Últimas Noticias de IA
Dabur Partners with Accenture to Build AI-Powered ‘Digital Brain’ Across Enterprise
Accenture will also support Dabur in redesigning talent strategies, operating models, and governance frameworks.
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Cisco Joins IIT Delhi to Launch Technology Hub for India's AI, Cybersecurity Capabilities
The Cisco Technology Hub aims to boost AI and cybersecurity research, innovation, and talent development in the Indo-Pacific region
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Palantir Reports 93% Revenue Growth, Pushes ‘Benchmarking’ Over AI Leaderboards
Palantir is now focusing on enterprise-specific AI benchmarks, sovereign fine-tuning, and open-weight models instead of frontier benchmark rankings.
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Anthropic Launches In-Country Claude Inference in India With Amazon Bedrock
Anthropic also announced new enterprise partnerships, expanded its Bengaluru team, and unveiled initiatives spanning cybersecurity, research, and Indian language AI.
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OpenAI Calls Apple’s Lawsuit ‘Careless & Personal’
The ChatGPT maker published emails and internal messages, alleging Apple misrepresented key events before suing over former Apple executives now working at OpenAI.
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Yotta Data Services launches ₹10,000 free credits programme for Shakti Studio
Yotta launches a ₹10,000 free credits programme for Shakti Studio, giving developers and enterprises complimentary GPU access to build AI applications.
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Shadow AI: The Silent Risk Stalking India's IT and GCC Corridors
Indian IT and GCC employees are turning to unsanctioned tools faster than governance teams can track them. Industry voices warn that visibility, not adoption, is now the real battle enterprises must win.
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Commerce-Focused Enterprise AI Startup Kily Bags ₹30 Cr Led by Sorin Investments
Razorpay and Wyser Capital also backed Kily, an autonomous AI platform for brands across e-commerce and quick commerce.
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AWS is helping vibe-coding startup Superblocks, and the implications are big
Vibe-coding startupSuperblocksannounced a multiyear joint marketing agreement with Amazon Web Services (AWS) that enables its tool to be embedded within the private clouds of AWS customers. That means an enterprise on AWS that subscribes to Superblocks will be able to offer vibe coding to the company’s business users, and those apps will not send data or information externally to model providers or databases. The apps will spin up Amazon Aurora databases within the company’s private cloud, not, for instance, create externalSupabase databases, the vibe-coding database of choice. The apps will also integrate withAmazon Bedrock, the cloud giant’s AI app development/AI gateway/inference platform. Essentially, these apps will automatically fall under IT’s management and security, rather than be rogue applications. “We’re going to bring it to your data inside your private cloud,” Superblocks co-founder and CEO Brad Menezes tells TechCrunch of vibe coding. “The big thing about that is data never leaves. … It’s their AWS account and basically secure with all of the auditing, all of the encryption, all of the network controls.” AWS will also help sell Superblocks to enterprises as it does for many of its Marketplace partners. “We support partners where we see strong customer demand and alignment with how customers want to build,” an AWS spokesperson tells TechCrunch. Still, AWS does not yet have its own vibe-coding agent aimed at business users. It has Kiro, an AI coding agent aimed at developers. Amazon also has an AI assistant, Quick, for business users. But again, that’s more like a Claude Cowork or Microsoft Copilot, rather than a Lovable or Replit. So this should be a nice boost for early-stage Superblocks, which has 50 employees and raiseda total of $60 million as of its Series A, announced in May 2025, backed by Spark Capital, Kleiner Perkins, Meritech Capital, and Greenoaks. Yet, it’s actually a more significant symbol than that. It’s part of a growing trend where the hyperscaler cloud providers urge their enterprise customers to separate their AI models from all the other scaffolding needed to run enterprise AI and do so on their clouds. They want enterprises to buy AI harnesses (aka agentic apps), AI orchestration, security tools, and the like from them, and not from the frontier providers. In the past few weeks, Microsoft CEO Satya Nadella has been banging the drum with exactly that message. He’s been telling his many