Who's Who of AI

Martin Trapp

179 trust researcher @trappmartin.bsky.social · 2,912 followers
AI research Culture, work & education
Why they matter

Researcher with public evidence across AI research, Culture, work & education.

AI signals
7
past 30d
Sources
6
distinct domains
Discusiones
7
past 30d
Latest signal
2d ago
View every signal from Martin Trapp →
Assistant Prof in Prob ML @ KTH 🇸🇪 WASP Fellow & ELLIS Member Ex: Aalto Uni 🇫🇮, TU Graz 🇦🇹, originally 🇩🇪. — https://trappmartin.github.io/ — Reliable ML | UQ | Bayesian DL | tractability & PCs
What they're sharing

Articles & links

↻ Martin Trapp reposted
Timnit Gebru @timnitgebru.blacksky.app

I'm not sure if y'all saw a CNN report on how the US had almost started WW3 with China based on fabricated information generated by a chatbot, claiming that a Chinese vessel was carrying components of nuclear weapons. That was an "existential threat" to humanity www.theguardia…

Forget ‘superintelligence’: error-prone AI nearly sparked world war three this month | Timnit Gebru and Emily M Bender theguardian.com
AI Weekly's analysis →
  • A US special operations analyst used a chatbot to assess intel on a Chinese ship, and the AI falsely claimed it carried nuclear weapon components.
  • Military planes were in the air and personnel were preparing to board before officials caught the hallucination and stood down, per CNN sources.
  • Gebru and Bender argue the real AI risk is error-prone deployment in high-stakes settings today, not speculative superintelligence.
Read full analysis →
 View on Bluesky →
↻ Martin Trapp reposted
Pierre Alquier @pierrealquier.bsky.social

The proceedings of ICML 2026 are online, including a position paper I took part to: proceedings.mlr.press/v306/papamar... The 29 other authors did all the work 😅 but I'm still proud to share it. Also I "officially" become a co-author of so many people I like a lot, this makes …

Position: Agentic AI Orchestration Should Be Bayes-Consistent proceedings.mlr.press
AI Weekly's analysis →
  • A 30-author ICML position paper argues Bayesian decision theory belongs in the orchestration layer of agentic AI, not inside the LLMs themselves.
  • The authors call making LLMs internally Bayesian 'computationally intensive and conceptually nontrivial as a general modeling target'.
  • They pitch calibrated beliefs and utility-aware policies for choices like which tool to call, which expert to consult, and how many resources to invest.
Read full analysis →
 View on Bluesky →
↻ Martin Trapp reposted
David Picard @davidpicard.eurosky.social

The E.T.👽 workshop submission is finally open! We aim at promoting scientific theory building in deep representation learning 2 tracks: 1p storyline & regular 14p full paper Deadline: Aug 1st 🖥️ empiricaltheory.github.io 📜 openreview.net/group?id=the... Let's do science! @eccv…

ECCV 2026 Workshop ET | OpenReview openreview.net View on Bluesky →

Are you interested in uncertainties, reliable decision-making in ML, or probabilistic perspectives on model compression, and would like to work together? DigitalFutures currently has an open call for postdoc fellowship applications: www.digitalfutures.kth.se/call/up-to-t...

Home - Martin Trapp trappmartin.github.io
View on Bluesky · ♥ 11 ↻ 3 ↩ 1 · 2 from the directory shared this · 99d ago
Their own posts

Recent commentary

I wonder how others feel about this. My impression is that it is increasingly hard to say, in double-blind reviewing, how “good” a paper is. Strangely, I think the credibility of an author (do I know this person and think she/he does good work) is an indicator that gained more importance with LLMs.

View on Bluesky · ♥ 15 ↻ 0 ↩ 5 · 101d ago

LLMs are somehow really good at telling you stuff you already know, but in a different, convoluted way, making it look really smart. Almost like replies by users on Reddit. …wait 🧐

View on Bluesky · ♥ 10 ↻ 0 ↩ 0 · 23d ago

Excited for the WASP(-HS) workshop on Bias, Representation and Transparency in generative models!

View on Bluesky · ♥ 0 ↻ 0 ↩ 0 · 39d ago
Their network

In Martin Trapp's orbit

Center = Martin Trapp. 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.

Are you Martin Trapp? Show it.

Add the Who’s Who of AI badge to your site or bio. It links back to this profile.

Listed in AI Weekly's Who's Who of AI

Markdown: [![Listed in AI Weekly's Who's Who of AI](https://aiweekly.co/modules/custom/aiweekly_whoswho/images/whoswho-badge.svg)](https://aiweekly.co/whos-who/person/trappmartin-bsky-social)