#ailabs — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #ailabs, aggregated by home.social.
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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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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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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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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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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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“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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“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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“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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“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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https://www.europesays.com/people/53522/ ‘Dario does not respect engineers’: Developer urges unhappy techies to quit Anthropic #AILabs #Anthropic #DarioAmodei #JavaScript #SoftwareEngineering #TechCulture #TheoBrowne #WebDevelopment
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https://www.europesays.com/people/50526/ ‘Dario does not respect engineers’: Developer urges unhappy techies to quit Anthropic #AILabs #Anthropic #DarioAmodei #JavaScript #SoftwareEngineering #TechCulture #TheoBrowne #WebDevelopment
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https://www.europesays.com/people/50442/ ‘Dario does not respect engineers’: Developer urges unhappy techies to quit Anthropic #AILabs #Anthropic #DarioAmodei #JavaScript #SoftwareEngineering #TechCulture #TheoBrowne #WebDevelopment
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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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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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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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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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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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Anthropic says Chinese companies misused Claude AI; Elon Musk lashes out
Elon Musk on Monday lashed out at Anthropic after the Dario Amodei-led company accused Chinese AI companies of…
#UnitedStates #US #USA #AILabs #anthropicdatastealin #anthropicstealingdata #anthrpoicai #Claude #ClaudeAImodel #claudecod #datatheft #distillation #ElonMusk #elonmuskonanthropic #industrial-scaledistillationattacks #Musk
https://www.europesays.com/2801482/ -
Invisible Technologies just announced a 20× revenue jump as AI labs scramble to hire its human‑in‑the‑loop workforce. The ex‑McKinsey‑backed firm is scaling data‑labeling and AI‑training pipelines, backed by fresh venture funding. How this model reshapes machine‑learning development is worth a read. #InvisibleTechnologies #AIlabs #HumanInTheLoop #DataLabeling
🔗 https://aidailypost.com/news/invisible-technologies-posts-20x-revenue-growth-ai-labs-hire-its
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Tôi tạo ứng dụng máy tính để bàn để gỡ lỗi AI, cho phép theo dõi, phát lại và gỡ lỗi từng tác vụ của agent trực tiếp trên laptop. #AILabs #GỡLỗiAI #ỨngDụngMáyTính #AI #GỡLỗi #LupisLabs #DebugAI #Agent #MáyTínhĐểBàn
https://www.reddit.com/r/SideProject/comments/1orqdhq/i_create_a_desktop_app_for_debug_ai_agent/
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—> #TheLateShow ⦁ Meanwhile ⦁ #StephenColbert <— #KourtneyKardashian's Vagina Lollipops #LOTR Wedding Stealing #Labubus Bomb #AI-Labs #Comedy #Humour #Humor #Colbert #Pol #Politics #GeoPolitics #WorldNews #News #AusPol #CdnPoli #EUpol #NZpol #UKpol #USpol youtu.be/T7H50WIThDE
Meanwhile..Kourtney Kardashian... -
—> #TheLateShow ⦁ Meanwhile ⦁ #StephenColbert <— #KourtneyKardashian's Vagina Lollipops #LOTR Wedding Stealing #Labubus Bomb #AI-Labs #Comedy #Humour #Humor #Colbert #Pol #Politics #GeoPolitics #WorldNews #News #AusPol #CdnPoli #EUpol #NZpol #UKpol #USpol youtu.be/T7H50WIThDE
Meanwhile..Kourtney Kardashian... -
#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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#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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#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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#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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#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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#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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#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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#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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#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.
It connects to something Mark Zuckerberg observed here:
What we basically found was that we were bottlenecked on compute to run tests, based on the number of hypotheses. It turns out, even with just the humans we have right now on the ads team, we already have more good ideas to test than we actually have either compute or, really, cohorts of people to test them with.
Even if you have three and a half billion people using your products, you still want each test to be statistically significant. It needs to have hundreds of thousands or millions of people. There’s only so much throughput you can get on testing through that. So we’re already at the point, even with just the people we have, that we can’t really test everything that we want.
#AILabs #bigTech #capitalism #corporations #DeepMind #investment #markZuckerberg #Meta #Research
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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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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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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.
It connects to something Mark Zuckerberg observed here:
What we basically found was that we were bottlenecked on compute to run tests, based on the number of hypotheses. It turns out, even with just the humans we have right now on the ads team, we already have more good ideas to test than we actually have either compute or, really, cohorts of people to test them with.
Even if you have three and a half billion people using your products, you still want each test to be statistically significant. It needs to have hundreds of thousands or millions of people. There’s only so much throughput you can get on testing through that. So we’re already at the point, even with just the people we have, that we can’t really test everything that we want.
#AILabs #bigTech #capitalism #corporations #DeepMind #investment #markZuckerberg #Meta #Research
-
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.
It connects to something Mark Zuckerberg observed here:
What we basically found was that we were bottlenecked on compute to run tests, based on the number of hypotheses. It turns out, even with just the humans we have right now on the ads team, we already have more good ideas to test than we actually have either compute or, really, cohorts of people to test them with.
Even if you have three and a half billion people using your products, you still want each test to be statistically significant. It needs to have hundreds of thousands or millions of people. There’s only so much throughput you can get on testing through that. So we’re already at the point, even with just the people we have, that we can’t really test everything that we want.
#AILabs #bigTech #capitalism #corporations #DeepMind #investment #markZuckerberg #Meta #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 -
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 -
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 -
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 -
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