enterprise customers touse multiple models to reduce costs and avoid lock-in. He’s also been preaching that theAI labs are not trustworthy enoughto turn to for agent orchestration or app-level harnesses because they may use that data to study a business andlater competewith it. Enterprises perhaps don’t need such warnings. They have already decided to adopt multiple models, particularly frontier Chinese open-weight options. “That is flipped because 60 days ago they were like, I want a specific model. It’s called Anthropic,” Menezes adds. Open models, for instance, accounted for 29% of all traffic routedthrough Vercel’s AI gatewaylast month, a popular tool among enterprises to manage multi-model AI use. Then, by necessity, all of their AI scaffolding can’t be tied to one provider. “Having a multi-model strategy across big frontier labs, OpenAI, Anthropic, and open source — and I’d say Chinese open source right now, but also U.S. open source is now starting to come up. It’s a must-have for the CIO,” he says. They want model choice for coding as well as customer service, HR, [and] sales automation, he adds. Menezes says the movement is so strong, he predicts that “any enterprise that is betting on a single model provider, that executive will be fired.” So now we’re seeing the cloud providers bring vibe coding for business users into private, secure clouds, too. That’s like a potential second wave after bringing AI coding agents for enterprise developers. “It’s an emerging category with real momentum, and exactly the kind of innovation we support,” AWS tells TechCrunch.
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After killer quarter, Palantir CEO Alex Karp calls AI industry ‘Marxist’
Palantir CEO Alex Karp on Monday once again warned that AI frontier labs are too untrustworthy for enterprises. The CEO, who famously studied philosophy and earned a PhD in social theory, implied in Palantir’s quarterly shareholder letter that these were the kinds of capitalists who gave rise to Marxist socialism. “There are Marxist overtones and undertones to our business,” he wrote in a letter toshareholders about Palantir’s outstanding quarter. “Others, including many of those building large language models, intend, knowingly or otherwise, to capture the means of production of their purported partners.” To be clear, AI labs have hardly cornered Palantir out of the market. Quite the opposite. The skyrocketing use of AI helped Palantir achieve record-breaking results. For its second quarter, the companyreported$1.9 billion in revenue, up 93% over the year-ago quarter, and $1.1 billion in profit, “more profit in a single quarter than we did in total revenue in the same period the year before,” he wrote. During the quarterly conference call with Wall Street analysts, he explained his analogy further, relying heavily on a sort of “tech bro patriot” jargon common among defense tech companies. (Palantir’s senior leadership is entirely male.) He asked on the call, if companies are going “to buy into a future” where your job helps your “adversaries win, and everybody who does win is a small, tiny group of people living in a tiny place that somehow believe because they eat vegetables and they don’t support war fighters that they deserve to have the total means of production of this country? And the rest of us should just sit by it back and absorb the cost of that revolution, which we’re paying for.” Palantir, in contrast, serves model-agnostic AI and analysis software to governments and enterprises, and allows organizations to control their data as well as their AI “exhaust,” aka, their prompts, orchestration, context. “How are we paying for it? In the enterprise context, people sign up for token self pleasurings… at real cost like other forms of self pleasure,” he said. “You are paying for the right for them to migrate your IP, your know-how, your expertise to their model, so that they can build a competitive business that doesn’t require your business or people. And why are they doing it? It’s actually being done for what they believe are moral reasons. They are superior to you. They deserve to colonize your enterprise.” Jarring language aside, he is making an underlying point that is increasingly being repeated elsewhere, including from the likes ofMicrosoft CEO Satya Nadella. This theory points to thesignificant list of companiesthat partnered or paid for Anthropic and OpenAI while the AI labs launched similar businesses ranging from design tools to, healthcare operations, legal, even drug discovery. The truth is, none of these companies are economic villains or heroes — anymore than other for-profit companies are. AI is growing so quickly, the market changing so rapidly, there is clearly room for all, Palantir’s results show.
