Latest AI News
AI May Reset Indian IT’s Pyramid Model, But Not Fresher Hiring
Industry voices repeatedly stress skills evolution, AI literacy and the accelerating pace of learning.
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‘We are Not in the Race to Build Data Centres’: Nikhil Malhotra
The Tech Mahindra CIO spoke to AIM about Project Indus and why the company decided to outsource heavier compute.
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This 23,000-Employee MNC is Betting on Pune Nano GCC for AI Solutions
Orbia’s Pune GCC houses roughly one-third of its global IT talent pool.
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5 days left to lock in the lowest TechCrunch Disrupt 2026 ticket rates
We are officially down to the final 5 days tosave up to $680on yourTechCrunch Disrupt 2026ticket. These lowest rates of the year disappear on February 27 at 11:59 p.m. PT. If you’ve been mapping out your 2026 tech event calendar, this isn’t the moment to wait.Register now to lock in your savings before prices increase. Each year,Disruptbrings together 10,000+ founders, tech leaders, and VCs at San Francisco’s Moscone West. From October 13–15, you’ll gain valuable takeaways and curated networking opportunities designed to elevate your startup trajectory, accelerate your career, or strengthen your portfolio. Last year, Disrupt featured 200+ onstage conversations with 250+ top voices shaping the tech ecosystem. Expect the same level of powerful, candid conversations this year. Highlights from 2025 include the following: Keep an eye on theevent pageas we roll out the 2026 agenda. Last year, more than 20,000 curated meetings took place across three days. This year, we’re rolling out improved networking technology to make those connections even more targeted and efficient. Meet the one person who can change the trajectory of your startup. It only takes one. You get: Startup Battlefieldis where 200 TechCrunch-selected, pre-Series A startups compete for $100,000 in equity-free funding, global visibility, and direct access to the industry’s top investors. This iconic pitch competition has helped launch breakout companies like Discord, Cloudflare, and Trello. Over 300 startup exhibitorswill showcase innovations across the venue, especially in the Expo Hall, where foot traffic converges. Discover tomorrow’s breakthroughs and today’s solutions — all in one place. Throughout Disrupt Week, October 11–17, TechCrunch Disrupt Side Events will take place across the Bay Area beyond the main venue. Attend a post-event cocktail hour, grab breakfast before the day begins, or even host your own off-site panel. The opportunities to make powerful connections around Disrupt are endless. Five days remain to lock in the lowest rate of the year. Prices increase after February 27 at 11:59 p.m. PT.Register nowand secure your savings of up to $680 before they’re gone. Save up to 30% ongroup passes.
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Spotify rolls out AI-powered Prompted Playlists to the U.K. and other markets
After initially testing its AI-powered “Prompted Playlists” feature inNew Zealandand recently launching inthe U.S. and Canada, Spotifyannouncedon Monday that it’s rolling out the tool to Premium subscribers in the U.K., Ireland, Australia, and Sweden. Prompted Playlists allows users to create custom playlists by simply describing what they want to listen to in their own words. Instead of searching for individual songs or artists, users can describe the vibe, scenario, or inspiration they want, and Spotify will take care of the rest. To access the feature, users tap “Create” and then select “Prompted Playlist,” then enter any prompt in English. The feature is designed to interpret themes including moods, aesthetics, and even memories. Prompts can be as broad or specific as the user wants, referencing musical eras, genres, activities, lyrics, instruments, or even requesting a playlist inspired by a TV show, movie, or personal milestone. Users can also specify whether they want the playlist to include mostly new music or just music from their library in the prompt. Once a prompt is submitted, Spotify’s AI generates a customized playlist tailored to the request. The system draws on the user’s listening history and incorporates current music and cultural trends. Plus, each song comes with a short explanation that offers insight into why it was chosen for that particular playlist. Users can refine their playlists by adjusting their prompts or starting over. For those whose musical tastes constantly evolve, playlists can be scheduled to automatically refresh on a daily or weekly basis. Since this is still in beta, Spotify noted that there might be changes as the company gets feedback, and that there are currently usage limits in place. Some users havereportedhitting limits after roughly 20 or 30 prompts. Spotify has recently expanded AI features throughout its platform, includingPage Match, which lets users scan a physical book page to jump to the corresponding spot in the audiobook, andAbout This Song. The platform alsoupdated its song lyrics featureto provide global translations and offline access. Last week,SeatGeek partnered with Spotifyto help listeners easily find ticket links for concerts on an artist’s page or upcoming tour dates within the app. Internally, the company has implemented AI throughout its workflows, with co-CEO Gustav Söderström saying earlier this month that Spotify’s best developershaven’t written a line of codesince December, thanks to AI. Spotify is alsoexpanding its audiobook businessby venturing into physical book sales. Soon, users in the U.S. and U.K. will be able to buy physical copies directly from the app.
