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Everyone is obsessed with which AI model is smartest. Wrong question. The real question is: whose worldview does the model export? China will deflate the cost of compute, finance data centers across Africa and emerging markets, and distribute open-source models trained to see history through Beijing’s eyes. Kimi K2... show more

Ben Pouladian

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27,799 views • 29 days ago •via X (Twitter)

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China is once again unsettling its American competitors in the AI race. Chinese labs have returned to the spotlight with the unveiling of GLM 5.2, described as the most powerful AI model ever trained in China — and one of the leading open‑source models worldwide. 🔍 Key highlights of “GLM 5.2”: ♦️ It is considered the strongest AI model developed in China to date, and ranks among the smartest open‑source models available. ♦️ It operates at a cost less than one‑tenth that of Anthropic’s latest models, making it a far more economical option. ♦️ It is likely to attract developers and companies seeking powerful, low‑cost models — especially amid growing technical and geopolitical restrictions. ♦️ Some evaluations place the model among the top globally, trailing OpenAI’s models while outperforming several competitors in specialized benchmarks and performance tests.

China is once again unsettling its American competitors in the AI race. Chinese labs have returned to the spotlight with the unveiling of GLM 5.2, described as the most powerful AI model ever trained in China — and one of the leading open‑source models worldwide. 🔍 Key highlights of “GLM 5.2”: ♦️ It is considered the strongest AI model developed in China to date, and ranks among the smartest open‑source models available. ♦️ It operates at a cost less than one‑tenth that of Anthropic’s latest models, making it a far more economical option. ♦️ It is likely to attract developers and companies seeking powerful, low‑cost models — especially amid growing technical and geopolitical restrictions. ♦️ Some evaluations place the model among the top globally, trailing OpenAI’s models while outperforming several competitors in specialized benchmarks and performance tests.

China pulse 🇨🇳

14,293 views • 1 month ago

ELON: CHINA HAS THE BEST OPEN SOURCE AI MODELS RIGHT NOW “The best open source models are generally from China, which is bizarre. I think the second best one, or maybe it’s better than second best, is Grok 2.5. The open source model is actually very good, and we will continue to open source our models.” Source: The All-In Podcast

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The new SpaceX-Cursor model is going to be insane. It is being trained from scratch, unlike previous Composer models, which were built off Kimi. This new model is Elon’s attempt to get back in the AI race, and he might rejoin as the frontrunner. Composer 2.5 is already a world-class model, only losing to models like GPT-5.5, Opus 4.8, and Fable 5. Grok Composer 3, with SpaceX’s massive compute and xAI’s team, could become the best AI model on the planet. Elon is back.

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This is the best way to understand how ML models actually work! Use Drawdata to draw a 2D dataset in Jupyter. Use it to actively pick data from the widget and update the model as the data is being drawn! Fully interactive, real-time, and open-source!

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Shay Boloor

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SPACE 😎

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Emmy 🥷

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When we first met Tom, his obsession with energy markets came through immediately. Seemed random, but it's "actually" central to what he's building at Actual Computer. The thesis is that local inference is inevitable. Open source models are getting good enough, people don't want to feed their thoughts to AI labs, and demand for compute will continue to be insatiable. But the main forcing function is that chips aren't the bottleneck anymore - power is. Compute is derivative of energy, and the massive data center buildout has created an energy shortage where GPUs sit idle waiting for power to come online. Yet one place that already has power, and always will, is everywhere else. Homes. Businesses. Universities. Collectively, they have more compute than all the data centers combined. Tom Lynch goal is to build a distributed network of people plugging in their local compute (devices like Mac minis to consumer Nvidia cards) to serve inference demand. The substrate he's chosen is Bittensor, on Subnet 95. Actual Computer has an exceptional team behind it, and this is one of the projects that's gotten me most excited in a long time. Enjoy this conversation with the two of us!

When we first met Tom, his obsession with energy markets came through immediately. Seemed random, but it's "actually" central to what he's building at Actual Computer. The thesis is that local inference is inevitable. Open source models are getting good enough, people don't want to feed their thoughts to AI labs, and demand for compute will continue to be insatiable. But the main forcing function is that chips aren't the bottleneck anymore - power is. Compute is derivative of energy, and the massive data center buildout has created an energy shortage where GPUs sit idle waiting for power to come online. Yet one place that already has power, and always will, is everywhere else. Homes. Businesses. Universities. Collectively, they have more compute than all the data centers combined. Tom Lynch goal is to build a distributed network of people plugging in their local compute (devices like Mac minis to consumer Nvidia cards) to serve inference demand. The substrate he's chosen is Bittensor, on Subnet 95. Actual Computer has an exceptional team behind it, and this is one of the projects that's gotten me most excited in a long time. Enjoy this conversation with the two of us!

Sami Kassab

35,706 views • 6 months ago

before you watch the World Cup final tonight, watch this 30-minute interview with Kimi founder Zhilin Yang it's the clearest look I've seen at how K2 was actually built and where AI models go next > why compute scaling still beats every other method > why the "data flywheel" everyone talks about hasn't formed yet > the real challenge in multimodality nobody mentions > why K2 was closer to a base model — the real potential wasn't unlocked yet this is only part of the interview, translated to English — and everything he hinted at just shipped as Kimi K3, 2.8 trillion parameters, the biggest open model ever full breakdown below

before you watch the World Cup final tonight, watch this 30-minute interview with Kimi founder Zhilin Yang it's the clearest look I've seen at how K2 was actually built and where AI models go next > why compute scaling still beats every other method > why the "data flywheel" everyone talks about hasn't formed yet > the real challenge in multimodality nobody mentions > why K2 was closer to a base model — the real potential wasn't unlocked yet this is only part of the interview, translated to English — and everything he hinted at just shipped as Kimi K3, 2.8 trillion parameters, the biggest open model ever full breakdown below

Kirill

533,393 views • 27 days ago

America is being covered with massive AI data centers, and almost nobody is asking the obvious question: What the hell are they really for? Shannon Joy and Kristen Meghan👩‍🔬🐻 say the public is being sold a lie. They’re not just data centers. They’re the control grid for the “digital slave state.” And now, the one congressman who stood in the way is under attack...👇🧵

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The Vigilant Fox 🦊

62,979 views • 2 months ago

Is compute scarcity masking the real economics of AI? interesting point from Peter Fenton: open-weight models are still complex to run well. For now, the big labs have the bundle: model + compute + reliability + access... and thus pricing power. But if compute supply loosens and open model tooling gets easier, routine AI work can more easily move to cheaper/open models.

Is compute scarcity masking the real economics of AI? interesting point from Peter Fenton: open-weight models are still complex to run well. For now, the big labs have the bundle: model + compute + reliability + access... and thus pricing power. But if compute supply loosens and open model tooling gets easier, routine AI work can more easily move to cheaper/open models.

Deirdre Bosa

50,558 views • 1 month ago

$PLTR Palantir CEO Alex Karp rips apart the overselling by various AI companies to enterprises: “This is the voice of American business that is being channeled through me” “The reality of compute + ontology + model is changing the course of history.” … “We do not have to oversell what we have. And it’s all being built in this country. ”

$PLTR Palantir CEO Alex Karp rips apart the overselling by various AI companies to enterprises: “This is the voice of American business that is being channeled through me” “The reality of compute + ontology + model is changing the course of history.” … “We do not have to oversell what we have. And it’s all being built in this country. ”

Jack Prescott

23,526 views • 1 month ago