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Is there a "secret sauce" driving the development of AI models? FutureTech researchers at MIT CSAIL found that at the frontier, sheer scale drives LLM performance, but proprietary techniques & algorithmic advances matter more away from it:

MIT CSAIL

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35,995 views • 5 months ago •via X (Twitter)

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$PLTR CEO Alex Karp said Palantir’s “secret to sales” is hoping customers LLM companies first and realize “they don’t care about you at all.” Frontier AI Models solve real problems but create even bigger ones while Palantir gives customers the ontology layer to solve those problems and “own the means of production.”

$PLTR CEO Alex Karp said Palantir’s “secret to sales” is hoping customers LLM companies first and realize “they don’t care about you at all.” Frontier AI Models solve real problems but create even bigger ones while Palantir gives customers the ontology layer to solve those problems and “own the means of production.”

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The next frontier after language models is world models, and learning to predict the next state of a world. Hear from our researchers how these models really work at a low-level and the mountain we're climbing. A general-purpose world simulator (AKA sci-fi) is now in sight.

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We got attacked by secret unreleased proprietary models and defended ourselves with an open model, more precisely the NVIDIA quantized version of GLM 5.2 coming from Z.ai. Banning any open model would hurt first cyber security defenders, startups, small companies, researchers and everyone who's not a frontier lab and need on-prem affordable controlable models to compete and protect themselves. Let's not do that!

We got attacked by secret unreleased proprietary models and defended ourselves with an open model, more precisely the NVIDIA quantized version of GLM 5.2 coming from Z.ai. Banning any open model would hurt first cyber security defenders, startups, small companies, researchers and everyone who's not a frontier lab and need on-prem affordable controlable models to compete and protect themselves. Let's not do that!

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#WATCH | Bengaluru, Karnataka: Co-founder, Sarvam AI, Pratyush Kumar says, "... Let me begin with what really is the mission of Sarvam. Many of you know us as a company, but it's important for us to tell you how we approach things. There are three things worth saying. Firstly, we are building at the frontier. AI is one of those technologies that is not only financially lucrative to build, but is also at the pinnacle of human engineering and insight. That pinnacle is moving much faster than in other generations of technology. That's why being at the frontier, at the very edge, becomes so significant. Everything that we do at Sarvam is about being at the frontier, building it, defining it, keeping pace with it, and pushing it further. Our first commitment is to have an innovation-led organisation that is building the frontier here in India..."

#WATCH | Bengaluru, Karnataka: Co-founder, Sarvam AI, Pratyush Kumar says, "... Let me begin with what really is the mission of Sarvam. Many of you know us as a company, but it's important for us to tell you how we approach things. There are three things worth saying. Firstly, we are building at the frontier. AI is one of those technologies that is not only financially lucrative to build, but is also at the pinnacle of human engineering and insight. That pinnacle is moving much faster than in other generations of technology. That's why being at the frontier, at the very edge, becomes so significant. Everything that we do at Sarvam is about being at the frontier, building it, defining it, keeping pace with it, and pushing it further. Our first commitment is to have an innovation-led organisation that is building the frontier here in India..."

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Empyreal

34,857 views • 1 year ago

Interesting that in three of my recent conversations with Krishna at Anthropic, Dylan Patel, and Gavin Baker, each said that frontier tokens are capturing the majority of the economic value. Gavin: "An overwhelming amount of the economic returns to AI at the model layer have been at the frontier. That's surprising to me, and I think it's been surprising to a lot of people. This is one of the most important questions to be answered, and you need to have a hypothesis on it as an investor." Krishna: "We think the returns to frontier intelligence are extremely high. Customers invest really heavily in more tokens with the newer models. The ones at the frontier clearly are capturing this economic value, driving meaningful ROI for customers. The returns to frontier intelligence are not slowing down." Dylan: "No one gives a crap about GPT-4 class models. They want the frontier because the frontier lets them create the economically valuable things."

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121,110 views • 3 months ago

Are open-source AI models catching up? Erik Voorhees tells David it depends on the benchmark. But if an open model can match frontier AI from a few months ago at 10% of the cost, that's worth watching. What's your take?

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Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

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Congrats to our partners Together AI on their $800M Series C fundraising round. Few teams have done more to make open models fast, accessible, and production-ready. We’re excited to keep working with Vipul Ved Prakash and the team on the next frontier of inference: lower costs, better performance, and open models at real scale.

Congrats to our partners Together AI on their $800M Series C fundraising round. Few teams have done more to make open models fast, accessible, and production-ready. We’re excited to keep working with Vipul Ved Prakash and the team on the next frontier of inference: lower costs, better performance, and open models at real scale.

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i found the secret to writing copy that SELLS with AI... it's not about the model, it's not about the prompt, and it doesn't matter how good you are at writing it's about feeding AI with world-class examples i built a full copywriting swipe file you can use with any LLM: - over 1,000 examples of the best emails, ads and landing pages copy - my 3-step process to use this inside AI projects - my super-prompt to extract the sauce from any copy reply "SWIPE" + retweet and i'll send it for free (must be following so i can DM)

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AI has a "last-mile problem" similar to self-driving cars. With self-driving cars, early demos impressed, but real-world deployment took years. It's easy to hack up a prototype, but making it work reliably at scale is hard. If each step of an AI agent is only 95% accurate, none of the 30-step workflows will work reliably. Going from 95% to 99.9% accuracy is the real challenge.

AI has a "last-mile problem" similar to self-driving cars. With self-driving cars, early demos impressed, but real-world deployment took years. It's easy to hack up a prototype, but making it work reliably at scale is hard. If each step of an AI agent is only 95% accurate, none of the 30-step workflows will work reliably. Going from 95% to 99.9% accuracy is the real challenge.

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14,926 views • 1 year ago

Wave 9 is here: a frontier model built for software engineering. Introducing our new family of models: SWE-1, SWE-1-lite, and SWE-1-mini. Based on internal evals, it has performance nearing that of frontier models from the foundation labs. Available now, only in Windsurf!

Wave 9 is here: a frontier model built for software engineering. Introducing our new family of models: SWE-1, SWE-1-lite, and SWE-1-mini. Based on internal evals, it has performance nearing that of frontier models from the foundation labs. Available now, only in Windsurf!

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Elon Musk is building a training cluster/ supercomputer so vast it’s visible from space. Colossus, in Memphis, Tennessee, is more than an AI experiment. It’s a statement of intent. A million GPUs wired together by the end of this year. A $40 to $60 billion physical bet that brute-force scale will birth the world’s most intelligent AI. This isn’t theory. It’s infrastructure. It’s industrial. And it shows us what the future looks like, not just in capability, but in the sheer energy, capital, and ambition now required to compete at the frontier. Colossus is the embodiment of a new era: Intelligence as utility.

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