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Particle’s AI news app listens to podcasts for interesting clips so you you don’t have to
An AI news app calledParticle, fromformer Twitter engineers, can now keep up with news breaking on podcasts as well as news published on the web. Just ahead of its recent Android release, Particle has introduced a feature called Podcast Clips, which finds the most interesting and relevant moments across many different types of podcasts, and then includes those clips alongside the related news stories in its feed. So instead of listening to a lengthy podcast just to catch the 45 seconds of interesting comments, you can play back the clip as you’re reading the news on Particle. You also have the option of reading the transcript of the clip instead, as the words are highlighted as they’re spoken. “We’ve done that basically for any news story — if there is a podcast that is talking about it, or relevant at all, we’ve got all those clips,” Particle CEOSara Beykpour, previously the Senior Director of Product Management at Twitter, told TechCrunch. “It’s a really cool way, when you’re reading a story or learning about a story, to get a breath of what are people saying about this? What’s the commentary?” The addition acknowledges a shift in the news ecosystem that’s been underway for years. Not only are more peoplegetting their news from podcastsand trusting them as reliable sources, but the medium is alsobecoming a destinationfor breaking news and major announcements from public figures. Tech CEOs, in particular, are now seeking out friendly podcast hosts to air their talking points instead of trying to work with traditional media, asBloomberg reportedin 2024. That makes paying attention to podcasts even more critical if you want to keep up with news. Beykpour says Particle usesembedding modelsto understand when podcasts relate to a given news story. These models are provided by the same companies that provide LLM models, but they’re not generative AI technologies, she explains. “We use vector embeddings to understand that these different parts of the podcasts are related to these different stories,” Beykpour notes. “A single podcast might cover 10 or 20 stories, so we use AI to understand that. We also use AI to do some of the logic around clipping, and understanding when to start a clip and end a clip.” The company leverages technology from ElevenLabs for transcription. However, some of the technology that identifies where exactly to clip the audio is part of Particle’s secret sauce. The idea to tap into podcasts to better understand the commentary around news is also something newsrooms are taking a closer look at these days. AsNieman Lab reportedthis month, The New York Times has been using a custom AI tool that employs LLMs to transcribe and summarize new episodes of dozens of right-wing and more conservative podcasts to better understand what influencers on that side are saying about the news. Particle’s Podcasts Clips feature isn’t only tied to news stories. Because the app already understands different entities — like people, places or things — you can go to the page for a notable figure, such as OpenAI CEO Sam Altman, to see all of his appearances on podcasts arranged as a feed. Particle has been busy building other features, as well. The company has made its first attempt at monetization with Particle+, an optional $2.99/month subscription (or $29.99/year) that lets you access premium features. These include the ability to: use natural language to have the news summarized in a style you prefer; pick from different voices when using the personalized audio feed; “Listen to the News”; unlimited crossword puzzles; support for private questions with its AI chatbot, and more. The Android release also brings a couple of other notable changes. The browse tab now includes timely stories, like the 2026 Winter Olympics, in addition to typical sections like politics, tech, or entertainment. Plus, when you tap on an entity, you’ll see a new page with the definition, stories, articles, related entities, and related topics. Particle isn’t sharing data about user activity or conversion rates, but Beykpour did point to the app’s international audience, pre-Android. On a weekly basis, 55% of Particle’s users are outside the U.S., with India (15%) its biggest market after the U.S.
