Latest AI News
Magnum Opens New R&D Centre in Bengaluru to Accelerate Ice Cream Product Innovation for India
The centre will support innovation across brands, including Kwality Wall's, Cornetto, Magnum, Carte D'Or, Feast, and Twister
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GalaxEye’s Mission Drishti Satellite Hit by Solar Storm After System Validation
GalaxEye says the maiden OptoSAR mission validated key systems and plans to launch two new OptoSAR satellites within the next 24 months.
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Telangana Govt Strengthens Life Sciences Ecosystem With ₹800 Cr Oncology Pharma Facility
The project is expected to generate around 500 direct employment opportunities.
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Samsung Projects 19-Fold Jump in Q2 Profit Amid Strong AI Memory Demand
Despite the strong earnings guidance, Samsung’s stock dropped as much as 7.9% in early trading.
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Cult.Fit Heads to Public Markets With ₹950 Cr Fresh Issue, Investor Exits
The DRHP filing follows reports that Eternal-backed Cult.fit was targeting an IPO fundraise of ₹3,500 crore to ₹4,000 crore at an estimated valuation of around $2 billion.
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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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