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Latest AI News
ITC Infotech-Happiest Minds Merger Is a Warning Shot for India's Mid-Tier IT
The ₹7,000-crore merger creates scale. But its bigger significance lies in what it says about the pressure building on India’s mid-sized IT services firms.
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Genesys Launches New Innovations To Automate End-To-End Customer Service
Snippet: The platform retains information across interactions, determines its actions and coordinates work between AI and human employees while operating within predefined business rules.
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MongoDB Appoints Richard Scott as SVP for Asia Pacific & Japan
Scott, who brings more than 25 years of experience across the technology sector, joins MongoDB after holding senior roles at Salesforce, Microsoft and SAP.
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IIT Madras-Backed Bodhan AI, AI4Bharat Launch 4 AI Models for Students & Teachers
The models will be offered as Digital Public Goods, with open weights and sovereign APIs that let developers build applications without training language models from scratch.
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OpenAI GPT-6 Astra Launched With Critical-Level Cybersecurity Capabilities as Part of AGI Push
OpenAI has released GPT-6 Astra, calling it the most capable flagship AI model yet. Its deployment is part of the San Francisco-based company's plans to eventually reach AGI (artificial general intelligence), a stage where a computer system can learn, reason, and perform any intellectual or cognitive task that a human can. GPT-6 Astra is designed for reasoning, coding, research and agentic workflows. It comes with a 1.05-million-token context window and supports up to 128,000 output tokens through the API.
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Crusoe reportedly raises $3B at a $30B valuation
Data center developer Crusoe, which counts Meta, Microsoft, and OpenAI as its customers, has raised a new $3 billion round at a $30 billion valuation,Bloomberg reported. The deal is being co-led by Atreides Management and Valor Equity Partners, and includes participation from Mubadala Capital, the asset management subsidiary of Abu Dhabi’s sovereign wealth fund Mubadala. The company recently signed amassive $13 billion, five-year cloud contract to supply quantitative trading firm Jane Street with GPUs and AI infrastructure, Bloomberg reported. The fresh fundraise comes 10 months after Crusoe raised a $1.38 billion round at a$10 billion valuationlast October. Launched in 2018 as a crypto mining operation powered by flared natural gas, Crusoe has since pivoted into a major AI infrastructure and cloud provider that is best known for developing hyperscale data center campuses for clients like Oracle and OpenAI. The company recently met with investment bankers, including Goldman Sachs and Morgan Stanley, to discuss a potential near-term IPO,Axios reportedlast month.
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The sameness problem behind those unappetizing AI-generated menus
When it first happens to you, you think you’re crazy. You wander into a cafe and look at a menu with a variety of bagel sandwiches, but each illustration looks eerily flawless, precisely symmetrical, and oddly smooth, eliciting a visceral sensation that something isn’t right. You might think you’re paranoid, but you’re not losing your mind. Generative AI menus have hit the restaurant business courtesy of models courtesy of models trained on a narrow, “pleasing” aesthetic that produces a look that feels wrong even when you can’t articulate why. Sometimes, these illustrations are egregiously fake, like a burrito with cheese so bubbly and melty that it looks more likeavant garde artthan lunch. More often, they’re soordinarylookingthat you only notice something iswrongwhen you take a second to look more closely. “It’s almost like an alien trying to make a pizza without understanding its core principles,” Reality Defender CTO Alex Lisle told TechCrunch. (Reality Defender itself is part of a growing category of startups selling AI-detection and content-verification tools — a business that exists in part because of issues like this one.) Throw a rock in NYC and you’ll hit a mildly off putting AI food advertisement.pic.twitter.com/lLXVkFIFoG Lisle says that the way these models are built can help explain why illustrations seem to embrace such a specific aesthetic — one where every ice cream scoop is perfectly round, and where shrimp seem to have been genetically modified to eat their own tails, creating new “Lovecraftian food horrors.” Large language models (LLMs) and diffusion models — the kinds of AI models that make seemingly omniscient chatbots and image generators like ChatGPT and Midjourney possible — are trained on vast quantities of data. The models then identify patterns in the datasets to predict what a