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Guide Labs debuts a new kind of interpretable LLM
The challenge of wrangling a deep learning model is often understanding why it does what it does: Whether it’s xAI’s repeated struggle sessions to fine-tune Grok’s odd politics, ChatGPT’s struggles with sycophancy, or run-of-the-mill hallucinations, plumbing through a neural network with billions of parameters isn’t easy. Guide Labs, a San Francisco start-up founded by CEO Julius Adebayo and chief science officer Aya Abdelsalam Ismail, is offering an answer to that problem today. On Monday, the company open-sourced an 8 billion parameter LLM,Steerling-8B, trained with a new architecture designed to make its actions easily interpretable: Every token produced by the model can be traced back to its origins in the LLM’s training data. That can as a simple as determining the reference materials for facts cited by the model, or as complex as understanding the model’s understanding of humor or gender. “If I have a trillion ways to encode gender, and I encode it in 1 billion of the 1 trillion things that I have, you have to make sure you find all those 1 billion things that I’ve encoded, and then you have to be able to reliably turn that on, turn them off,” Adebayo told TechCrunch. “You can do it with current models, but it’s very fragile … It’s sort of one of the holy grail questions.” Adebayo began this work while earning his PhD at MIT, co-authoring a widely cited2018 paperthat showed existing methods of understanding deep learning models were not reliable. That work ultimately led to the creation of a new way of building LLMs: Developers insert a concept layer in the model that buckets data into traceable categories. This requires more up front data annotation, but by using other AI models to help, they were able to train this model as their largest proof of concept yet. “The kind of interpretability people do is…neuroscience on a model, and we flip that,” Adebayo said. “What we do is actually engineer the model from the ground up so that you don’t need to do neuroscience.” One concern with this approach is that it might eliminate some of the emergent behaviors that make LLMs so intriguing: Their ability to generalize in new ways about things they haven’t been trained on yet. Adebayo says that still happens in his company’s model: His team tracks what they call “discovered concepts” that the model discovered on its own, like quantum computing. Adebayo argues this interpretable architecture will be something everyone needs. For consumer-facing LLMs, these techniques should allow model builders to do things like block the use of copyrighted materials, or better control outputs around subjects like violence or drug abuse. Regulated industries will require more controllable LLMs, for example in finance, where a model evaluating loan applicants needs to consider things like financial records but not race. There’s also a need for interpretability in scientific work, another area where Guide Labs has developed technology. Protein folding has been a big success for deep learning models, but scientists need more insight into why their software figured out promising combinations. “This model demonstrates is that training interpretable models is no longer a sort of science; it’s now an engineering problem,” Adebayo said. “We figured out the science and we can scale them, and there is no reason why this kind of model wouldn’t match the performance of the frontier level models,” which have many more parameters. Guide Labs says that Steerling-8B can achieved 90% of the capability of existing models, but uses less training data, thanks to its novel architecture. The next step for the company, which emerged from Y Combinator and raised a $9 million seed round from Initialized Capital in November 2024, is to build a larger model and begin offering API and agentic access to users. “The way we’re current training models is super primitive, and so democratizing inherent interpretability is actually going to be a long term good thing for our role within the human race,” Adebayo told TechCrunch. “As we’re going after these models that are going to be super intelligent, you don’t want something to be making decisions on your behalf that’s sort of mysterious to you.”
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OpenAI calls in the consultants for its enterprise push
OpenAI is beefing up partnerships with four major consulting giants as the AI company looks to grow its enterprise business in 2026. OpenAI announced on Monday the“Frontier Alliance,”a signal that the AI lab is willing to try different approaches to get enterprises to meaningfully adopt its technology. The alliance includes multi-year partnerships between OpenAI and four major consulting firms, Boston Consulting Group (BCG), McKinsey, Accenture and Capgemini, to sell its enterprise products. OpenAI’s Forward Deployed Engineering team will work with the consulting giants to help them implement OpenAI’s enterprise-focused technologies like OpenAI Frontier into customers’ tech stacks. The companylaunched OpenAI Frontier in early February. The no-code open software allows users to build, deploy, and manage AI agents both built on OpenAI’s AI models and beyond. OpenAI argues in its latest announcement that consultants are the right avenue to get enterprises on board. “AI alone does not drive transformation. It must be linked to strategy, built into redesigned processes, and adopted at scale with aligned incentives and culture to deliver sustained outcomes,” BCG CEO Christoph Schweizer said in OpenAI’s blog post. “Our expanded partnership combines OpenAI’s Frontier platform with BCG’s deep industry, functional, and tech expertise and BCG X’s build-and-scale capabilities to drive measurable impact with safeguards from day one.” Thus far,enterprise adoption of AI has been relatively slowas these companies struggle to find a meaningful return on investment from their AI pursuits. OpenAI’s alliance strategy makes sense and goes beyond just pitching enterprises on attaching AI to their existing workflows. Instead, this effort focuses on consultants persuading companies to change their strategies and workflows to fold in OpenAI’s tools where it makes sense. It’s worth noting the OpenAI rival Anthropic has inked deals with consulting giants includingDeloitteandAccenturein recent months too. Company CFO Sarah Friar wrote in a blog post in January that enterprise is abig area of focus for OpenAIin 2026. OpenAI has also inked sizable enterprise AI deals withSnowflakeandServiceNowso far this year, in addition to naming Barret Zoph to lead the company’s enterprise sales effort in January.
