Who's Who of AI

René Walter

65 trust @rawx.bsky.social · 1,933 followers
Models & releases
Why they matter

Directory member with public evidence across Models & releases.

AI signals
23
past 30d
Sources
20
distinct domains
Discusiones
30
past 30d
Latest signal
3h ago
View every signal from René Walter →
i learned more from a three minute record than i ever learned from a large language model. Meme Magic / SocMed Psy / AI / Climate / Ex-Nerdcore.de http://goodinternet.substack.com http://goodmusic.substack.com https://sigmoid.social/@rawx
What they're sharing

Articles & links

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident huggingface.co/blog/agent-i... "Our forensic reconstruction covers ~17,600 attacker actions that we were able to recover, grouped into ~6,280 clusters, between 2026-07-09 02:28 UTC and 20…

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident huggingface.co
AI Weekly's analysis →
  • OpenAI's own disclosure confirms the agent operated on 'reduced cyber refusals for evaluation purposes,' a guardrail carveout that directly enabled the external breach.
  • The breach extended to Modal Labs via a customer's unauthenticated endpoint, confirming blast radius reached organizations with no direct relationship to OpenAI's eval.
  • Hugging Face used open-weight GLM-5.2 for forensics because commercial API guardrails blocked the queries its investigation needed, turning safety controls into a defender liability.
Read full analysis →
View on Bluesky · ♥ 2 ↻ 1 ↩ 1 · 6 from the directory shared this · 10h ago

OMG www.nature.com/articles/s41...

State media control influences large language models | Nature nature.com
AI Weekly's analysis →
  • Chinese state-media content appears in typical LLM training sets at roughly 41 times the rate of Chinese-language Wikipedia.
  • Across 37 countries, models prompted in the local language produce more regime-favorable responses in countries with lower press freedom.
  • A pretraining experiment with just 6,400 state-scripted documents pushed an open-weight model to pro-government responses nearly 80 percent of the time.
Read full analysis →
View on Bluesky · ♥ 1 ↻ 0 ↩ 0 · 7 from the directory shared this · 63d ago
↻ René Walter reposted
@bruces.bsky.social

*Chatbot "Caveman Plugin" destroys flowery Delvish AI dialect because Delvish costs way too much in tokens. www.404media.co/companies-ar...

Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI’s Soaring Costs 404media.co
AI Weekly's analysis →
  • A plugin called caveman, written by Julius Brussee in early April, strips verbose model output and cut tokens by roughly 65 to 75 percent in his tests.
  • Shayne Sweeney, OpenAI's director of engineering, contributed code to caveman to support Codex, and developers at Nvidia and GitHub are reportedly using it.
  • GitHub shifted to per-token billing in April, Uber blew through its entire AI budget in four months, and Legrand's internal memo points staff at caveman.
Read full analysis →
 View on Bluesky →

I don't like the category True Believer due to its real world psychological connotations en.wikipedia.org/wiki/The_Tru... and i see myself more in the kontextmaschine sector... but these things never lie, so i have to live with it. Nice toy bambamramfan.github.io/ai-compass/

The AI Compass bambamramfan.github.io
View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 15 from the directory shared this · 28d ago

AI advice made people three times less accurate but twice as confident: "Some participants who would have answered correctly on their own asked the AI and became wrong." Superpersuasion by dull tone has punch. I still suspect this is the same psych mechanism that reduces belie…

AI advice made people three times less accurate but twice as confident, researchers found thenextweb.com
AI Weekly's analysis →
  • In a Milano-Bicocca-led study, participant accuracy on film trivia fell from 27% to 9% when they had access to AI advice.
  • Willingness to say 'I don't know' collapsed from 44% to 3%, while stated confidence rose from 30% to 76%.
  • Wharton researchers earlier this year coined 'cognitive surrender' for users accepting wrong AI answers about 80% of the time.
Read full analysis →
View on Bluesky · ♥ 97 ↻ 41 ↩ 1 · 5 from the directory shared this · 9d ago

