Working hypothesis: spend too much time with Americans and adopted that ‚yeah, it’s okay‘ attitude

As autistic German (having paperwork on both), I was surprised by the scoring. Or the test is broken

Danke! Hm, das hat mit dem claim „word fliegt raus“ aber nur lose zu tun. Steht da ja neben csv und json, was ja viel bedeuten kann

In dem Dokument geht es um KI- und allg. Developer-Infrastruktur. Zu Office-Dateiformaten steht da gar nichts drin.

“Humanity isn’t ready for that much software”
Very true. I’m not sure, where the new bottleneck is located. Currently trying to build nicer, beautiful things and make MVPs a bit less messy. But not really settled on the right way, yet

The public perception around this topic seems to shift. Slowly, but some hope exists that we will end up in a better position someday
ssir.org/articles/ent...

Seems plausible. Way 3 is feasible for small company/team to come up with a somewhat valuable dataset and pipeline that is specific and unique enough to provide value and get customers. More or less what I do

Yes, the models exist but their economic impact is yet very small

You also don’t emit any CO2 if you fly to the Maledives. The plane would go regardless of your ticket purchase

Make it a MCP server!

After all those years, the "data is the new oil" thing makes sense

Interesting, thanks for that. Selected more neutral scores, don’t see eg airborn precaution as my identity, but do it as a necessity

Movement Identity
Overall Identity Strength: 5.55 / 7
Airborne Health Identity
Overall Identity Strength: 5.75 / 7
Proactive Health Identity
Overall Identity Strength: 5.65 / 7
Cross-Domain:
Largest gap: Movement ↔ Airborne (0.20)

Provisional Pattern: Integrated Triad
Cross-domain convergence: 98%

🚀 Big news for TRL users with AI agents:

We just released the trl-training SKILL in TRL v0.29.0 🤗

Agents can now use the TRL CLI as a structured capability:

I see AI-forward teams spending a ton of time building bespoke tools to help them develop more effectively using agents (see: proliferation of CLIs to work with git worktrees), trying out different models, testing our new workflows.

The /llms.txt file – llms-txt A proposal to standardise on using an /llms.txt file to provide information to help LLMs use a website at inference time.

Would maybe add llms.txt here (llmstxt.org). Not specific to agents or discovery but imho a good way to serve up-to-date static content.

TreeWriter: AI-Assisted Hierarchical Planning and Writing for Long-Form Documents Long documents pose many challenges to current intelligent writing systems. These include maintaining consistency across sections, sustaining efficient planning and writing as documents become more co...

We’re excited to share a new preprint that may reshape how humans write -

TreeWriter: AI-Assisted Hierarchical Planning and Writing for Long-Form Documents 🌳

📃 arxiv.org/abs/2601.12740
Demo: drive.google.com/file/d/1R-X6...
Live demo: treer.ai

[1/5]

Abstractive Red-Teaming of Language Model Character ArXiv link for Abstractive Red-Teaming of Language Model Character

This study presents "abstractive red-teaming," a method for pre-deployment audits of language models, identifying problematic query categories causing character violations. This innovation improves model reliability by exposing risks like illegal behavior and sexism. https://arxiv.org/abs/2602.12318

Quantitative measures are always a dangerous yardstick. You can describe severe diarrhoea as "an explosion in bowel productivity", but you wouldn't say it correlates positively with gut health.

unsloth/Nemotron-3-Nano-30B-A3B-GGUF · Hugging Face We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Nemotron3 nano is a solid choice: huggingface.co/unsloth/Nemo...
Running it with 2x 3090 and OpenCode for local stuff.

Think of Alex and Palantir what ever you want; this is probably the best 3D-chess move you could make...

AI use-cases - a dwablimol Collection A collection of datasets that describes various use cases of AI in enterprise and other settings.

Started a collection of LLM use-case dataset on HF. Key entrances: the super cool ZenML LLMOps use-case database and Anthropic's new interview dataset. Details below, any other things to include?
huggingface.co/collections/...

How Emmy Award–winning filmmakers use AI to automate the tedious parts of documentaries YouTube video by How I AI

One of the few examples of how to use AI tools in a creative process that's fully curative instead of generative. Describing images, OCRing documents and make it searchable. www.youtube.com/watch?v=9ngb...

Fenster hoffentlich alle vorsorglich vermauert um Haftungsrisiko zu minimieren

“Hacke” is quite universal used for all hand tools that help loosen the soil; very general term. “Queraxt“ is a term I loosely remember from 19th century narratives, but it’s very uncommon in today’s gardening practice.

Yeah, would have problems to name all the tools properly in German

Learning/speaking English now for ~30y and feeling quite comfortable with it. The density of new words in a single post is just insane. Need to level up my gardening game

Classrooms as cluster-mixing machines because of poor air? Color me surprised. </s>

This Nat. Comm. study found: In schools, it is not only direct contact, mainly the “shared classroom exposure.” Poor air quality increases the risk exponentially.
www.nature.com/articles/s41...

"Nobody wanted to do this work": How Emmy-award-winning filmmakers use AI to automate the tedious parts of documentaries Listen now | 🎙️ How AI transformed Ken Burns' documentary team's production process

Es gibt auch ein paar unaufgeregte Berichte aus den eher kreativen Bereichen, wie man Nutzen jenseits der sloppy Bilder/Filme/Musik ziehen kann

www.lennysnewsletter.com/p/nobody-wan...

Für bestimmte Themen gibt es schon gute Ideen, zB Jeremy Howards solveit

www.answer.ai/posts/2025-1...

Die Adoption und Adaption ist viel langsamer als von der Hype-Bubble angenommen, wenn die Nützlichkeit echt ist, wird sie aber kommen.