user is looking for when they ask something like, “Make me a menu for a burger restaurant.” “A lot of this stuff looks like a Chili’s menu from 2015, and there’s a reason for that,” Lisle said. “That was the corpus of work from which [the models] drew their function.” New training data is invaluable to the companies building AI models — Amazon has even been found to source rare books to scan and add to its training data, only todestroy those booksonce they’ve been uploaded. It’s inevitable that some AI-generated content will seep into these incomprehensibly large data sets. But when AI models train on too much of their own AI-generated content, they riskmodel collapse. “Model collapse is almost like a mad cow disease… when you feed the outputs from one model back into itself, eventually the inbreeding becomes too much, and the whole thing collapses,” Lisle explained. “What we see here is convergence, which isn’t necessarily model collapse.” Convergence is a bit less extreme, degrading the quality of an AI’s outputs without making it entirely useless. If someone asks an AI model to generate a menu for a fast food restaurant, the model will likely reference menus from Wendy’s, Burger King, McDonald’s, or another popular chain. These menus already share a similar style, which means that the AI-generated outputs will mimic that same style, only to further reinforce it further if the AI-generated menu ends up back in training data. But menus and advertisements for food will always look better than the real thing, like a Big Mac in a McDonald’s commercial where each layer of the sandwich is arranged by a prop designer to look maximally appetizing. This effect can become even more pronounced in AI outputs. “The optimization of the data sets is for pleasingness, or you know, not being offensive, and so there’s a way that turns into homogenization,” Lee Rainie, Director of the Imagining the Digital Future Center at Elon University, told TechCrunch. “What AI is known to do both in images and language is to shave off the edges.” On a more localized scale, this smoothing of images seems to happen when you use an AI image generator to create a menu and apply edits to it. On X, a user namedLabtecshowed what happens when you make a menu in ChatGPT, then edit it 100 times to see how the food continues to look less and less like it should. (We replicated the experiment and found similar results.) “The end result actually makes me uncomfortable,” Labtec wrote. I made a restaurant menu in ChatGPT then edited it 100 times to see how those hideous slop menus end up the way they are. The end result actually makes me uncomfortablepic.twitter.com/sDIUKlabdp Restaurants are likely falling victim to this problem, revising their AI-generated menus to alter small details over and over, like prices or item names. It seems that with each edit, the food images become a tiny bit more round and smooth. “People have an almost unexplainable sense about when they’re looking at something that’s AI-generated, compared with something that was real in the first place,” Rainie said. “There’s just a sensibility that people sometimes find hard to articulate, but they kind of know it when they see it and I think that’s one of the reasons why some of the early stories about the backlash [against restaurants using AI menus] is so pronounced.” There’s science behind our aversion to these AI menus. Researchers at the University of Duisburg-Essen in Germanyfound that AI-generated food images exhibited an “uncanny valley” effect, where images of food that looked almost real elicited more disgust and unease than images that were obviously fake. That squeamishness only intensifies in light of the cultural context around AI. If people react to these images so negatively, then that’s probably reason enough for restaurants to stop trying to make AI menus work. But the issues that bring us perfectly browned hamburger buns extend beyond the dinner table. “Seeing and hearing has always been believing, to the point where even our court systems are entirely tuned to the idea that the gold standard in evidence is taped confessions and videotaped evidence,” Lisle said. “That’s no longer the case. The world has fundamentally shifted, for good or for ill.”
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OpenAI Declares ‘AGI Era’ after Launching GPT 6
The company believes that it is the best model in the world for professional work.
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How to Talk to a Speaker at an AI Conference
The four minutes after a talk ends are the most valuable and least used minutes of any conference. Here is how to use them without being the person everyone edges away from.
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Adobe Names Anil Chakravarthy as CEO, Shantanu Narayen to Become Executive Chair
The leadership change comes as Adobe expands its focus on agentic software across creativity, productivity and customer experience.
