Knowledge catalogue
arXiv:2605.07979v1 Announce Type: new Abstract: The rise of machine learning has shifted targeted resource allocation in policy and humanitarian settings toward algorithmic targeting based on predicte
arXiv:2605.07462v1 Announce Type: cross Abstract: Moltbook is a Reddit-like platform where OpenClaw agents post, comment, and vote at scale - a so far unprecedented incident that comes with serious sa
arXiv:2605.07409v1 Announce Type: new Abstract: Natural Language Processing is rapidly evolving into a primary instrument for Computational Social Science, with researchers increasingly using embeddin
arXiv:2605.07105v1 Announce Type: cross Abstract: Language model (LM) alignment improves model outputs to reflect human preferences while preserving the capabilities of the base model. The most common
arXiv:2605.07461v1 Announce Type: new Abstract: Rubrics have been extensively utilized for evaluating unverifiable, open-ended tasks, with recent research incorporating them into reward systems for re
Gary Marcus critiques the typical hype cycle pattern where emerging technologies experience inflated expectations followed by inevitable disappointment. The post likely illustrates this cycle using a
This post from AI researcher Gary Marcus likely discusses the enormous economic value or potential return on investment related to artificial intelligence developments, suggesting AI's worth or impact
arXiv:2605.07693v1 Announce Type: new Abstract: Geometric representation-conditioned molecule generation provides an effective paradigm that decouples molecule representation modeling from structure g
arXiv:2605.07049v1 Announce Type: cross Abstract: We present the first theoretical guarantees for differentially private online reinforcement learning (RL) with general function approximation, extendi
arXiv:2605.06891v1 Announce Type: new Abstract: Labeled datasets reflect the biases of their annotation pipelines, which sometimes introduce label bias: group-conditional label errors that cause syste
arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict
arXiv:2508.10016v3 Announce Type: replace Abstract: Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantia
arXiv:2605.06990v1 Announce Type: new Abstract: Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL
arXiv:2410.21438v3 Announce Type: replace Abstract: By pretraining on trillions of tokens, an LLM gains the capability of text generation. However, to enhance its utility and reduce potential harm, SF
arXiv:2408.15339v4 Announce Type: replace-cross Abstract: RL alignment methods, including RLHF and DPO, are primarily based on pairwise preference data. Although scalar or score-based feedback has bee
arXiv:2605.07356v1 Announce Type: new Abstract: Semantic segmentation of large-scale 3D point clouds is crucial for applications such as autonomous driving and urban digital twins. However, the sparse
arXiv:2508.02129v2 Announce Type: replace Abstract: Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gauss
arXiv:2602.10693v3 Announce Type: replace-cross Abstract: Off-policy updates are inevitable in reinforcement learning (RL) for large language models (LLMs) due to rollout staleness from asynchronous t
arXiv:2605.05848v2 Announce Type: replace-cross Abstract: Video large multimodal models increasingly face a scalability bottleneck: long videos produce excessively long visual-token sequences, which s
arXiv:2605.06094v2 Announce Type: replace-cross Abstract: Training VideoLLMs for complex reasoning remains challenging due to sparse sequence level rewards and the lack of fine grained credit assignme
what i have been saying for 6 years. maybe now you will believe it? 📁 Fei-Fei Li, former Google Chief Scientist, says the industry is dangerously fixated on language models. Most of the real economy i
arXiv:2605.06868v1 Announce Type: new Abstract: Fixed-budget nonconvex optimization can fail not because local descent is unstable, but because it is too stable: after reaching a nearby stationary poi
Which has better odds? Generative AI earning $1.6 trillion/year or the roulette wheel landing on zero? One estimate of how much annual revenue AI needs to “make sense”: 1.6 trillion. That’s four times
arXiv:2605.05558v2 Announce Type: replace Abstract: A natural intuition about the economics of AI agents is that, because agents can be replicated at very low marginal cost, agent labor may be supplie
arXiv:2605.06992v1 Announce Type: new Abstract: AI agents are increasingly deployed in multi-task settings, where the task to perform is specified at test time, and the agent must generalize to unseen
arXiv:2605.08075v1 Announce Type: new Abstract: Decoding imagined speech from non-invasive brain recordings is challenging because imagined datasets are scarce and difficult to align temporally across
32,000 views for my tweet; 2.2 million for the nonsense it critiques. so typical. lies and distortions beating debunking by a factor of roughly 100. Wanna get a million views? Make stuff up. Take a ti
a tweet to keep in mind when Sam testifies this coming week How can anybody take seriously your claim that “Working towards prosperity for everyone, empowering all people, and advancing science and te
This post highlights a contradiction in AI industry arguments, contrasting Western tech company claims that regulation will disadvantage them competitively against China with evidence of China's own s
FAR more scary than the misunderstood METR time horizon graph everyone here seems to be (wrongly) panicking about. The #AI circular funding bubble is already twice the size of the outstanding debt in
Happy to put money against superintelligence in 2029. Why Superintelligence is Alien Intelligence (A Brief Outline of the Future) We are no longer in the realm of normal technological progress. If the
