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AI NewsMeta Launches Muse Spark 1.1 Challenges GPT-5.5 & Opus 4.8
12:33 PM IST · July 10, 2026
Meta also introduced the Meta Model API in public preview, allowing developers to build applications using Muse Spark models for the first time.
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Applefiled a trade secrets lawsuit against OpenAIlast Friday, and it’s not messing around. The complaint alleges a pattern of misconduct reaching all the way up to OpenAI’s chief hardware officer and claims more than 400 former Apple employees now work at the company.OpenAI’s response so farhas been carefully hedged, and the timing couldn’t be worse with the company reportedly eyeing an IPO as early as later this year. On this episode of TechCrunch’sEquitypodcast, hosts Kirsten Korosec, Anthony Ha, and Sean O’Kane dig into what the lawsuit could mean for OpenAI’s own hardware ambitions and IPO timeline, plus a bigger theme running through the week’s news: how much should anyone trust AI companies with their data? Listen to the full episode to hear more about: Subscribe to Equity onYouTube,Apple Podcasts,Overcast,Spotifyand all the casts. You also can follow Equity onXandThreads, at @EquityPod.
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Patreon, the membership platform for creators, is cracking down on AI scraping its content for training purposes. On Thursday, the company shared that it’s working with internet infrastructure provider Cloudflare to directly block access to AI bots designed to train their AI models on creators’ work without permission. The strengthened measures were necessary because AI scraping has become more sophisticated since it first put measures in place to deter AI crawlers in 2023, the company says. In addition, Patreon’s paywall has long locked much of creators’ content out of reach of crawlers. But more recently, the company introduced new discovery tools like a redesigned Home Feed and itstweet-like Quips, which could expose more content to crawlers. The changes come about as more online publishers and content creators are coming to grips with how AI is ingesting their work for the purpose of making their AI models smarter. To combat this, Cloudflare now offers tools that allow website publishersto restrict AI bots, including amarketplace that lets websites charge AI bots for scraping, dubbed Pay Per Crawl. Earlier this month,it changed its policiesso that “mixed-use” crawlers, meaning those that both index and train on a website’s content, are blocked by default on any pages that host ads. Patreon says that it’s extending its existing work with Cloudflare to use the company’s AI Crawl Control technology to update its AI policies and enforcement tools. The difference here is that instead of simply asking AI crawlers not to scrape content using the robots.txt files — a standard way to provide bots with instructions on how they can use its site — Patreon is now actively blocking AI training bots. “Consent shouldn’t depend on whether a scraper chooses to behave,” aPatreon blog postexplains, referencing the stricter measures. When testing the features, individual AI training crawlers’ weekly attempts to access Patreon went from “thousands of attempts to zero,” the post noted. That indicates that the AI scrapers were ignoring Patreon’s robots.txt file and scraping the site anyway, despite its requests. However, the company said that it will allow bots that index pages and organize information that can be used to send users back to Patreon. “As AI agents become increasingly powerful and popular, creators deserve a meaningful say in how their work is used by AI companies,” remarked Patreon’s product chief Drew Rowny in the announcement. “On most of the Internet, creators have to accept AI training on their work just to reach and grow an audience. Patreon has a different vision: creators should be able to grow their audience and control how their work is used.”
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Loading the player… Applefiled a trade secrets lawsuit against OpenAIlast Friday, and it’s not messing around. The complaint alleges a pattern of misconduct reaching all the way up to OpenAI’s chief hardware officer and claims more than 400 former Apple employees now work at the company.OpenAI’s response so farhas been carefully hedged, and the timing couldn’t be worse with the company reportedly eyeing an IPO as early as later this year. On this episode of TechCrunch’sEquitypodcast, hosts Kirsten Korosec, Anthony Ha, and Sean O’Kane dig into what the lawsuit could mean for OpenAI’s own hardware ambitions and IPO timeline, plus a bigger theme running through the week’s news: how much should anyone trust AI companies with their data? Subscribe to Equity onYouTube,Apple Podcasts,Overcast,Spotifyand all the casts. You also can follow Equity onXandThreads, at @EquityPod.
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General Compute, an AI inference cloud startup, has landed a $400 million loan from Upper90, a tech investment firm. It might be the first deal to put up inference-specific chips as collateral — chips built to run already trained AI models quickly and efficiently, rather than the more expensive chips used to build the models in the first place. The financing is the latest signal that markets are responding to concerns over the price of AI tools and tokens by turning to infrastructure that runs open source models more cheaply than the newest LLMs from frontier labs. Founded by CEO Finn Puklowski and CTO Jason Goodison, General Computeraised a $15 millionseed round in May to build an inference neocloud around silicon from SambaNova, an Intel-backed chipmaker. (Neoclouds are purpose-built for AI workloads, unlike the general-purpose infrastructure offered by traditional hyperscalers like AWS or Azure.) The company’s SN50 chips are designed for inference. They’re power-efficient and don’t require expensive water-cooling systems, which means they can be deployed more quickly than GPUs across a larger variety of data centers. General Compute says the new chips will provide 16 times faster inference than GPU-based clouds. The challenge is getting a lot of these chips, especially when you’re a brand-new company. Upper90 co-founder and CEO Billy Libby, a former Goldman Sachs quantitative trader, had a playbook for this: In 2021, his firm financed GPU purchases by Crusoe, the energy-focused data center startup, which he believes was the first loan against the value of advanced chips. Traditional lenders eschewed such deals at the time because of the risks and uncertainties around GPU depreciation. But as CoreWeave made chips-backed loans into a business model and then the basis of a blockbuster IPO, this kind of financing has become common. “When we financed Nvidia GPUs as the first group to do that, the market was inefficient,” Libby told TechCrunch. “We could really put together something as an early participant, and kind of get compensated for the risk.” Now that GPUs are comparatively well understood andperhaps over-bought, Upper90 is turning to companies like General Compute to ride the next wave of the AI boom. “We think open source models are going to be important, and we went and looked for a player last year that was in inference,” Libby said. “Everyone doesn’t need a supercomputer, but they do need inference and AI.” That thesis has been growing stronger, with companies that provide access to open models, like OpenRouter and Fireworks, raising new rounds at huge valuations. New models likeKimi’s K3have proven to compete with the latest releases from Anthropic and OpenAI on coding benchmarks. And new chipmakers like Groq and Cerebras have drawn interest from acquirers and public markets alike. General Compute’s ability to access chips outside of Nvidia’s ecosystem matters for the same reason. TensorWave, another AI infrastructure company, is making a similar bet on a partnership with AMD. As more alternatives to Nvidia emerge, compute providers that aren’t locked into Nvidia deals may have an advantage in providing cost-efficient inference. “There are a bunch of chips that are starting to scale that have amazing [total cost of ownership], or that can operate much faster than Nvidia, but there’s not too many buyers for them,” Puklowski said. “By getting together with Upper90, this is not just, ‘a cool startup got some money to buy some compute.’ Like, this is the first signal of capital organizing itself and the fragmenting of Nvidia’s monopolistic dominance.”
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