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Recent AI breakthroughs challenge the status quo narrative that only closed, mega labs have the ability to push the frontier of superintelligence. Today we announce Nous Psyche built on Solana - a cooperative training network for generative AI. Psyche coordinates heterogeneous hardware to join a run and train open-source... show more

Nous Research

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Read more in our blog post:

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You can now experiment with Psyche’s DisTrO-enabled training code on our GitHub, and the larger open-sourced distributed training stack will be released alongside testnet.

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Apply to attend Nous Research x Solana Foundation this Thursday in NYC:

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Confused about AI? Get clarity today with Book VI - "The Rational Being!" Understand the benefits & risks, empower your future now by learning what AI really is and how it really works! Also check out the Free Weekly Newsletter "How Things Work: A Brief History of Reality"

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@solana Probably nothing

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@solana lfg brosefs

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@solana hauntingly beautiful

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@solana Wow nous just keeps on delivering. Keep it up.

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@solana 10/10 storytelling. Looks sick!!

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@solana Become the swarm you’d like to see in the world.

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@solana CA?

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Jensen says Open Source can be MORE expensive for enterprises, Brad Gerstner explains why: Brad Gerstner: “Over the last two weeks, everybody's been saying that the Chinese have caught up, that open source tokens have caught up in intelligence, that they're much cheaper, etc. And Elon comes out and says, ‘Not so fast. We're entering the singularity, and the frontier models are way further ahead than people think.’ I believe that to be true. And then Jensen came out this week and said, ‘Closed models are actually cheaper if you don't have to build it for yourself, the training costs, and a lot of expertise to fine-tune, and maintain, and guardrail, and keep it safe. So he's basically making the argument that not only are the frontier models further ahead, but that the cost differential between the two is not what everybody's making it out to be, which I think explains why (closed models) continue to run away with it on the revenue side of the equation. For the vast majority of use cases, I think token consumption is going up for the open source guys, while share of economics is going up for the frontier labs. I think that's what we want to see.” $NVDA

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$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."

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We put together a $1.1B round for River AI to build American leadership in open weights. Frontier labs push the boundary of humanity, but open weights empower humanity, putting intelligence into everyone's hands. Igor Babuschkin has built frontier capability three times over. Now he's making it something you can own.

Hemant Taneja

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Sundar Pichai just reminded everyone that Google was built on open source. He personally worked on Chromium, Android, and Kubernetes before becoming CEO. Three systems that power billions of devices today. Now Google is applying the same philosophy to AI. Their Gemma models are updated year after year, designed to run on edge devices rather than requiring massive cloud infrastructure. The question he got was why not release a large open source frontier model. His answer was revealing: frontier training requires enormous capex investment, and Google is putting billions into R&D to stay at the frontier. The open source AI landscape is quietly consolidating around a few players who can sustain the investment. Google's two decades of open source credibility gives them a position that's hard to replicate.

Sundar Pichai just reminded everyone that Google was built on open source. He personally worked on Chromium, Android, and Kubernetes before becoming CEO. Three systems that power billions of devices today. Now Google is applying the same philosophy to AI. Their Gemma models are updated year after year, designed to run on edge devices rather than requiring massive cloud infrastructure. The question he got was why not release a large open source frontier model. His answer was revealing: frontier training requires enormous capex investment, and Google is putting billions into R&D to stay at the frontier. The open source AI landscape is quietly consolidating around a few players who can sustain the investment. Google's two decades of open source credibility gives them a position that's hard to replicate.

Shruti

152,324 görüntüleme • 1 ay önce