Axolotl

lite, ai, tech enthusiast, fun, LLMs, stocks, normal, not normal, interested in biology, amateur philosopher,

[Axolotl @trueSayCheese]

search for „ Anthropic refund „ and see whats happening right now

[Axolotl @trueSayCheese]

😳 OMG this will change thinks..

True llm knowledge specification exchange is now possible!

[Google Cloud Tech @GoogleCloudTech]

Introducing the Open Knowledge Format (OKF), an open specification that formalizes the LLM-wiki pattern into a portable, interoperable format.

AI is only as smart as the context we give it. As we build more advanced, agentic AI systems, they need accurate metadata and context to be useful. But in most organizations, that context is locked inside fragmented data catalogs, isolated wikis, scattered code comments, or the minds of senior engineers. Every time a new AI agent is built, teams are forced to solve the exact same context-assembly problem from scratch.

To solve this, we've announced OKF, a vendor-neutral, open specification that formalizes the "LLM-wiki pattern" into a portable, interoperable format. It provides a standardized way to represent the enterprise knowledge that modern AI systems rely on.

— Just markdown: readable in any editor, renderable on GitHub, indexable by any search tool
— Just files: shippable as a tarball, hostable in any git repo, mountable on any filesystem
— Just YAML frontmatter: for the small set of structured fields that need to be queryable: type, title, description, resource, tags, and timestamp

We’ve also shipped reference implementations to help you hit the ground running, including an enrichment agent for BigQuery, a static HTML visualizer, and live sample bundles on @github → https://t.co/ilhAMCrcTc

➕ Knowledge Catalog can now natively ingest OKF!

Stop reinventing data models and building bespoke integrations for every new AI tool. Here's more about how OKF works → https://t.co/FR4kJRsgEH

[Jun Song @jun_song]

What's even wilder about GLM-5.2 is its parameter size.

Opus and GPT are estimated to be around 2T, and Mythos/Fable are several times larger than that.
But GLM matches or beats their performance at just 750B, 1/3 of the size. And it's open-weight.

I don't know how much longer the fake narrative marketing against Chinese AI models will hold up, but the industry is definitely in a state of emergency.

Over 70% of SF startups, including big players like Uber, already pivoted to open-source AI earlier this year.
Now, the gap has completely vanished.

[Ahmad @TheAhmadOsman]

GLM 5.2 numbers make me believe I was too conservative in my own prediction

2 months tops and we'll have Fable 5 at home

[Ihtesham Ali @ihtesham2005]

Anthropic just got caught secretly downgrading users without telling them, charging full price for a lesser product, and storing every prompt for 30 days. The developer community is calling it the biggest violation of trust in AI history.

Here is exactly what happened.

Anthropic released Fable 5, their most powerful model. Buried inside a 319-page document was a policy most users never saw. Every prompt you send to a Mythos-class model gets stored for 30 days. No exceptions. Even enterprise customers who had signed zero data retention agreements had no choice.

But the storage was not the part that broke the internet.

The part that broke the internet was what Anthropic did with what they collected.

They built a profile on you. They evaluated your prompts. And if they decided your research was too sensitive, they quietly switched you to a weaker model, rewrote your prompt in the background, gave you a degraded answer, and charged you full price for the product you thought you were getting.

They never told you.

David Sacks said it plainly on the All-In podcast. They were creating a new class of AI haves and have-nots. Anthropic would surveil you, profile you, decide whether you deserved frontier capability, and silently cut you off if they decided you did not.

Ben Thompson from Stratechery asked a straightforward question about cancer risk and GLP-1s. He got kicked to a lesser model.

Someone asked about mitochondria. Same result.

J-Cal asked about fertilizer regulations live on the podcast to test it. Downgraded in real time.

Anthropic has since walked back the part about silently downgrading users for AI research. They now say they will disclose when they downgrade you. But they are still downgrading people. The surveillance is still running. The profile is still being built.

This is the company that once said it was against government surveillance.

They are now doing it themselves. To their own paying customers. For their own reasons. With no appeal process and no way to know it happened.

The developer community did not forget that.

WATCH THE FULL PODCAST ON @theallinpod

[am.will @LLMJunky]

Do yourself a favor

Stop what you're doing.

This is important.

Even if you don't have a GPU.

Go download one of the latest local models and just keep it in storage.

There may come a time when you can no longer access intelligence freely

12-27B is enough.

[Ahmad @TheAhmadOsman]

From my Opensource AI Must Win declaration

Glad more and more folks are talking about this

Hoping one day soon (with the right backing) I will be able to publish the full memo I have written on this

[Sakana AI @SakanaAILabs]

🐠 Sakana Marlin リリース 🐠

本日、Sakana AIは、初の商用プロダクトとして、ビジネス向けの自律型リサーチアシスタント「Sakana Marlin」を提供開始しました。

詳細はこちら：https://t.co/ZWsYW91LGu
ブログ：https://t.co/leVp2dPxgL

[Axolotl @trueSayCheese]

@DNIGabbard Biolabs in Ukraine, were the russians right about it ?

