being replaced by AI,” but noted, “what is true is that AI is changing how work gets done.” “Some of the tasks we do every day can now be automated, and that means we all need to keep learning, keep building new skills, and keep adapting as the work evolves,” Coleman wrote. To many feeling the sting of unemployment, that’s a distinction without a difference. The layoffs build on Microsoft’s recent launch of itsFrontier Company business unit, which is focused on delivering enterprise AI deployments with the firm’s existing AI tools and an army of forward deployed engineers. That move is backed by a $2.5 billion investment, mirroring a common theme we’re seeing among layoffs this year — job cuts are correlating with increased AI spending. Speaking about the Xbox layoffs, Coleman said little: “We are restructuring to position the business for long-term success. Engineering teams across the company will also evolve their structure and priorities to meet customer needs and innovate for the future.” Of today’s 4,800 layoffs at Microsoft, 1,600 will hit Xbox, with about 3,200 cuts in total expected through fiscal year 2027,according to Asha Sharma, CEO of Xbox. In an email she sent to employees on Monday, Sharma called this “the most significant restructure in Xbox history.” “Our business today is not healthy,” Sharma wrote. “We are operating at margins that are 3–10x lower than comparable platform and publishing businesses.” She added that Xbox made bets like its monthly subscription service Game Pass, alongside moves to grow its portfolio of content and invest in multiplatform, among other attempts to breathe life into the business. None of those strategies grew at the expected pace, leading to the core business weakening even as Xbox added more teams and investment. “And now the industry is facing the most severe hardware crisis in its history,” Sharma said. “We must reset Xbox.” As part of the shift, Microsoft will transition four of its gaming studios to operate under new management, ensuring preservation of intellectual property and ongoing projects. Specifically Compulsion Games and Double Fine Productions will return to independent studios, according to Sharma. Ninja Theory and Undead Labs are coming under new ownership with funding to complete and grow some of their more popular games. According to Sharma’s memo, Xbox is also flattening management hard, cutting the current 14 management layers to no more than five, but ideally three. As part of this major organization redesign, Xbox is making longtime executive Helen Chiang chief operating officer with end-to-end profit and loss authority across content, hardware, platform, and services. Xbox’s restructuring plan centers around narrowing focus by dropping sprawling creative bets that don’t produce platform-scale returns, and instead homing in on core strategic pillars like Mojang and King, the studios behind Minecraft and Candy Crush. The Xbox layoffs come as the gaming industry shrinks amid new generative AI opportunities. Companies building world models — like Google DeepMind, World Labs, General Intuition, Luma AI, and Runway — have received millions in funding over the past year and garnered plenty of hype for their playable world model demos. All of those companies see gaming as a near-term opportunity for commercialization. In April,Microsoft offered buyoutsstructured as voluntary separations to an undisclosed number of employees —some estimatesput the number at around 5,500 — with the goal of building high-performing teams. Last year, Microsoft laid off about 15,000 employees across two rounds. The eliminations are part of a series of layoffs in the tech industry that’s seen close to 154,000 people lose their jobs just in the first half of 2026, with Big Tech firms like Meta, Oracle, Amazon, and Cognizant cutting thousands of workers. Microsoft said that along with Monday’s cuts, it’s working on ways to keep staff on by reskilling workers or placing people in new roles. “Over the past year, we have redeployed more than 4,000 employees into new roles, including another 500 this month,” Coleman said. Microsoft did not immediately return a request for comment and more information. This article has been updated with more details into the Xbox layoffs. It was originally published July 6, 2026, at 8:08 a.m. PT.
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If you use Google, you’re training its AI. Here’s how to opt out.
