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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Showing signals surfaced by Evangelos Kazakos ×

What is moving across the network now

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

Developing AI research Research 1d ago
⚡ 24 h early
AutoCompass visual localization paper

AutoCompass: Accurate Visual Localization on Public Maps by Learning from Weak Labels

2 directory members surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Eric Brachmann
“New #ECCV2026 paper alert: 🧭 AutoCompass: Accurate Visual Localization on Public Maps by Learning from Weak Labels 🧭 Paper: arxiv.org/abs/2609.02798 Website: nianticspatial.github.io/autocompass/ Video: www.youtube.com/watch?v=hmUF...” evidence ↗
2 experts 1 community 3 sources clustered

“New #ECCV2026 paper alert: 🧭 AutoCompass: Accurate Visual Localization on Public Maps by Learning from Weak Labels 🧭 Paper: arxiv.org/abs/2609.02798 Website: nianticspatial.github.io/autocompass/ Video: www.youtube.com/watch?v=hmUF...”

Established Models & releases Research 5d ago
⚡ 2210 h early
VLM suppresses female representation paper

Vision-Language Models Suppress Female Representations Under Ambiguous Input

2 directory members surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · AI Firehose
“Research shows vision-language models (VLMs) default to male in ambiguous images, outputting male for female jobs. While alignment improves outputs, it masks encoded biases, raising fairness issues in AI applications. https://arxiv.org/abs/2605.31556” evidence ↗
2 experts 2 communities 1 sources clustered

“Research shows vision-language models (VLMs) default to male in ambiguous images, outputting male for female jobs. While alignment improves outputs, it masks encoded biases, raising fairness issues in AI applications. https://arxiv.org/abs/2605.31556”

What experts are discussing without an anchoring article

2 experts · 3 posts · 2d ago
Matches Research & technical analysis
“This is why I work on data efficiency: to allow AI training for the long tail of SMEs and universities who don't have the huge resources. I don't believe AI will go away. Let's make training more a…” evidence ↗
Multiple readings Research & technical analysis · 1 Opportunity & adoption · 1
Evangelos Kazakos: Given everything that is going on, I’m more demotivated than ever to contribute to ‘AI’, whatever that term means. And no, currently I see literally zero benefits to society. AI for good is the sca…
jvgemert.bsky.social: This is why I work on data efficiency: to allow AI training for the long tail of SMEs and universities who don't have the huge resources. I don't believe AI will go away. Let's make training more a…
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