Latest AI News
Indian Enterprises Now Fear AI Vendor Lock-In Thanks to US Govt
As AI providers shift to usage-based pricing and governments restrict access to frontier models, Indian enterprises are rethinking their AI architecture.
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China to Let Top AI Firms Buy Limited NVIDIA H200 Chips
Beijing is expected to cap purchases at under 2,00,000 chips while restricting their use to training AI models on public data.
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Microsoft’s New TypeScript 7 Promises 8–12x Faster Builds With Native Go Compiler
Microsoft says the new language server cuts the number of failed commands by over 80% and server crashes by more than 60% compared with TypeScript 6.
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Why Aurigo is Betting on AI, Talent & Long-Term Thinking
Aurigo founder Balaji Sreenivasan on building an AI-native company for the full construction lifecycle spanning capital planning, project delivery, and asset management for some of the largest infrastructure programs in North America.
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OpenAI Launches GPT-Live with Real-Time Voice Conversations Powered by GPT-5.5
The model allows users to interrupt the model, pause without being cut off, and have faster back-and-forth conversations.
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Nurix AI Acquires Verloop.io, Expanding AI Agents Across Voice and Chat
Following the acquisition, Verloop.io’s team and operations will be integrated into Nurix AI.
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Semiconductor Fabs to Benefit as Govt Scraps Import Duty on Critical Electronic Components
The waiver of basic customs duty covers essential inputs such as capital goods and equipment for producing lithium-ion cells, including machinery to enhance domestic production.
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Mistral Bets on Physical AI With 8 Bn Parameter Autonomous Robot Navigation Model
French AI startup Mistral expands into robotics with Robostral Navigate, an 8B navigation model that enables autonomous movement using a single camera.
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SpaceXAI Launches Grok 4.5, Narrows Gap with GPT 5.5 and Opus 4.8
SpaceXAI has priced Grok 4.5 at $2 per million input tokens and $6 per million output tokens.
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This startup thinks robotics is about to have its ChatGPT moment
Loading the player… Before OpenAI’s GPT-3 ushered in the era of foundation models, companies built specialized natural language processing models from scratch, training each on large amounts of task-specific data. Today, most organizations start with a general-purpose model like OpenAI’s GPT series, Claude, or Llama and then fine-tune or prompt it to solve their specific needs. Pim de Witte, CEO ofGeneral Intuition, thinks embodied AI will follow a similar pattern. Rather than collecting huge real-world datasets to build specialized robot models, he argues the industry should focus on better quality datasets that can produce foundation models capable of transferring intuition about movement and interaction across many environments. “A lot of companies right now are doing lots of specialized work focused on individual embodiments, individual environments, and individual robots,” de Witte told TechCrunch on arecent episode of Equity. Much of that work will become redundant soon, he argues, with the emergence of general models like the one General Intuition has been developing and deploying. “The generalization of the model itself is the product,” he said. “The fact that it has a base level of reasoning about space and time is going to be the reason why people stop collecting hundreds of thousands or millions of hours of real-world data. Because the reality is, you only need a few minutes.” General Intuition built its own such foundation model after training on millions of hours of video game data, including information like what buttons on a controller a human pushed and when. Both de Witte and General Intuition’s lead investor, Vinod Khosla, argue the action data is the key to developing a human-like intuition for spatial-temporal reasoning. The startup last monthraised $320 million at a $2.3 billionvaluation on the back of that thesis. The company has demonstrated that its current model is capable of both playing a video game for hours and powering a quadrupedal robot — the latter after fine-tuning it on just eight minutes of real-world robotics data. “The fact that [the robot] was actually able to zero-shot on just the front camera, with no other sensors, in the office with dynamic objects being introduced and people walking by was a very big surprise to us,” de Witte says. “I think it’s a sign of what’s to come.” The end game for General Intuition isn’t to build robots itself, but to become the foundation model of physical AI, a base model for other robotics companies to build upon for their own machines. Or, as de Witte put it: “We’re not gonna build a self-driving car company. We’re gonna make it 10 times easier for the next person to build a self-driving car company.”
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SpaceXAI releases Grok 4.5, which Elon describes as an ‘Opus-class model’
SpaceXAI has released its latest model, Grok 4.5 — the first since the company went public several weeks ago. Ina blog postpublished Wednesday, SpaceXAI characterized its new release as a workhorse that can tackle all of the typical tasks that the AI industry has sought to automate: coding and app-building, office and clerical work, research, writing, and other forms of routine knowledge work. Grok can supposedly do all this for less spend, too, as SpaceXAI says that its model has “twice greater token efficiency” than other leading models. If it carries through to real-world use cases, that efficiency would be a big advantage for SpaceXAI, since the cost of tokens has been a growing concern for AI consumers. The company released benchmark metrics Wednesday that appeared to show Grok’s competitiveness with other top models from SpaceXAI competitors, although just short of best-in-class: Ina poston his social media platform X (which is a subsidiary of SpaceXAI), founder Elon Musk compared the model to Opus, Anthropic’s LLM designed for intensive and complex tasks. “Based on strong positive feedback from customers in our beta test program, @SpaceXAI will make Grok 4.5 available to the public tomorrow. It is an Opus-class model, but faster, more token-efficient and lower cost,” wrote Musk in his post on X. Musk later added: “Our internal assessment is that Grok 4.5 is roughly comparable to Opus 4.7, but much faster. The combination of capability, faster speed and lower cost is what makes it competitive.” SpaceXAI says that its new model costs $2 per million input tokens and $6 per million output tokens. That’s quite competitive, if Grok’s capabilities match SpaceXAI’s rhetoric. Opus 4.7, by comparison, costs $5 per million input tokens and $25 per million output tokens. OpenAIhas tiered costsfor different model versions: Sol, its most expensive, costs $5 for 1 million input tokens and $30 for 1 million output tokens, while its least expensive, Luna, costs $1 for 1 million input and $6 for 1 million output tokens. It’s a big week for AI model releases. OpenAI isplanning to releaseGPT 5.6, its latest, most powerful model, on Thursday. The release of that model had previously been limited by the Trump administration, due to concerns about its security implications. OpenAIhas called itits “strongest model yet.”
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Google’s deepfake detector system used to debunk McConnell hoax pic
Google’sSynthIDsystem has been used to debunk a high-profile AI-generated hoax image, in a rare but significant win for the system. Earlier this week, a picture circulated online that seemed to show Kentucky Senator Mitch McConnell covered in tubes in a hospital bed in a state of extreme distress. The image was shared widely onRedditandX, but by Wednesday, the revered fact-checking siteSnopeshad debunked the image, noting that, when checked, the image registers as containing the SynthID watermark designed by Google to identify AI-generated pictures. In short, the watermark worked exactly as it was supposed to in a win for anti-deepfake technology. Senator McConnell’s health has been the subject of intense speculation since he checked into the hospitalafter an emergency call on June 14. Since that time, he’s been largely absent from the public eye, fueling speculation that his health may be failing. In this case, however, the evidence proved to be entirely fake. Launchedat Google’s I/O developer conference in 2025, SynthID works as an invisible signature, visible to SynthID algorithms but designed to be unnoticeable to the casual observer. Because the signature is built into the image itself, it survives even when an image is screencaptured across multiple platforms, as the McConnell image was. SynthID’s main limitation is that it can only be used when an image-generation tool actively participates in the program. Gemini models have included the watermark since the program launched in 2025. OpenAI joined in May 2026, as part ofa broader effort to fight malicious image generation. Anthropic does not participate in the program. Users can check if images contain the watermark by asking a Gemini model or uploading them toOpenAI’s public image verification tool.
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