ask_know

[ask_know @Ydf_189]

@net_termina Great! Thank you so much for the time and the explanation!🫡

[ask_know @Ydf_189]

@net_termina May I ask which model you used to guide you through every step?

[ask_know @Ydf_189]

@QwenDevs @ddalcu Thanks for not letting my rtx 3090 become obsolete & useless❤️

[ask_know @Ydf_189]

@freeCodeCamp @manishmshiva I am very grateful that also the concpets of AI are discussed, not just the technical aspects and applications.

[ask_know @Ydf_189]

@xiong_hui_chen 感谢Qwen哥们儿要发布27b

[ask_know @Ydf_189]

@Alibaba_Qwen 为了开源地发布27b 太谢谢���们拉。

[ask_know @Ydf_189]

@UnslothAI @Kimi_Moonshot Ship this: --> Kimi_K3_3T_Q_0.0001_K GGUF. This is the only quant my single RTX 3090 can run, lol.

[Ahmad @TheAhmadOsman]

Please DON'T DO this

This is a waste of money given how outdated both the software and the hardware are

[ask_know @Ydf_189]

To my humble opinion, one of the rare contributions that shows real soul💪🦾, not today, but the day anthropic's behavior became public. "AI as civilizational infrastructure" is the vocabulary unique to its author.

[Ahmad @TheAhmadOsman]

Anthropic wants the public to see one thing: the careful lab, the safety lab, the grown-up in the room trying to keep frontier AI from running off a cliff. However, the pattern around Anthropic does not look like caution by itself. It looks like a company wrapping a business model in moral language, then using that language to justify opaque model behavior, anti-competitive access rules, regulatory pressure, and a future where builders, startups, researchers, and Opensource communities stay downstream of a few blessed frontier labs.

Imagine a compiler that emits worse binaries when it thinks you are building a competing compiler. Imagine a microscope that blurs certain samples because the manufacturer dislikes the research direction. Imagine a debugger that lies only when your codebase resembles a future rival.

Anthropic can learn from the internet, copyrighted books, code, public knowledge, user feedback if permitted, synthetic data, and its own models. But if a developer uses Claude to bootstrap a competitive open assistant, Anthropic calls foul. The company argues that safety controls may be lost and that competing models undermine the investment required to build frontier systems.

The fight is whether intelligence becomes something people can own, inspect, modify, run locally, fine-tune, study, route, and improve, or whether it becomes a subscription permission layer run by companies that can refuse, degrade, surveil, retain, revoke, reroute, or lobby away your access.

Anthropic's moat is being a permission regime. On daily basis, competitors and acquisition targets discover that access can disappear. The company asks governments to bless safety frameworks, deployment gates, incident reporting, evaluation regimes, and even future pauses that incumbents are best positioned to survive.

If a coding or research model secretly changes the quality, direction, or reliability of an answer because it classified the user as doing disallowed frontier work, the tool is no longer merely "safe." It is untrustworthy.

If Anthropic wants to be treated like a public-interest safety institution, it cannot behave like a hypersensitive platform monopolist whenever a customer gets too close to building alternatives.

Yes, companies protect their IP. But Anthropic is not selling a normal SaaS widget. It is selling cognition as infrastructure. Once cognition becomes infrastructure, anti-competitive access control stops being a normal vendor dispute and becomes a social bottleneck.

Anthropic repeatedly converts safety, security, and responsible deployment into mechanisms of control over who may build and what could be built.

We cannot trust them.

[ask_know @Ydf_189]

@TheAhmadOsman A nice move by openai and anthropic now would be opensourcing gpt 4.5, and Claude Sonnet 4.5.

[ask_know @Ydf_189]

@MaxForAI @Alibaba_Qwen 这我不管，重要是他们会发布Qwen 3.8 27B, 我只有一个RTX3090🫠

[ask_know @Ydf_189]

@mervenoyann @TheAhmadOsman @MikeBradleyAI @alexocheema I enjoyed it a lot! Thanks for the initiative!🙏

[ask_know @Ydf_189]

@TheAhmadOsman @huggingface @mervenoyann @MikeBradleyAI Thanks, I loved it! I run ODS for a while on my single RTX 3090, and play with it often. It's still overwhelming for me as a beginner, but I'm happy that I've been able to use the chat, hermes & try a voice model. It doesn't allow me to use Qwen 3.6 35B, but I can live with it.

[ask_know @Ydf_189]

@poolsideai Great, it is never late!

[Mike Bradley @MikeBradleyAI]

@DaveShapi Open models :
1. Massively increase innovation
2. Decrease costs of experimentation
3. Create a much larger AI economy
4. Democratize intelligence
5. Improve competition
6. Accelerate hardware investments
7. Accelerate scientific progress
8. Reduce bottlenecks

[ask_know @Ydf_189]

@siliconvalleymm @drfeifei Great points, thank you for the summary!🙏

[ask_know @Ydf_189]

@Alibaba_Qwen A huge number of researcher have limited number of GPU for local testing. Releasing a 27b version is much appreciated🫰🤝

[Hugging Face @huggingface]

Join us this Tuesday to learn more on Local AI, from software to hardware 🤗

We'll be joined by @TheAhmadOsman & @MikeBradleyAI covering hardware setups & local inference with live demo, and @alexocheema & @0xSero on picking model for your hardware, model compression and REAPs 🔥

Set your reminders to not miss out! 🔔

[Nader Khalil🍊 @NaderLikeLadder]

Open source creates the necessary environment for competition

Without competition, only incumbents have power.

We saw this first happen with Stable Diffusion.
Open AI released Dall-E. In the name of safety it would not render faces and it was extremely limited via waitlist. I only got access because I was a YC founder.

Then Stable Diffusion came out. It rendered faces. No wait list. Simply download the model and run it on your hardware.

In response to this competitive pressure, open AI released DALL-E 2. No waitlist. Renders faces, added in painting, etc

Same thing happened with reasoning models. OpenAI had o1, which at the time, seemed to give OpenAI an insurmountable advantage over everyone else.
Deepseek released a reasoning model, open weights, which led to a proliferation of reasoning models coming from research labs.

Same pattern again with Mythos and Fable.
Closed model, extremely limited. This time worse, because of nonsensical fear-mongering.
GLM 5.2, Kimi K3 both get released. Frontier Intelligence, open weights.

But now the calculus is different:
The fearmongering has inspired distrust in the closed-source model labs. If we can't trust continued access to the tools then why would we learn to use them? Closed source labs open sourcing harnesses is a great way to build trust.

The ecosystem is only healthy when we have both. Competition is crucial to keep the ecosystem fair. Open source is necessary for competition.

[ask_know @Ydf_189]

@simonw There is no ChatGPT Work anymore. They rolled the name back to Codex.