steve chen

531 posts

steve chen

steve chen

@stevechen

Co-Founder, @YouTube.

San Francisco, CA Katılım Nisan 2007
1.4K Takip Edilen34.7K Takipçiler
steve chen
steve chen@stevechen·
Great catching up with @abc7kristensze! It’s astonishing to look back at the last 21 years of YouTube’s growth. From a simple idea to a truly global community, YouTube has come a long way. Check out the interview here: abc7news.com/post/youtube-f…
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steve chen
steve chen@stevechen·
@CardilloSamuel Seeing this prompted me to download and try hermes agent. So far, so good!
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Samuel Cardillo
Samuel Cardillo@CardilloSamuel·
oh no, peter, openclaw founder, blocked me after i stated, without even tagging him, that i prefered hermes agent. and it literally confirms all the feelings i had toward him. he's unable to take critics, feedbacks, ... kudos to him for giving agentic ai the highlight it needed but thanks god for @NousResearch for giving us a team that actually care about community and build real solutions.
Samuel Cardillo tweet media
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れいちょ / RAIT-09
れいちょ / RAIT-09@rainbow_0219·
🚀 Just released my first Obsidian plugin — Agent Client Plugin! Bring AI coding agents (Claude Code, Codex, Gemini CLI, etc.) directly into your vault. 🧩Organize notes, search the web, and automate workflows with MCP tools. Built on Agent Client Protocol (ACP) by Zed.
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steve chen
steve chen@stevechen·
@DavidSacks I just installed the gateway on my Mac mini and i have two other machines talking to it. Clawdbot is all I’ve been playing with this last week. This month’s bill for Claude is going to reach a peak. Clawdbot is the future!
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David Sacks
David Sacks@DavidSacks·
Replaced my NYT subscription with a Mac Mini and Clawdbot. Told it to gather as much factual information as possible, then rewrite it as left-wing propaganda. Works perfectly.
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steve chen
steve chen@stevechen·
@liquidai @ramin_m_h Love seeing this! Lisa Su is a massive inspiration to me, both as a Taiwanese icon and a visionary leader. Her turnaround of AMD is legendary. Seeing the CEOs of Liquid @ramin_m_h and AMD @LisaSu together on stage is amazing!!
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Liquid AI
Liquid AI@liquidai·
Today, we release LFM2.5, our most capable family of tiny on-device foundation models. It’s built to power reliable on-device agentic applications: higher quality, lower latency, and broader modality support in the ~1B parameter class. > LFM2.5 builds on our LFM2 device-optimized hybrid architecture > Pretraining scaled from 10T → 28T tokens > Expanded reinforcement learning post-training > Higher ceilings for instruction following 🧵
Liquid AI tweet media
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Dominic Lee 李梓敬
Dominic Lee 李梓敬@dominictsz·
Oath-taking ceremony! I swear that, being a member of the Legislative Council of the Hong Kong Special Administrative Region of the People’s Republic of China, I will uphold the Basic Law of the Hong Kong Special Administrative Region of the People’s Republic of China, bear allegiance to the Hong Kong Special Administrative Region of the People’s Republic of China and serve the Hong Kong Special Administrative Region conscientiously, dutifully, in full accordance with the law, honestly and with integrity.
Dominic Lee 李梓敬 tweet media
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Red Xiao
Red Xiao@Red_Xiao_·
Today marks a moment I'll remember for the rest of my life. When we started Manus, few believed that general AI agents could work. We were told it was too early, too ambitious, too hard. But we kept building. Through the doubts, the setbacks, and the countless nights wondering if we were chasing the impossible. We weren't. This isn't just an acquisition. It's validation that the future we've been building toward is real, and it's arriving faster than anyone expected. But this is not the end. The era of AI that doesn't just talk, but acts, creates, and delivers, is only beginning. And now, we get to build it at a scale we never could have imagined. To everyone who believed in us before it was obvious: thank you. The best is yet to come.
Manus@ManusAI

Manus is entering the next chapter: we’re joining forces with Meta to take general agents to the next level. Full story on our blog: manus.im/blog/manus-joi…

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Liquid AI
Liquid AI@liquidai·
Meet the strongest 3B model on the market. LFM2-2.6B-Exp is an experimental checkpoint built on LFM2-2.6B using pure reinforcement learning. > Consistent improvements in instruction following, knowledge, and math benchmarks > Outperforms other 3B models in these domains > Its IFBench score surpasses DeepSeek R1-0528, a model 263x larger Download and play 👉 huggingface.co/LiquidAI/LFM2-… Happy holidays, The Liquid AI team🎄✨
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Manus
Manus@ManusAI·
$0 → $100M ARR in 8 months. Since we launched in March: -147 trillion tokens processed -80M+ virtual computers created -Total revenue run rate over $125M Thank you to everyone building with us. manus.im/blog/manus-100…
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steve chen
steve chen@stevechen·
It was an incredible opportunity to be in Bogotá, Colombia, in person this summer to speak at the Game Changers Fest 2025 hosted by @GameChangersC0. A bonus was to do this 1:1 interview with @IvanDuque, the president of Colombia from 2018-2022: youtube.com/watch?v=88grTZ…
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steve chen
steve chen@stevechen·
@PingbangHu Taiwan to Urbana-Champaign to Silicon Valley. Congrats.
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Pingbang Hu 🇹🇼
Pingbang Hu 🇹🇼@PingbangHu·
3 months ago, saw this, applied. A month ago, got notified that I passed the first stage. Went through 4 rounds of interviews. Few days ago, received the offer. Excited and honored. See you in San Francisco soon I guess.
Pingbang Hu 🇹🇼 tweet media
Anthropic@AnthropicAI

We’re running another round of the Anthropic Fellows program. If you're an engineer or researcher with a strong coding or technical background, you can apply to receive funding, compute, and mentorship from Anthropic, beginning this October. There'll be around 32 places.

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Liquid AI
Liquid AI@liquidai·
Introducing Liquid Nanos ⚛️ — a new family of extremely tiny task-specific models that deliver GPT-4o-class performance while running directly on phones, laptops, cars, embedded devices, and GPUs with the lowest latency and fastest generation speed. > model size: 350M to 2.6B > built on LFM2, our v2 efficient model architecture > perform competitively with models up to hundreds of times larger > enable core agentic tasks: precise data extraction, multilingual translation, tool call, math, and RAG. 1/n
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