#ai-labs — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #ai-labs, aggregated by home.social.
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#Wirestock, a platform for photographers, pivoted to a #dataprovider for #AIlabs in 2023, supplying #datasets of images, videos, and design assets. The company raised $23 million in Series A funding to expand its data supply business, which currently provides multimodal data to six major foundation model makers. https://techcrunch.com/2026/05/14/wirestock-raises-23m-to-supply-multi-modal-data-to-ai-labs/?eicker.news #tech #media #news
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Chinese #AIlabs are excelling at building #LLMs due to a culture that emphasises #meticulouswork, #collaboration, and a focus on the #finalproduct rather than individual recognition. This cultural difference, coupled with a large pool of talented students and engineers, allows #China to quickly adapt to new techniques and build highly effective models. https://www.interconnects.ai/p/notes-from-inside-chinas-ai-labs?eicker.news #tech #media #news
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“Banks are hunting for new ways to offload risks tied to a glut of data centre debt as the race to build #AIInfrastructure stretches financing limits among the largest global lenders. Groups including JPMorgan Chase, Morgan Stanley and SMBC are trying to find ways to distribute portions of data centre-related deals to a broader range of investors, according to people familiar with the matter.
Lenders are exploring private deals to sell stakes in the #debt as well as so-called risk transfers to reduce exposure to big borrowers and free up capacity for more lending. The efforts showcase the unprecedented scale of #borrowing that underpins the #AI sector and the pressure it is putting on lenders. #Oracle and #CoreWeave, two data centre operators, have borrowed hundreds of billions to build sites across the #USA for #AILabs.”
#ArtificialIntelligence / #Banking / #capacity / #profit <https://archive.md/GoRyM> / <https://ft.com/content/08aba5e4-5834-4e79-a48d-989a2c5bad0f> (paywall)
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All 11 xAI cofounders have departed Musk's AI startup, including eight since January. The $250 billion company lost researchers like Jimmy Ba (Adam optimizer co-author) and DeepMind's Igor Babuschkin after SpaceX's acquisition. Musk admitted xAI "was not built right" and is rebuilding with product hires rather than research talent. Suggests organizational challenges that funding and compute infrastructure alone cannot resolve.
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#GoogleCloud is gaining momentum against AWS and Microsoft Azure, largely due to its focus on #AIstartups. The company works with nine out of ten leading #AIlabs and 60% of #generativeAI #startups, including #Lovable and #Windsurf. Google Cloud offers generous deals, such as $350,000 in cloud credits, to attract and support these startups. https://techcrunch.com/2025/09/18/how-ai-startups-are-fueling-googles-booming-cloud-business/?eicker.news #tech #media #news
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#NewYork state lawmakers passed the #RAISE Act, aiming to prevent #AI-related disasters: requires large #AIlabs to publish #safety reports and #incidents, with penalties for non-compliance. https://techcrunch.com/2025/06/13/new-york-passes-a-bill-to-prevent-ai-fueled-disasters/?eicker.news #tech #media #news
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The chaotic reality of contemporary AI labs
This was interesting from DeepMind’s Sholto Douglas about the reality of working in AI labs. They have billions of dollars flooding into them but they’re also scaling rapidly in a slightly chaotic way, working in ways that constantly throw up more things to explore than their existing capacity allows:
I also think that it’s underappreciated just how far from a perfect machine these labs are. It’s not like you have a thousand people optimizing the hell out of computer use and they’ve been trying as hard as they possibly can.
Everything at these labs, every single part of the model generation pipeline is the best effort pulled together under incredible time pressure, incredible constraints as these companies are rapidly growing, trying desperately to pull and upskill enough people to do the things that they need to do. I think it is best understood as with incredibly difficult prioritization problems.
#AILabs #bigTech #capitalism #corporations #investment #Research
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During the #DiscAI-lab event, our colleague @neocarlitos will talk about why reusable and transparent #AI is impossible without #Software sharing at University of Utrecht #AILabs
https://www.uu.nl/en/research/ai-labs/disc-ai-lab