Sarah Chieng
@MilksandMatcha
1.6K Following 27.8K Followers
Pretraining teaches a model to predict. Reinforcement learning teaches it to act.
@jeffreygwang of @OpenAI explains how the two paradigms turn next-token prediction into models that can reason, use tools and complete useful tasks.
Big Chip Club with @cerebras // @alyciazcary
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Not every agent task needs a frontier model.
@Thom_Wolf (Co-founder of Hugging Face) on routing work to smaller open models for repeatable sub-tasks, evaluation, and cost control, matching compute to the value of the work.
Join us in the Token Billionaires Lounge by @cerebras and @aiDotEngineer.
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should we give @elonmusk early access to gpt-5.6-sol ultrafast
Agents are only as good as the context they can access.
@jerryjliu0 on production document workflows: structure the data, retrieve broadly, then zoom in only where deeper analysis is needed.
Join us in the Token Billionaires Lounge, presented by
@cerebras and @aiDotEngineer
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“The codebase is part of the prompt.”
@dexhorthy on why coding loops amplify existing patterns, and why better verifiers, human review, and deliberate codebase gardening matter more as generation gets faster.
Join us in the Token Billionaires Lounge, presented by @cerebras and @aiDotEngineer.
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AI should reduce workflow friction, not add another chatbot.
@sarahmsachs (Head of AI @ Notion) on moving from isolated assistance to durable agent workflows built around a shared system of record.
From the Token Billionaires Lounge, presented by @cerebras and @aiDotEngineer.
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Open models are being asked to do more in smaller footprints.
@thorwebdev on the tradeoffs behind open, on-device AI, and how model size, deployment location, and product goals shape what developers can build.
Join us in the Token Billionaires Lounge by @cerebras and @aiDotEngineer.
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From training his first neural net in high school to working at OpenAI.
@jeffreygwang followed a five-year trail through Andrew Ng’s course, early GAN papers + OpenAI research.
By the time ChatGPT arrived, “it all pointed toward OpenAI.”
Presented with @cerebras // @alyciazcary
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The hard part of agent loops is not starting them!
It’s knowing when to move up a layer, and when to come back down. @swyx explains the operator skill behind useful loops: automate repeatable work, watch for failure, drop into the problem when reliability breaks, then climb back up once the system is sound.
That flexibility (not token volume for its own sake) is the key to productive loops.
Join us in the Token Billionaires Lounge, presented by
@cerebras and @aiDotEngineer
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the new age of 'personalized shopping'
I made a clone of aritzia where I'm the model on every piece of clothing
Buillt with gpt-5.6-sol standard...but just you wait for gpt-5.6-sol ultrafast (750 tok/s) running on @cerebras
coming soon 👀
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Redefining 'personalized shopping' with GPT-5.6-sol
NYC builders: next Tuesday we’re turning @datadoghq into Cafe Compute with @GoogleDeepMind ☕️
Come try Gemma 4 31B at @cerebras speed, get increased model access, and meet the teams behind it.
Comment what you're building, and top ideas will get a special gift from Cerebras 🤭
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Sometimes the best DX is deleting the README.
@andrewqu (@vercel) built npx skills add so one skill could install across Claude Code, Codex, OpenCode, and more.
That tiny CLI became the flywheel for Vercel’s Skills Marketplace.
Join us in the Token Billionaires Lounge, presented by @cerebras and @aiDotEngineer
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The fastest way to get the same AI UI every time is asking for “a beautiful UI.”
What works better: interview yourself, decide design before code, use ugly data, set scale/tone, then art direct the loop.
Fast generation does not replace taste. It makes taste matter more.
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Should people building AI products use the competition?
@OfficialLoganK's answer: obviously.
Using other teams’ tools is how you understand what great feels like, find your own gaps, and keep up with the frontier. The internet discourse is just a bonus 😅
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I had to ask @OfficialLoganK whether he actually bought the Mac mini 😅
He did, and his take is a useful reminder: technical possibility isn’t the same as a great product. The next big opportunity in local AI may be making it click for normal people.
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Technical writing is the #1# top-of-funnel motion at a $12B company
@philipkiely broke down exactly how he does it, his full writing process, the hindsight 20/20 lessons, and how one article drove 500K+ views
This [technical] Write and Learn workshop #5# is part of our Independent Studies series, hosted with @swyx @KernelLabs_ai.
All sessions are recorded. Our next one will be in two weeks :)
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5 part loops prompting structure to avoid MASSIVE TOKEN BURN
on set filming with the co-founder of hugging face
geopolitics, open models, why hasn't my reachy robot arrived yet
the one and only @Thom_Wolf
I host a ton of events.
This video was so fun to make, capturing how my team and I leverage AI when curating an incredibly high volume of intimate, tasteful, and high-quality events using some of our favorite tools like @OpenAIDevs Codex, Eve by @vercel and more.
But we are also excited to learn. Let me know if you have any suggestions or favorite tools and workflows :)
And if you're heading to ICML, definitely say hi to the @Cerebras team.
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