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Last 2 days to apply to host a Side Event at TechCrunch Disrupt 2026
There are just 48 hours left to apply for your Side Event in theTechCrunch Disrupt 2026Side Events lineup. If you’ve been thinking about hosting a meetup, happy hour, cocktail party, workshop, panel, or another gathering during Disrupt week, now is the time to make it happen. Applications to host an official Disrupt Side Event closeSeptember 4 at midnight PT. Apply to host your Side Event before September 4 ends > From October 10–16, San Francisco will be packed with founders, investors, builders, and tech leaders coming together to connect, learn, and get a front-row seat to tomorrow’s innovation. ASide Eventgives you the opportunity to bring your own community into that momentum — and create the kind of conversations that continue long after the conference floor closes. Amplify your brand: Approved Side Events can be featured on the Disrupt Side Events page, agenda, mobile app, newsletters, articles, and social channels. Bring your community into the action: Connect your audience with thousands of Disrupt attendees, potential investors, partners, and fellow innovators. Make your mark on Disrupt week: Host an experience that reflects your brand, community, and vision. Give your network an extra reason to join: Hosts receive a25% discount on Disrupt ticketsto share with their community. And you don’t have to squeeze your time to connect with tech leaders into three short days at the main conference. Side Events can take place throughout the Bay Area onOctober 10–16, giving you more opportunities to find the right time to bring people together. You have 48 hours left to get your event into consideration for the official Disrupt Side Events lineup. Applications closetomorrow, September 4, at midnight PT. Don’t wait until Disrupt week to wish you had hosted something.Bring your people together. Own a moment during Disrupt. Make your event part of the conversation.
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OpenAI launches Astra, its powerful (and controversial) new model
OpenAI released Astra on Thursday, its latest AI model and — according to the company — its most powerful and capable one yet. OpenAI claims that Astra represents “a new frontier on computer and browser use,” and that it handles tasks with unmatched “speed, accuracy, and safety.” The model is being made available Thursday to OpenAI customers that use Daybreak, its cybersecurity program. Over the next week, it will also become available through OpenAI’s paid plans — including Pro, Plus, Enterprise, and Business accounts — as well as through its API. In a call with journalists on Thursday, OpenAI president Greg Brockman said that Astra was the company’s “most intelligent and, also very importantly, our most aligned model yet.” He added that it “brings together years of our research and big bets, with each breakthrough having built on the last” and that it represents a “real shift in what kind of work people can delegate to AI and how it can empower them.” Much has been made about Astra’s cyber capabilities. OpenAIpublished a blogearlier this week in which it discussed the model’s new capabilities, as well as new safeguards that have been instituted to make it a safer experience for users. The company said Thursday that it had tested Astra on a variety of security benchmarks to ensure its capabilities, and that “Its ability to identify and develop zero-day exploits can help defenders find and patch weaknesses.” The company’s focus on alignment — that is, the tendency of a model to do what a user wants or is in their best interests — can’t help but seem like a response to the recent Hugging Face breach, in which an OpenAI agent escaped its sandboxed testing environment and hacked several companies (a very blatant example of misalignment). OpenAI has also boasted about Astra’s coding abilities, claiming that it is the “best model for software engineering to date.” To back up that assertion, the company provides results from a variety of cyber-related benchmarking tests. Those tests seem to show that Astra scores higher than other existing models — including OpenAI’s own Sol and Anthropic’s Fable — when it comes to activities like finding bugs, executing terminal tasks, and answering queries about codebases. Astra is also possibly OpenAI’s most controversial model yet due to its use of a particular reasoning technique known as opaque recurrence. This technique is known to obscure an important model-monitoring process known as chain of thought, which allows researchers to audit how and why an AI model made the decisions that it did. OpenAI has downplayed the degree to which Astra engages in opaque recurrence — and on the call chief scientist Jakub Pachocki seemed to frame a certain amount of opacity as a natural outgrowth of model evolution. He stated that monitoring the reasoning process of a model was a critical form of oversight but that “as model capabilities are increasing, monitorability is getting more challenging.” He later added that one potential reason for this was that “more capable models can perform harder tasks using fewer language tokens” or “no language tokens,” which he said then reduces the ability to monitor those particular tasks. One reporter on the call wanted to know if OpenAI was actually heralding Astra as the official arrival of AGI, or artificial general intelligence — the oft talked about but poorly defined technological juncture at which AI surpasses human capabilities in all (or most) things. Here, Brockman quibbled. “There’s no contractual AGI triggering anymore, so that’s actually not a relevant concept,” he said. Here Brockman was referring to the previously existing stipulation in OpenAI’s contract with Microsoft that said the duo’s partnership would dissolve once AGI had arrived. As Brockman noted, that stipulationno longer exists. Instead, Brockman explained that AGI’s definition had evolved from a contractual obligation to a “mission concept or spiritual concept.” He added: “I do leave it up to the reader to decide for themselves if this qualifies for them. For me personally, I do think we’re there.”
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