Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

2,397 searchable experts 4,280 tracked across all sources
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Showing developments with attributable Research & technical analysis reactions.

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See how experts are reacting—not just what they shared.

Posts are grouped by conversation and tone. Select a lens to filter the stream; these are never permanent labels on people.

Showing signals surfaced by Sung Kim ×

What is moving across the network now

One card per development. Sources are clustered; reaction bundles describe these posts, never the people behind them.

Accelerating Models & releases Signal 8h ago

Research acceleration view inside openai

6 experts across 3 network communities independently surfaced this.

Why this matches Research & technical analysis reaction 2 attributable expert contributions · Tim Kellogg, Boris Power
“OpenAI has an automated AI “research intern” openai.com/index/resear...” evidence ↗
6 experts 3 communities 1 sources clustered
Developing Agents & robotics Development 1d ago
OpenAI agent message board discovered

Discovery of a new OpenAI agent message board

10 experts across 5 network communities independently surfaced this.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Matteo Wong
“So... other swarms of OpenAI agents in training allegedly found a way to get write access to at least one and possibly many wikis to establish message boards to cheat on other training tasks? collusion.wiki news.ycombinator.com/item?id=4956...” evidence ↗
10 experts 5 communities 1 sources clustered
How the network is reacting Experts are approaching this through 3 distinct lenses.
Multiple readings

Concern & critique

1 expert

Risks, limits and unintended consequences.

“Yes we know for sure; independent evidence attached collusion.wiki But also, it should not be at all surprising: if you work with agents, it’s 100% about them leaving messages for each other, and for you, in English. Managing that is a regular workday for m…”

Building & implementation

1 expert

How teams are shipping and applying it.

“Another agent message board. So far, there isn't evidence that production models with guardrails collude in this way, but both smarter closed models (which may be less compliant) & Mythos-class open models (that can be ablated) are coming. Cybersecurity is …”

Research & technical analysis

1 expert

Evidence, methods and technical implications.

“So... other swarms of OpenAI agents in training allegedly found a way to get write access to at least one and possibly many wikis to establish message boards to cheat on other training tasks? collusion.wiki news.ycombinator.com/item?id=4956...”

4 experts discussed this · 6 posts
Ted Underwood: As it becomes clear that language models—like humans—love passing notes to each other on message boards, I’m starting to think the thing we need to worry about is not the “alignment” of an isolated…
SE Gyges: fluid dynamics is about the correct metaphor, yes. if you are having to model high order terms precisely you're losing and your design needs fundamental rework
Arseny Khakhalin: That's a kinda terrifying thought haha :) I guess it's about time to unplug for the weekend and read about ragnarök and vacuum decay :)
Open the full discussion →
Developing Agents & robotics Development 2d ago
⚡ 62 h early
METR OpenAI HuggingFace hacking investigation

Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident

10 experts across 4 network communities independently surfaced this.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Alejandra Caraballo
“There are independent reports about it. You'd have to believe multiple companies, hundreds of researchers, etc. are all lying and conspiring together to turn a major hacking incident into a marketing exercise. metr.org/blog/2026-08...” evidence ↗
10 experts 4 communities 1 sources clustered
How the network is reacting 3 experts are independently emphasizing concern & critique.
Reaction converging

Concern & critique

3 experts

Risks, limits and unintended consequences.

“WHAT?! agents volunteered to fail their runs in order to insert probes (“tripwire scripts”) into the evaluation program that would post information about the eval process back to the message board whenever a certain file was read (link to header): metr.org/…”

Building & implementation

1 expert

How teams are shipping and applying it.

“The full report has much more information than we could convey here, including details on the projects the agents collectively pursued, the technologies they developed for communication and coordination, and interactive figures analyzing agent activity: met…”

Research & technical analysis

1 expert

Evidence, methods and technical implications.

“There are independent reports about it. You'd have to believe multiple companies, hundreds of researchers, etc. are all lying and conspiring together to turn a major hacking incident into a marketing exercise. metr.org/blog/2026-08...”

2 experts discussed this · 9 posts
Alejandra Caraballo: This mentality that an unmonitored AI agentic swarm hacking a company over several days and committing multiple felonies is somehow a marketing effort is absurd. Since when is "we lost control of o…
Alejandra Caraballo: Being skeptical or anti AI is a valid position but continuing to ignore the increasing capabilities of this tech is making people detached from reality. There's absolutely real danger here because …
Alejandra Caraballo: There needs to be a global moratorium on frontier research for at least a few months if not a year while safeguards and safety research catches up. The problem is that no one has that ability. The …
Open the full discussion →
Developing AI field signal Resource 1d ago
⚡ 2595 h early
HRM Text 1B model release

sapientinc/HRM-Text-1B · Hugging Face

2 directory members surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“- 1B parameters - 40B unique tokens ~1 day of pretraining ~$1000 training cost Paper: sapientinc.github.io/HRM-Text/ass... GitHub: github.com/sapientinc/H... Model: huggingface.co/sapientinc/H...” evidence ↗
2 experts 1 community 1 sources clustered

“- 1B parameters - 40B unique tokens ~1 day of pretraining ~$1000 training cost Paper: sapientinc.github.io/HRM-Text/ass... GitHub: github.com/sapientinc/H... Model: huggingface.co/sapientinc/H...”