Consider this a belated PSA: A recent change to Google’s privacy settings is allowing the company to store more of your data, including media such as “images, files, and audio and video recordings,” to improve its AI models. In other words, if you upload any media to Google’s Search services, it’s being used to train AI unless you opt out. The change came about via an under-the-radar update to Google’s Search services privacy settings, announced in June via a customer email. With the update, the company essentially opted people into this expanded AI training under the guise of giving users more control over their saved history and personalized recommendations. The update introduced two new settings, Search Services History and Personalized Recommendations, allowing you to configure how your activity is used to personalize your Google experience and how long your web and app activity is saved. This update applies beyond Google Search itself, and also includes other search services such as Maps, Shopping, Flights, Hotels, Translate, and News. For instance, when you use Google Lens to search for something visually by snapping a photo, that image may now be saved for AI training. Similarly, if you use the newerSearch Livefeature to search via voice input in the Google app, those audio recordings could be saved, as can any other Google voice search. If you use Google Translate to practice speaking, that audio is saved, too. The changes reflect a broader industry shift toward gathering data by any means necessary to improve AI services. Instead of relying solely on information scraped from the web, Google and others are increasingly collecting data that people upload or create when using their services. Meta is another example of a consumer-facing tech company doing this at scale,training its AI on users’ imagesand media, as well as oncontent recorded by its AI glasses. Google confirms the media-training use directly, stating in that email to customers: “Like your Search Services History, your saved media is also used to develop and improve Google services and technologies, including AI models and safety measures.” Itshelp documentationechoes this, noting that the company “uses your history to provide, develop, and improve its services (such as training generative AI models) and to protect Google, its users, and the public with the help of human reviewers.” Some of this storage is temporary and tied to making the product work, but per Google’s own language, saved media can also be retained specifically to train its AI. The good news is you have some control here. You can change your preferences on theSearch Services HistoryandSearch Services Personalizationpages. On the former, you can uncheck the “Save Media” box separately from the “Search Services History” box, or uncheck both. You can also configure how often you want saved data automatically deleted — after 3 months, 18 months, or 36 months. From there, you canjump to this pageto dig into other privacy settings, including Web & App Activity, Timeline, YouTube History, and more. Beyond saved media, Google also uses your search history, location, and other information from the websites you visit to personalize your experience on Google, including which ads are shown. Before this update, Google let you configure what historical search data was saved via its “Web & App Activity” settings. That’s now been separated into two settings: the Web & App Activity data and the new Search data setting, which is on by default. That means if you make a change to the Web & App Activity data retention settings in an effort to opt out of having your data stored by the tech giant, the update will no longer impact your use of Google Search services, as it’s now a separate option.
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The running list: major tech layoffs in 2026 where employers cited AI
Microsoft said Monday that it has eliminated about 4,800 roles, or 2.1% of its global workforce, adding to the string of AI-related layoffs hitting the tech world. The company said the roles being cut are “not being replaced by AI,” but acknowledged that “AI is changing how work gets done” and automating many everyday tasks. The cuts continue what feels to many in the tech industry like an epidemic: companies reporting record revenues while simultaneously culling their workforces, pointing to AI as both the engine of growth and the reason for the cuts. Tech layoffs hit theirhighest single monthin years in May, and AI was the most-cited reason, according to outplacement firm Challenger, Gray & Christmas. Roughtly120,000 tech roleshave now been cut in 2026, according to Layoffs.fyi, a tracker that has monitored industry layoffs since 2020. We recently wrote about why that rationale is something companiesmay want to rethink, not least because for many of these companies, the teams they’re now cutting ballooned during the pandemic hiring surge, raising questions about what’s really going on right now. Below is a running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor. Oracle— June 22, 2026. Oracle disclosed in late June that it had reduced its workforce by 21,000 employees over the past 12 months, a decline of 13%, which means more cuts than was previously known, including because of AI. “The adoption and deployment of AI technologies across our operations have resulted, and may continue to result, in reductions to our workforce,” the company said in anannual financial regulatory filing. GitLab— June 3, 2026. GitLab laid off roughly 350 workers, about14% of its staff, to fund AI infrastructure investment and handle surging traffic from AI workflows. CEO Bill Staples said agentic workloads are “pushing competitors to the brink” and that the company had begun a “generational rebuild” of its core infrastructure to support what he called 100x growth requirements. GitLab is exiting 22 countries, flattening management layers, and partnering with an unspecified AI lab to rebuild its platform for