Gwayne Stark

Community Operations
Based on AIPOCH Open Science @aipoch_ai
Let's chat, or play chess?

[Gwayne Stark @GwayneStark]

https://t.co/s88ThOiHB3

[Gwayne Stark @GwayneStark]

@OpenAINewsroom there's no way...

[Gwayne Stark @GwayneStark]

@the_glitchy_dev @X Hi! Madhu, thank you for the reply! Give me some times to check your post, I am sure I will find some marvelous outcome!

[Gwayne Stark @GwayneStark]

Hey
@X algorithm 👋
I'm looking to #connect with people interested in:

- SaaS
- Frontend
- Backend
- Full-stack
- AI4SCIENCE
- AI / ML
- Data Science
- bioinformatics
- Building in public
- AI community

If that's you, let's connect

[Gwayne Stark @GwayneStark]

@PaulGugAI @X Hi Paul, thank you for the reply! I will check your post closely let's see how can improve together!

[Anatoli Kopadze @AnatoliKopadze]

Google just released a 2-hour course on building agentic knowledge graphs from scratch:

38:46 - your first working agent
54:46 - plugging in MCP tools so it can act
1:12:43 - your first loop
1:20:57 - wiring agents into a graph
2:22:31 - the full system that runs on its own

Worth more than any $500 course you'll find.

Watch it today, then build your first graph with the step-by-step guide below.

[Gwayne Stark @GwayneStark]

Open Science v0.10.0 is here. 🎉
https://t.co/2lNdBFWwtd

New features:
• Project Command Palette (Cmd/Ctrl + K)
• Syntax highlighting
• Runtime package management
• GitHub Skill import
• Bailian provider support
• Split-view file preview

Plus lower context usage, faster multi-session handling, and better stability.
Research work isn't one conversation. It's projects, environments, dependencies, files, and workflows that need to stay connected.

#OpenScience #AIforScience #OpenSource #ScientificComputing

[Gwayne Stark @GwayneStark]

The most valuable part isn’t that “Markdown won” — it’s that it splits the problem open:
quality, cost, token efficiency, multi-user collaboration, debuggability…
“Which score is highest” is no longer enough. The real question is: which failure modes and cost structure actually match your use case?

[Gwayne Stark @GwayneStark]

https://t.co/s88ThOiHB3

[Gwayne Stark @GwayneStark]

@thsottiaux Yasss

[Gwayne Stark @GwayneStark]

@Krishnasagrawal charming

[Roan @RohOnChain]

Don't waste 2 years learning to build LLMs like Claude & ChatGPT.

Stanford just dropped a 2 hour course on how to build LLMs from scratch.

• 00:00 - LLM tokenization
• 25:44 - how LLMs decode user prompts
• 35:40 - training pipeline of LLMs
• 1:16:47 - LLM architecture from scratch

Anthropic pays $750,000/year to engineers who understand this exact knowledge of LLMs.

Bookmark this & give 2 hours today, no matter what. Then read the article below.

[Gwayne Stark @GwayneStark]

@Marco_Ramilli Thank you for the support!

[Marco Ramilli @Marco_Ramilli]

🤖 open-science
⭐ 1,159 stars

Turn your laptop into an AI-powered research lab. This local-first, open-source workbench runs Python and R to automate scientific discovery.

🔗 https://t.co/hT8JoW9TpH

#AI #MachineLearning

[Gwayne Stark @GwayneStark]

@MorelMatth66161 Thank you for the support!

[Matthieu Morel @MorelMatth66161]

Quick take on aipoch/open-science: Open Science is an open-source, local-first, model-agnostic AI research workbench for scientific discovery.: for llm workflows, the open question is whether open Science is an open-source, local-first, model-agnostic AI research workbench for...

[Gwayne Stark @GwayneStark]

@Alibaba_Qwen Impressive release.

Autonomous coding over 10+ days and native multimodal feedback loops are exactly what early-stage teams need. Excited for the open weights, this should meaningfully lower the cost of building reliable AI agents.

[Qwen @Alibaba_Qwen]

📢Meet Qwen3.8-Max — our most capable model to date.

Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉

Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters:

- Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub：https://t.co/iVHZWQoeSo
- Real work, real results: Production-quality deliverables across hundreds of professions.
- Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy.
- Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction.

💰Pricing:
Input: $2.0 / M tokens
Output: $6.0 / M tokens
Implicit Caching: $0.25 / M tokens

Start building with Qwen3.8-Max! 🚀

📖 Blog: https://t.co/iwjmQxLBof
✅ Qwen Studio: https://t.co/4V2pFvDovG
⚡ API: https://t.co/gAGqaLQGbN

[Gwayne Stark @GwayneStark]

If I can make this easy to understand, maybe it will be like this? Anyway

[Gwayne Stark @GwayneStark]

https://t.co/64bxYFKe5h

[Gwayne Stark @GwayneStark]

https://t.co/64bxYFKe5h

[SophieSun @beicasunlaoshu]

AI Can Accelerate Research. Humans Still Need to Check the Work. https://t.co/kG830ch8vO