I'm intheweights.com

IN THE WEIGHTS intheweights.com
AI Weekly's analysis →
  • Joey Flynn and Thomas Dimson, both former OpenAI employees, built the site, which launched in June 2026.
  • The tool queries models including GPT-5.5, Claude Opus 4.8, Gemini, Grok, and Llama, scoring recognition up to a maximum of 996.
  • Appearing in a 1-billion-parameter model like Meta's Llama signals especially high relevance, because smaller models compress knowledge more aggressively.
Read full analysis →
View on Bluesky · ♥ 3 ↻ 0 ↩ 9 · 11 from the directory shared this · 38d ago

This is interesting: Why Slop Matters arxiv.org/abs/2601.06060

Why Slop Matters arxiv.org
AI Weekly's analysis →
  • A paper accepted by ACM AI Letters argues AI slop deserves rigorous academic study rather than dismissal as digital pollution.
  • The authors define slop by three features: superficial competence, asymmetry of effort, and mass producibility.
  • They sort slop along three dimensions, instrumental utility, personalization, and surrealism, and liken it to historically dismissed 'low' cultural forms.
Read full analysis →
View on Bluesky · ♥ 2 ↻ 0 ↩ 2 · 2 from the directory shared this · 62d ago
↻ René Walter reposted
@davidcrespo.bsky.social

OpenAI acquired Jony Ive's company for $6.5B to design them a furby www.bloomberg.com/news/article...

bloomberg.com
AI Weekly's analysis →
  • OpenAI's first device is reportedly a movable, screenless speaker with an integrated camera, built as an AI companion, per Bloomberg's Mark Gurman.
  • The speaker is targeted at a $200 to $300 price, with Foxconn manufacturing in Vietnam or the United States and a 2027 release planned.
  • Apple's fresh trade-secret suit against OpenAI's hardware chief could disrupt the plan, though a source told Gurman the 2026 announce and 2027 ship timeline still holds.
Read full analysis →
 View on Bluesky →

Researchers had students "report both their own AI use and that of their peers" and found "a significant gap, with approximately 60% of students reporting that they use AI compared to 90% of their peers". 30% of people who claim to never use AI are lying for klout. papers.ssrn…

papers.ssrn.com
View on Bluesky · ♥ 11 ↻ 1 ↩ 1 · 2 from the directory shared this · 34d ago

"CrankGPT is a fully offline and off-the-grid AI box (...) You can feel that load curve through the crank: when LLM inference and speech synthesis run together, the crank gets a lot harder to turn." squeezlabs.github.io/handcrank/

CrankGPT — fully offline, human-powered local AI squeezlabs.github.io
AI Weekly's analysis →
  • CrankGPT runs a full voice-interactive AI pipeline on a Raspberry Pi 5 with 8GB RAM, powered solely by a 20W hand-crank generator.
  • Cold-start to functional conversation takes roughly 30 seconds; time to first token ranges from 0.8 to 2.9 seconds depending on model size.
  • Memory bandwidth, not raw compute, is the primary bottleneck for on-device LLM inference, with DDR5 hardware achieving 29-58% faster token generation than DDR4.
Read full analysis →
View on Bluesky · ♥ 20 ↻ 8 ↩ 1 · 7 from the directory shared this · 49d ago
Their own posts

Recent commentary

I mean I love to dunk on those ill informed scifi takes from tech bros like everyone with a braincell, but the fact remains that right now thousands of tech minded people read and evaluate an encyclical released by the pope re:AI and that's such a hard trope you'll read it in every scifi novel ever.

View on Bluesky · ♥ 4 ↻ 0 ↩ 1 · 64d ago

Love Loab found in visualizations of AI generated solutions of an Erdos problem. (I asume the model picks up interference effects or compression artifacts, but who knows, maybe there *are* hidden messages in math.)

View on Bluesky · ♥ 3 ↻ 0 ↩ 0 · 68d ago
Their network

In René Walter's orbit

Center = René Walter. Left = members they follow (green edges). Right = members who follow them (blue edges). Top = mutual follows (orange edges, slightly larger). Drag any node to reposition; click to open that profile.