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Congress’s favorite AI tool? ChatGPT
OpenAI’s ChatGPT is Congress’s AI tool of choice so far in terms of money spent, according to areport from CNBC. OpenAI received roughly 90% of all spending on AI tools by House offices, committees and institutional accounts during the year ending in March 31, per House disbursement records. CNBC found that Congress spent around $100,580 across 798 transactions on ChatGPT, out of at least $113,740 in total AI spending. Anthropic’s Claude trailed in second place at $13,160 across 37 transactions. Democratic offices accounted for $54,165 in AI purchases, three times the $15,782 spent by Republican offices. The insights exclude any Congressional AI adoption from free accounts or AI bundled into broader software contracts. Congressional staffers are using ChatGPT and other tools to write memos, summarize and analyze legislation, respond to constituents, prepare hearing materials, sort through policy research, and even draft social media posts.
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Apple finally fixed Siri. So why does it feel anticlimactic?
Afterroundsofdelays,Siri AI arrivedin the consumer beta build of iOS 27,launchedin July. The AI assistant now does what Apple promised: it understands your personal context, taps into broad world knowledge to answer your questions, and surfaces relevant information stored on your iPhone. And yet, the arrival feels somewhat anticlimatic. Apple finally has a functional — actually, a fairly impressive — AI assistant, but it’s arrived past the time where such a launch feels novel and exciting. If anything, the AI race has surged ahead in the months and years Apple hasdawdledon AI. Today, AI tools are coding and building software, AI agents are completing multi-step tasks, and AI is working alongside you, using your computer, reasoning, thinking, remembering, creating media, and more. Being a functional chatbot or AI helper isn’t the breakthrough that it once would have been. That is not to sayApple’s Siri AIisn’t valuable or useful. With Siri AI’s launch, Apple delivered on its promises and then some. You can now have natural, back-and-forth conversations with Siri, which has settings that let you tweak the expressivity and pacing of its voice responses. You can also type to the assistant, if you choose, or use it via a dedicated app for the first time, referencing past conversations. The assistant can understand your personal context, helping you find things like photos, emails, contacts, texts, or calendar appointments — even when you’re not quite sure what you’re looking for or where. For instance, you could ask it to pull up the last receipt you saved on your iPhone, without saying where it was stored or what the receipt was for, and Siri will find it for you. You can also ask it about things you’ve saved only as a photo, like your Driver’s License number from a pic of your license, or a QR code you screenshotted to reference later, as a reminder to visit someone’s website. You can launch websites and use apps via Siri, doing things like getting directions, playing music, editing a photo, drafting an email, playing your audiobooks, and much more. Thankfully, Siri now consistently and accurately plays the song, podcast, or audiobook you request on your preferred app — a low bar to be sure, but onewhere Siri stumbled before. Siri can brainstorm with you, too. Among other things, it can help you refine ideas, learn about a new topic, or explore a recipe — like suggesting something you can make with your random ingredients in your fridge! You can ask when your favorite band is playing or when a particular event is, and Siri answers correctly, giving you the information you need, based on your location. You can use Siri in the Camera’s viewfinder to learn about things in the real world or to help you split a restaurant bill with your friends. In short, it’s exactly what you always hoped Siri would be: a useful assistant that lets you use your iPhone easily, just by talking, and one that can answer questions of any sort instead of shuffling you off to the web. Theseimprovementswere made possible byApple’s partnership with Googlefor the use of its Gemini AI models. Apple didn’t just slap its name on Gemini AI; it used Google’s technology to train and refine its own proprietary Apple Foundation Models. The result is AI models designed to run on Apple’s own Silicon and on its Private Cloud Compute infrastructure and actually work. Yet, despite finally delivering a functional, helpful version of Siri, it feels almost like Apple fixed a longstanding bug — a forever-broken Siri — rather than doing something revolutionary here. This is how Siri was meant to work all along. The only marvel is that, after so many years of failing to perform tasks correctly, it actually works. The general public who don’t run beta builds on their devices will gain access to the new Siri when Apple officially releases iOS 27, expected in September.
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