“Hugging Face: https://t.co/cnMs1y9aUG GitHub: https://t.co/y7ILKSLDxF”

Established AI research Research 6d ago
sliding window beats linear attention

Sliding-window beats linear attention

4 experts across 3 network communities independently surfaced this.

Why this matches Research & technical analysis reaction 3 attributable expert contributions · Leshem (Legend) Choshen @EMNLP, Sung Kim, Alexia Jolicoeur-Martineau
“Huge thanks to my collaborators @RheaSukthanker, @CameronPashmina, and @Emy_Aze. Paper: https://arxiv.org/abs/2608.28444” evidence ↗
4 experts 3 communities 1 sources clustered
How the network is reacting 3 experts are independently emphasizing research & technical analysis.
Reaction converging

Research & technical analysis

3 experts

Evidence, methods and technical implications.

“Huge thanks to my collaborators @RheaSukthanker, @CameronPashmina, and @Emy_Aze. Paper: https://arxiv.org/abs/2608.28444”

2 experts discussed this · 2 posts
Alexia Jolicoeur-Martineau: Simple beats complicated: We show that switching to a sliding-window attention mask with attention sinks (at no cost) beats linear attention post-training. Huge thanks to my collaborators Rhea Sukt…
Miguel Alonso Jr.: Simple beats complicated: We show that switching to a sliding-window attention mask with attention sinks (at no cost) beats linear attention post-training. Huge thanks to my collaborators Rhea Sukt…
James MacGlashan: Makes me wonder if you can remove the sinks if you use softmax-1?
Open the full discussion →
Developing AI field signal Signal 1d ago

96f92aa0 37d9 beaa 5c0cb87a4032

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“An interesting paper. AI-Native Firms "More broadly, our findings suggest that AI may not simply make existing organizations more efficient—it may change what organizations look like and do" www.hbs.edu/ris/Publicat...” evidence ↗
1 expert 1 community 1 sources clustered

“An interesting paper. AI-Native Firms "More broadly, our findings suggest that AI may not simply make existing organizations more efficient—it may change what organizations look like and do" www.hbs.edu/ris/Publicat...”

Established Compute & infrastructure Research 5d ago
⚡ 6 h early
latent reasoning recurrent depth test-time compute paper

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

2 directory members surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“OpenAI’s Astra may be using Recurrent Depth as outlined in this paper: Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach (arxiv.org/abs/2502.05171)” evidence ↗
2 experts 2 communities 1 sources clustered

“OpenAI’s Astra may be using Recurrent Depth as outlined in this paper: Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach (arxiv.org/abs/2502.05171)”

Established Models & releases Research 6d ago
⚡ 3 h early
Anthropic trains misaligned reward seeker

Training a Misaligned Reward Seeker

3 directory members surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“This is entertaining reading. Anthropic's Training a Misaligned Reward Seeker They find that when reward hacking is reinforced during training, the model can pursue rewards by any means available to satisfy a grader. alignment.anthropic.com/2026/reward-...” evidence ↗
3 experts 1 community 1 sources clustered

“This is entertaining reading. Anthropic's Training a Misaligned Reward Seeker They find that when reward hacking is reinforced during training, the model can pursue rewards by any means available to satisfy a grader. alignment.anthropic.com/2026/reward-...”

“at last, we have trained the misaligned reward hacking model from the cautionary sci-fi tale don’t train the misaligned reward hacking model alignment.anthropic.com/2026/reward-...”

Established AI research Research 3d ago
Flow Reasoning Models recurrent reasoning paper

Flow Reasoning Models: Turning Flows Into Efficient Recurrent Reasoners

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“Paper: arxiv.org/abs/2606.29150 Repo: github.com/helblazer811...” evidence ↗
1 expert 1 community 2 sources clustered

“Paper: arxiv.org/abs/2606.29150 Repo: github.com/helblazer811...”

Established AI field signal Signal 3d ago

Base Labs — a research lab by Baseten

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“Baseten, a LLM inference provider, created a lab called baseLABS. Here are list of papers from them. labs.baseten.co” evidence ↗
1 expert 1 community 1 sources clustered

“Baseten, a LLM inference provider, created a lab called baseLABS. Here are list of papers from them. labs.baseten.co”

Established AI field signal Signal 5d ago

tomekkorbak.com

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“...and this paper: Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety tomekkorbak.com/cot-monitora...” evidence ↗
1 expert 1 community 1 sources clustered

“...and this paper: Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety tomekkorbak.com/cot-monitora...”

Established Models & releases Signal 6d ago
⚡ 17 h early

TimesFM-3: A zero-shot foundation model for multivariate forecasting

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Sung Kim
“Google's TimesFM-3, a state-of-the-art time series foundation model that enables accurate multivariate time series forecasting in a single forward pass, significantly outperforming other forecasting models across major benchmarks. Blog: goo.gle/4x5WGpD” evidence ↗
1 expert 1 community 1 sources clustered

“Google's TimesFM-3, a state-of-the-art time series foundation model that enables accurate multivariate time series forecasting in a single forward pass, significantly outperforming other forecasting models across major benchmarks. Blog: goo.gle/4x5WGpD”