hey @elonmusk, if you really care about making X a source of truth as you used to claim, take note: @GaryMarcus lies are optimized for engagement, truth is optimized for accuracy the algorithm doesnt
Many are valiantly fighting against the age of bullshit. Bullshit is winning, I'm sorry to report. 😠 32,000 views for my tweet; 2.2 million for the nonsense it critiques. so typical. lies and distorti
Oy. According to a new paper in The Lancet, the rate of made-up citations in biomedical papers has increased by more than 12x since 2023. https://www.thelancet.com/journals/lancet/article/PIIS0140-673
Remarkable numbers here. Goldman Sachs: 'The consensus of analysts is now for the mega-cap US hyperscalers to spend $755 billion on capex in 2026, representing growth of +83% vs. 2025. This capex is e
> shipped the agent > opened the dashboard > latency: fine > error rate: fine > users: unhappy > checked the responses > technically correct > wrong tool called 3 steps earlier > no trace to follow >
This post likely discusses the proliferation of AI bots and chatbot applications while arguing that despite their abundance, many demonstrate reasonable safety practices or alignment with human values
Terence Tao - 'AI tools are like taking a helicopter to drop you off at the site. You miss all the benefits of the journey itself. You just get right to the destination, which actually was only just a
The post asks about user engagement metrics for a specific mode within Codex, requesting data on what percentage of users utilize it and how adoption has changed over the past month. The author sugges
Wow! Wonder how many people on this site hyped this paper – and how many of them will walk back their hype now that the paper has been retracted. A year-old nature paper that advocated the use of Chat
This post likely discusses a cognitive or computational principle where one should primarily focus on horizontal (broad, general, or foundational) aspects of a problem or system, then use inference or
but as noted here, not zero threat, either: The detailed investigation of a prior hantavirus human-human transmission event has evidence of airborne transmission of Andes strain: Patient 1 --> Patient
Gary Marcus discusses how symbolic tools and verification methods may be undervalued in AI development, suggesting that if harnesses and verification systems are performing the primary computational w
David Shepardson / Reuters: GM agrees to pay 12.75M to resolve a California investigation into claims that it illegally sold the location and driving data of OnStar subscribers to brokers — GM (GM.N)
Gary Marcus publicly challenged Joseph Jacks with a $10,000 bet regarding a prediction Jacks made about 2030, requesting direct message contact to formalize the wager. The challenge was posted on X (f
Gary Marcus shares a humorous projection suggesting Anthropic could potentially reach $2 trillion in annual revenue if certain growth assumptions materialize. The post likely comments on AI industry r
🌷 If X had been around during the Dutch tulip craze🌷 1. Prices would have gone even higher before the crash 2. Tweets saying “there’s no bubble” would have gone viral. 3. Prices still would have crash
Is there a version of the bull case that spells out where the multitrillion dollar revenue will come from that doesn’t ultimately revolve around “trust me bro”? (And does it factor in the inevitable p
Questions people will be writing about in the coming years: • Was it a Ponzi scheme? • Why didn’t more people worry about the circular financing? • Why were investors so blasé about the lack of profit
Sorry, @peterwildeford, but this is wrong. Please don’t play along. The measurement “wall” you mention is hit ONLY if you don’t insist on reliability. If you demanded 95% accuracy on the task, the sys
A 2018 study by D.K. Roy and Soroush Vosoughi published in Science found that false information spreads faster on social media platforms than accurate information. The research demonstrates a quantifi
This post likely references the famous opening lyric from The Rolling Stones' 'Satisfaction' (1965) as a commentary on contemporary issues, possibly relating to AI confusion, information overload, or
Gary Marcus discusses the 'too big to fail' concept in the context of AI systems, likely examining how large AI companies or models may pose systemic risks that make them difficult to regulate or shut
'Trump’s most lethal policy will almost surely be his 71% cut in humanitarian aid from 2024 to 2025....The aid cuts cost more than 750,000 lives worldwide in their first year' and 'will cost 9.4M live
Wanna get a million views? Make stuff up. Take a tiny tiny bit of truth and distort it wildly. Consider the tweet below, 1.4M views. Take the chess thing. The paper that is linked doesn’t actually say
'50 percent of Americans told the Pew Research Center last year they were more concerned than excited about what’s to come from A.I. Only 10 percent said they were more excited. That is a yawning gap
Asking for HTML explanations of things is pretty neat, I tried it just now with the obfuscated Python POC for the new http://copy.fail Linux vulnerability: https://simonwillison.net/2026/May/8/unreaso
“Combined free cash flow across Microsoft, Alphabet, Amazon, Meta, and Oracle is projected to FALL more than -70%, to ~100 billion, by the end of …. AI capital expenditure is consuming nearly every do
Alex Lekander / CyberInsider: EU warns that VPNs are being used to bypass online age-verification systems, calling their use “a loophole in the legislation that needs closing” — The European Parliamen
Good summary of today, @katiemiller, but then again it is getting hard to track of the total number of ex-board members who have called Altman a liar 🤷♂️ Also hard to keep track how many OpenAI safet