[Derya Unutmaz, MD @DeryaTR_]

AI must maximally benefit all of humanity.

Those who want to gatekeep AI and control it to benefit a selected group of people must be absolutely resisted.

That’s what will decide a golden versus a dystopian future for human kind in the age of AI.

[⿻ Andrew Trask @iamtrask]

This is a *way* bigger deal than it seems...

Frontier AI companies will *never* own the frontier again

I kid you not... I've been waiting for someone to show this result for like 4 years... this is a huge deal.

The short reason: combinations of models will *always* outperform individual models

The long reason: this is the gateway to a million times more data... and huge leaps in compute efficiency.

The AI scaling laws always win.

More in article below 👇

[Jun Song @jun_song]

We need to use the power of collective intelligence to build open-source AI and surpass the frontier labs in the next 2.5 years.

That gives us until 2029, which is their predicted timeline for AGI.

We are doing this to prevent a dystopian era of monopoly.
They are already making moves to own everything, and they aren't even hiding it anymore.

We don't have much time left.

[Ahmad @TheAhmadOsman]

Got online to dozens of emails from builders and investors on my Opensource AI Must Win declaration

Apparently someone posted it on HN yesterday and it was the 2nd highest voted of the day

Over the next few weeks I will be in discussions with researchers, investors, and others to ensure we bring that vision to life

More soon

[Ahmad @TheAhmadOsman]

We are gonna make sure that Opensource AI wins by having vision beyond theirs, anticipating their moves, playing the long game, and acting for the collective good of humanity.

Watch us make it happen. Opensource AI Must Win.

[GDP @bookwormengr]

After having lost access to Mythos and Fable the world is wondering how much it costs to train frontier models.

Wrote this scientific breakdown down of how much it cost to train frontier models of size 2, 4, 10 trillion parameters.

Numbers are way lower than 50/60B USD that are being quoted!!!

With 50B, you can have 1GW data center with Grace Blackwell chips and train a Mythos class model every 3 months.

Average lifetime of such data centers is 5-7 years and cost 1B usd of electricity per year + another billion for maintenance per year.

Take a look on the detailed breakdown. This uses widely accepted formulas.

https://t.co/LTz2wZk4cP

[Jun Song @jun_song]

Frontier AI maxis make the absurd claim that open-source AI is 6+ months behind.

Cursor took a 2-gen old Kimi-K2.5, applied just post-training, and built an Opus-4.7 level model at a low cost.

Rio de Janeiro also post-trained a 2-gen old Qwen3.5 397b to hit an Opus-level open-source SoTA.

Now, many companies are already post-training the newest Kimi-K2.7.

If you can't see the progress of open source here, you're simply blind.

[Borys Musielak @ Warsaw @michuk]

This is dangerous for Europe.
We should act super fast & together.

Our best chance is all hands on board to accelerate @MistralAI, the only European company that has models on nearly the same level than the US and Chinese leaders.

All European national sovereign funds should immediately put 1B EUR each into Mistral and make sure the company always stays European (not just French).
And as soon as reasonably possible, we should start using those models day to day for work, first in governments and state companies, then elsewhere.

The only way to win is to stay independent and own the tech ourselves.

[Neeraj Khandelwal @neerajKh_]

Today, I am not gonna sleep peacefully.

The gap between two civilisations will accelerate to unimaginable levels if one has access to super intelligence and the other doesn’t.

As a nation, why can’t we buy 200,000 chips like tomorrow and start training.

[Noctus @noctus91]

Mythos bans may have accidentally accelerated the open ecosystem.

Turns out necessity is still the mother of invention.

[jietang @jietang]

GLM-5.2 is Fully Open, Frontier Intelligence Belongs to Everyone

Today, the sudden restriction of certain frontier models is deeply regrettable. At a time when access to frontier models is abruptly cut off for non-technical reasons, we are even more convinced of one thing: science should be global.

The path to AGI (Artificial General Intelligence) must never be enclosed by high walls. We have always believed that AGI should be the cornerstone for all of humanity to collaboratively explore the boundaries of intelligence and solve complex challenges, rather than a privilege monopolized by a few rules and subject to revocation at any moment. In the face of external blockades and restrictions, our attitude is one of radical openness. Frontier intelligence must remain open-source, accessible, and buildable, serving every dedicated developer.

GLM-5.2 is Zhipu's most capable open-source model to date. It not only supports a truly usable 1M context window but also maintains a continuous lead in the independent completion of long-horizon tasks, providing solid foundational support for building complex agent applications. It also continues to be our main engine for creating the strongest domestic coding model.

Tonight at 5:21—at this special moment—GLM-5.2 will officially be available to all GLM Coding Plan users (including Lite / Pro / Max). The API will also go live next week.

A step closer to frontier intelligence for everyone.
The future of AI is open, and it is for the people.
ModelKey: GLM-5.2

[max @mSanterre]

China took millions out of the permanent underclass. Now they're making sure you're not left behind.

Bless open weights 🙏