Stelian Balta

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Stelian Balta

Stelian Balta

@stelyb

compute & intelligence backing the infrastructure of AI founder @ hyperchain capital

Singapore Katılım Nisan 2008
367 Takip Edilen27.2K Takipçiler
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Nscale
Nscale@nscale·
Nscale has entered into a definitive agreement to acquire Anyscale, enhancing our full-stack AI cloud platform. Together, Nscale’s vertically integrated AI infrastructure and @anyscalecompute's software would help customers move from raw compute to production AI. Read more: nscale.com/press-releases…
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Matei Zaharia
Matei Zaharia@matei_zaharia·
We benchmarked coding agents on our own internal tasks at Databricks and learned a lot! There are many surprising opportunities to lower cost and increase quality, and many models including open source ones are truly competitive now. 🧵
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Stelian Balta
Stelian Balta@stelyb·
Not your weights, not your IP.
David Sacks@DavidSacks

Legacy Media types are calling this Alex Karp interview a “crash-out” so that’s your first clue that he is actually saying something extremely insightful. He is articulating what real “AI safety” looks like in the enterprise. Not abstract alignment research or certification by a government-run DMV for AI. Real AI safety for businesses is the ability to control their own data, model weights, and compute — so a frontier lab can’t hoover up their proprietary knowledge and turn it into their next product. As Karp explains, technical customers want “control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it’s not being transferred to someone else.” Don’t think that can happen? Just look at Figma. According to The Information, Anthropic “blindsided” its then-business partner with the launch of Claude Design. Figma’s founder said Anthropic had not been “consistently honest” with them. Anthropic’s chief product officer had even served on Figma’s board until three days before the launch of Claude Design. Figma’s stock has fallen sharply this year while Anthropic’s valuation has surged. This isn’t an isolated example. Anthropic has launched Claude Science, Claude Security, Claude Legal, and of course Claude Code — each expanding into categories previously served by companies building on top of their models. The pattern is consistent: watch where value is being created, then move in directly. Dominate the model layer, then use that position to capture the most lucrative verticals. Dario has argued that open source models powerful enough to compete with Anthropic are “dangerous.” But dangerous to whom? Not to enterprises that want to retain control over their data and workflows. Dangerous to a business model that benefits from customers having few real alternatives at the model layer. As Karp exposes, true enterprise safety isn’t trusting that a lab’s future roadmap won’t include your business. It’s retaining the ability to choose — at the model layer — who gets to see and use your alpha.

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Yann LeCun
Yann LeCun@ylecun·
Exactly. I've been disseminating a similar message for years. The concentration of power in AI and the desire for control is by far the biggest danger of AI. It could lead to a few private companies and/or countries being in control of access to information, access to knowledge, and access to the tools of economic expansion. It's a kind of medieval obscurantism akin to the Ottoman empire banning the use of the printing press for 200 years, in part to keep control of the dogma, but also to protect the corporation of the calligraphers and scribes. Relevant historical bits about the Internet: 1. It took a deliberate decision by Al Gore and Bill Clinton to open up access of what was then ARPAnet to commercial entities and to the public, against the desires of the entrenched telecom industry. During a public roundtable about the "information superhighway" in 1993, the CEO of AT&T told Gore and Clinton "leave it to us". Gore said no. 2. In the late 1980s, setting up an Internet presence required buying proprietary hardware with proprietary OS and software stack from Sun Microsystems, HP, IBM, or Dell. By the 2000s, all of this was wiped out by commodity hardware, Linux, Apache, and an entirely free/open software stack. This migration to open platforms was the result of market forces. Infrastructure wants to be open. Foundation models are becoming an infrastructure and will inevitably become commoditized. Long term, the money is in the application layer, which is what I, Arthur Mensch, Alex Karp, and others have been saying.
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Matei Zaharia
Matei Zaharia@matei_zaharia·
It was great being on this panel with @vgcerf, @fchollet, Dave Patterson and @JohnOusterhout on building things that last at OpenFrontier yesterday! Probably the only time I’ll be on a panel with two Turing Award winners. Great conference overall and all the panels were recorded.
Laude Institute@LaudeInstitute

"Father of the Internet" Vint Cerf @vgcerf joins Dave Patterson, @fchollet and @JohnOusterhout to talk about lessons from building the internet and how they apply to building an open commons in AI. youtube.com/live/-41kYH6Jg…

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Stelian Balta
Stelian Balta@stelyb·
With Meta and SpaceX moving into the neocloud market and offering AI compute directly to customers, my conviction around the physical layer keeps getting stronger. The model layer is moving fast, open source models are getting close to frontier level and intelligence will become more accessible, cheaper and more widely distributed over time. Hyperscalers and neoclouds are becoming the infrastructure layer behind the next decade of innovation.
zerohedge@zerohedge

*META IS BUILDING A CLOUD BUSINESS TO SELL EXCESS AI COMPUTE First SpaceX, now Meta selling something called "excess compute"

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jietang
jietang@jietang·
Any new features we must have in the next version of glm?
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Stelian Balta
Stelian Balta@stelyb·
I’ve been skeptical of open weight models, tried most of them in our ai lab over the past 12 months and too many benchmark wins never matched the real world feel glm 5.2 is the first one I’ve tried that actually passes the vibe check, feels like a deepseek moment for inference open weights are getting close enough to frontier that cost could become a feature.
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Stelian Balta
Stelian Balta@stelyb·
tokenmaxxing is not ending, I think it's just getting started. the pareto setup: route 80% of your workload to deepseek or other cheap models, save frontier models for the 20% that actually needs them. intelligence is becoming a cost curve.
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