agent-scale workloads. The company reported first-quarter revenue of $264 million, up 23% year-over-year, and expects to incur $30 to $35 million in restructuring costs. Google— ongoing through May. Alphabet’s Google hasquietly cutemployees across its Cloud division, including its Threat Intelligence Group and Mandiant-linked cybersecurity staff, even as Cloud revenue grew 63% to exceed $20 billion for the first time and its backlog nearly doubled to over $460 billion. Over the past year, Google has cut more than a third of the managers overseeing small teams — 35% fewer managers with fewer direct reports. Unlike most companies on this list, Google has never announced a single overall number — the cuts have come through a rolling performance review process, a voluntary buyout program, and structural reorganizations, with outside estimates putting the 2026 total at between 1,500 and 3,000+ engineers. Intuit— May 20, 2026. Intuit announced plans to eliminateroughly 3,000 jobs— about 17% of its total workforce — in a restructuring centered on reducing complexity and reallocating resources toward AI. CEO Sasan Goodarzi reportedly told staff the company is reducing complexity and simplifying the structure so it can deliver better products. Meta— May 20-21, 2026. Meta laid off about 8,000 employees, roughly 10% of its workforce, while moving about 7,000 employees into new AI-focused roles (that theyreportedly hate). CEO Mark Zuckerberg told staff the cuts were necessary because “success isn’t a given” in AI. Cisco— May 14, 2026. Cisco announced it’s cutting nearly4,000 jobs, about 5% of its workforce, despite reporting better-than-expected profit and revenue. CFO Mark Pattersonsaid: “This was really not a savings-driven restructure… this is more [about] realigning … resources around silicon, optics, security and AI.” Cloudflare— May 7-8, 2026. Cloudflare cut about 20% of its workforce (1,100 people), reporting quarterly revenue of $639.8 million, up 34% year-over-year and thehighest single quarterin company history. CEO Matthew Princewrote that“the vast majority of those we laid off last week were measurers” — middle management, finance, legal, internal auditing, and revenue recognition. General Motors— May 12, 2026. GM eliminated 500 to 600 jobs, largely in IT roles in Austin, Texas, and Warren, Michigan, saying it was reevaluating its workforce needs amid uncertain market conditions. A person familiar with the cuts told CNBC thatAI played a role in the decisionbut that it wasn’t the only reason. GM’s statement said it was “transforming its Information Technology organization to better position the company for the future.” Despite the cuts, the company still had roughly 80 open IT positions, including roles in AI, motorsports, and autonomous vehicles. Coinbase— May 5, 2026. The crypto exchange said it was cutting about 700 employees, or 14% of its staff, as part of a restructuring aimed at addressing market volatility and increasing AI efficiency. The company flattened its organizational structure to five layers below the CEO and COO, and said it would experiment with “one-person teams” combining engineering, design, and product roles. CEO Brian Armstrong wrote that AI had changed the pace of work dramatically — “engineers useAI to ship in days what used to take a team weeks” — and that the company needed to “leverage AI across every facet of our jobs.” PayPal— May 5, 2026. PayPal announced plans to cut around 20% of its workforce over the next two to three years — north of 4,500 jobs — as part of a turnaround strategy centered on AI adoption and organizational simplification. CEO Enrique Lores told investors the company would “aggressively adopt AI” in its development processes and formed a new “AI transformation and simplification” team reporting directly to him, tasked with redesigning the company’s processes “function by function.” Lores framed the cuts as removing organizational layers, and said AI would extend well beyond coding into customer service, support operations, and risk management.Microsoft— April-May 2026. Microsoft offered buyouts structured as voluntary separations, without disclosing how many employees these would impact. CFO Amy Hood said total headcount declined year-over-year in fiscal Q3, and is expected to keep declining as the company focuses on “building high-performing teams that operate with pace and agility”amid rising AI investment. Snap— April 16, 2026. Snap cut roughly16% of its global workforce— about 1,000 full-time employees — and closed more than 300 open roles, with CEO Evan Spiegel citing AI advancements as a key driver. “Rapid advancements in artificial intelligence enable our teams to reduce repetitive work, increase velocity, and better support our community, partners, and advertisers,” Spiegel wrote in a memo filed with the SEC. The company said it had already seen small squads using AI tools to drive progress across Snapchat+, ad platform performance, and infrastructure efficiency. IBM— rolling through 2026. Between Q4 2025 cuts and April 2026 Red Hat engineering reductions, estimates range from 3,000 to 9,000 U.S. positions eliminated, bringing IBM’s cumulative total since September 2024 above 15,000. Bloomberg reported IBM plans to triple its U.S. entry-level hiring for AI and hybrid-cloud roles, even as roughly 200 HR positions were replaced by AI agents. An IBM spokesperson described the Q4 2025 round as aroutine rebalancingaffecting “a low single-digit percentage” of its global workforce. Atlassian— March 11, 2026. Atlassian cut about1,600 jobs(10% of its workforce) to “rebalance” toward AI and enterprise sales, even as shares rose nearly 2% on the news. CEO Mike Cannon-Brookes said: “Our approach is not ‘AI replaces people.’ But it would be disingenuous to pretend AI doesn’t change the mix of skills we need or the number of roles required in certain areas. It does.”Dell— January 30 (though disclosed in March 2026). Dell’s total workforce fell about10%in fiscal 2026 — roughly11,000 jobs— to about 97,000 employees from 108,000 a year earlier, with $569 million spent on severance. The cuts came as Dell projected its AI-optimized server revenue could double in fiscal 2027. Oracle— March 5-31, 2026. As noted above, Oracle began telling employees it would be cutting thousands of jobsvia terminal emails. The cuts came even as Oracle posted $3.7 billion in quarterly net income, up 27% year-over-year, with remaining performance obligations up 325% to $553 billion — savings redirected toward AI data centers. The cuts that would later total 21,000 over 12 months, as Oracle disclosed in its June 22 annual filing. Block— February 26-27, 2026. Jack Dorsey’s Block cut 4,000 jobs — nearly half its workforce, down to under 6,000 from over 10,000. Dorsey wrote on X: “We’re already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company.” He added: “I think most companies are late. Within the next year, I believe the majority of companies will reach the same conclusion andmake similar structural changes.”Salesforce— February 10, 2026. Salesforce laid off fewer than 1,000 employees across marketing, product management, data analytics, and its Agentforce AI unit. The companytold Fortune, “Because of the benefits and efficiencies of Agentforce, we’ve seen the number of support cases we handle decline and we no longer need to actively backfill support engineer roles.” This followed an earlier cut of about 4,000 customer-support roles, shrinking that team from roughly 9,000 to 5,000, with CEO Marc Benioff saying the company needed “less heads” because AI agents handle the work.Amazon— January 28, 2026. Amazon cut16,000 corporate jobs, following 14,000 cuts in October 2025 — about 9% of its corporate workforce in three months. The company said it was part of “strengthen[ing] our organization by reducing layers, increasing ownership, and removing bureaucracy.” CEO Andy Jassy had said in June 2025 that, “As we roll out more generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs that are being done today… in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
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Station F ramps up as a launchpad for Europe’s hottest AI startups
Station F, a Paris-based startup hubfoundedby French billionaire Xavier Niel, is gearing up for a new edition of itsF/ai accelerator programin a bid to strengthen its positioning as a stepping stone for promising AI startups. Launchedin January of this year, F/ai’s planning to kick-start its second batch this September, aiming to help a handful of AI-focused startups move from early product to real revenue in a matter of weeks. Spanning 538,000 square feet, Station F is often described as a co-working space, but its footprint extends beyond the physical space, its directorRoxanne Varzatold TechCrunch. One example isStation F’s Future 40annual selection, in which the team names the most promising teams among some 1,000 companies it welcomes each year. In 2024, TechCrunch observed thatnearly all of that annual cohortincorporated AI into its core business. Station F today has a front row seat to the rise of AI startups, leveraging its position as acornerstoneof “la French Tech.” The startup hub has also successfully leveraged its position to capture equity stakes in its Future 40 companies. “We have been investing [in these companies]since 2022,” Varza said. Helped both by its size and Niel’s connections, Station F has become a frequent stop for officials seeking to connect with Europe’s tech scene, with no less than 11 presidential visits since President Macron’sinaugural tour in 2017. It has also welcomed AI big nameslike Sam Altman, and is now leveraging these ties for F/ai. The first cohort of F/ai’s program wasbacked by a long list of significant tech companies— AMD, Anthropic, AWS, Clay, Google, G42, Hugging Face, Lovable, Meta, Microsoft, Mistral AI, OpenAI, OVHcloud, Snowflake, and Qualcomm — not to mention several VC funds. The second cohort will add a few more big names, TechCrunch has learned: Eleven Labs, Nebius, Rippling, OpenRouter, HubSpot, and GitHub. “The goal was to bring together all the major players and make it much easier for [AI] startups looking to launch in Europe to connect with them,” Varza said. Two teams from the accelerator’s first batch have already gained international recognition: Alpic, whichwon the global grand finaleofThe Pitch, a competition organized by Deel; and Rippletide, whichwontheOpenAI Codex Hackathon. While awards rarely hurt, especially when they bring funding, F/ai is focused on helping its cohort generate revenue, targeting €1 million (about $1.14 million) within six months. “We’d heard quite a bit of criticism about the slow pace of commercialization of European startups,” Varza said. “This brings them on par with what investors are seeing in the U.S.” Investors seem to like what they’ve seen so far. The first cohort collectively raised $34 million in pre-seed funding, according to Station F. The teams’ track record may have also helped: 80% of these 20 AI startups were founded by repeat entrepreneurs, a third of whom hold PhDs. The founder profile skews that way mostly because F/ai selects its cohort exclusively via recommendations from founders, partners, and investors — a process that could add to the cliquishness and elitism France’s tech scene is at times accused of. But while teams can’t apply directly, they can get in touch with one of F/ai’s many partners, and perhaps soon with alumni, Varza said. She added that Station F has some30 other programsstartups can apply to. Access appears to be a key focus for F/ai, which has in the past hosted the likes of Turing Award winnerYann LeCunfor private chats. “Today, if the founders here want to speak to people at this level, they all seem to think they need to go to the U.S. and join a program there. We actually want to show that you can stay here and do it from here,” Varza said.
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