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Samsung Galaxy S26 Series to Support 'Hey Plex' Hotword for Perplexity Voice Assistant
Samsung on Monday announced that the upcoming Galaxy S26 series of smartphones, which is expected to comprise the standard Galaxy S26, Galaxy S26+, and the Galaxy S26 Ultra, will offer support for another AI agent. An addition to Galaxy AI, the Samsung Galaxy S26 series will also support Perplexity AI, according to the company. Users will be able to invoke the AI assistant using the 'Hey Plex' hotword, or by pressing the side button. It will also work across the company's built-in apps as well as some third-party apps.
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Honor Teases Humanoid Robot, Schedules Showcase a Day Ahead of MWC 2026
The Mobile World Congress (MWC 2026) is scheduled to begin on March 2 and will go on until March 5. During the four-day event, various smartphone makers and tech firms will showcase their new products and innovations. Ahead of MWC 2026, various Chinese companies, including Xiaomi and Honor, will also globally unveil new devices. Recently, Honor confirmed that its Magic V6 foldable and the Robot Phone with a pop-out camera will be globally launched a day before the event starts. Now, the Chinese smartphone maker has confirmed that the handsets will be accompanied by a humanoid robot.
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Defense Secretary summons Anthropic’s Amodei over military use of Claude
Defense Secretary Pete Hegseth is calling in Anthropic CEO Dario Amodei to the Pentagon on Tuesday morning to discuss the military use of Claude, according to reporting fromAxios. The meeting comes as the Pentagon threatens to declare Anthropic a “supply chain risk” — a label typically reserved for foreign adversaries — after the AI firm refused to allow the Department of Defense to use its tech for the mass surveillance of Americans and the development of weapons that fire without human involvement. Anthropic signed a $200 million contract with DOD last summer, and Claude wasreportedlyused during the January 3 special operations raid that resulted in the capture of Venezuelan president Nicolás Maduro, an episode that brought the two sides’ tensions into the open. A source told Axios that Hegseth is giving Amodei an ultimatum: play ball or be banished. It’s unclear whether he’s bluffing — replacing Anthropic would be a significant undertaking. But the stakes are real: a supply chain risk designation would void Anthropic’s contract and force other Pentagon partners to drop Claude entirely.
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How AI agents could destroy the economy
On Sunday, an analyst group called Citrini Research publisheda remarkable pieceillustrating how agentic AI could bring on mass economic destruction over the next two years. The scenario imagines a report from two years in the future, in which unemployment has doubled, and the total value of the stock market has fallen by more than a third. As the report puts it: AI capabilities improved, companies needed fewer workers, white collar layoffs increased, displaced workers spent less, margin pressure pushed firms to invest more in AI, AI capabilities improved… It was a negative feedback loop with no natural brake…The system turned out to be one long daisy chain of correlated bets on white-collar productivity growth. It’s a new kind of bear case, focused not on Skynet-style misalignment but on the gradual unspooling of the economy itself. In particular, the Citrini scenario looks at the implications of integrating AI agents into the economy at large, and what it would mean when outside contractors get replaced by cheaper in-house AI. It’s similar to theDeath of SaaSscenario, but Citrini goes further, implicating any business model that involves optimizing transactions between companies. As you might expect, the report is causingquiteastironline. Not everyone is buying it — even Citrini describes it as more of a scenario than a prediction — but it’s not so easy to name the specific point where you think the scenario goes wrong. Personally, I’m not sure companies are ready to hand off purchasing decisions to AI agents, no matter how smart they are. But in Citrini’s scenario, most of the impacted decisions have already been handed off to third-party contractors, so it’s not quite as implausible as it seems.
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