Knowledge catalogue
Weird how the Pope seems to understand AI better than @geoffreyhinton, but I am 100% with the Pope on this. We are NOT creating beings. The Pope is right. We are creating interactive fiction that is t
weird the way this tweet was getting a ton of traffic and then just stopped. 🤷♂️ I honestly think Elon’s best days are behind him: BYD is crushing Tesla in EVs. Waymo is crushing Tesla in AVs. Anthro
This post likely critiques the irony of someone insulting another person's intelligence while making a basic grammatical error (omitting an apostrophe in 'don't'). Gary Marcus, a cognitive scientist a
genius reply, full of reasoned intellectual argument, from the kind of retail investor who is probably going to get burned on the SpaceX IPO. Going to MIT and NYU may have meant something in the past,
Gary Marcus discusses his moderation approach on social media, noting that he blocks Tesla supporters primarily when they resort to insults rather than substantive arguments, and observes that this oc
I honestly think Elon’s best days are behind him: BYD is crushing Tesla in EVs. Waymo is crushing Tesla in AVs. Anthropic, Openai, and Google are crushing Xai on AI. The SpaceX S-1 is so ridiculous th
“I'm more concerned about the lack of intellectual diversity within the frontier AI commentariat/research world. This improved a lot over the last two years, but we're still far from a healthy ecosyst
is having a four month lead a sustainable multitrillion dollar business model? We took another look at the capability gap between open-weight and proprietary models. Since the start of the year, open-
it is the single most clever move Elon ever pulled off Rule changes for the SpaceX SPCX IPO: Index providers waived the profitability requirement and cut the seasoning window from 90 days to 5. This f
More of my thoughts on the topic in @Corriere: https://www.corriere.it/esteri/26_maggio_29/yoshua-bengio-ai-pope-6aa95de2-33f7-4f73-8905-34b1abedbxlk.shtml “Like nuclear energy, AI must be at the serv
Gary Marcus expresses frustration about an influx of Elon Musk supporters on his social media feed who conflate personal insults with substantive counterarguments. The post appears to critique a lack
so much for multitrillion dollar candy companies Note to all staff: Turns out that super tasty AI candy we've been putting out in large bowls isn't free and it isn't necessarily leading to better prod
this won’t end well. it will end with a bailout. Cash flow no longer covers the AI capex bill, so hyperscalers are funding it with record debt: Hyperscaler bond issuance has soared to $150 billion YTD
what a time to be alive wow, Opus 4.8 is very... argument-happy? it picked a fight with me about my usage of the word 'ontology', and when we eventually got back on the same page philosophically, told
Where is the power/value of money physically located? It's clearly not in the actual physical bills. Why are we more scared of an elderly mafia boss than their much more physically dangerous underling
Why LLMs rarely payoff—and what I have been saying literally for 7 years—confirmed yet again: LLMs can’t handle the truth. (Nor apparently can my critics, who keep saying I am “always wrong”, when I h
A 25B fund just refused SpaceX at any price. It says the company can't be worth more than 1T, half the $1.8T IPO target, and Musk's 85% control makes it impossible to fix from inside. https://thenextw
arXiv:2605.29975v1 Announce Type: new Abstract: We present a fully convolutional denoising autoencoder (FC-DAE) for denoising two-time intensity-intensity correlation functions (C_2) in X-ray photon c
arXiv:2605.29673v1 Announce Type: cross Abstract: Reconstruction-based inference assigns a class by comparing class-wise reconstruction residuals; Sparse Representation Classification (SRC) is a canon
arXiv:2605.30313v1 Announce Type: new Abstract: Simulation-based RL for contemporary robot control is increasingly organized around GPU-resident simulation: physics, rollout collection, and learning a
arXiv:2605.28824v1 Announce Type: new Abstract: Constructing artificial lexicons that are pronounceable, typologically plausible, and semantically structured remains an open challenge in computational
arXiv:2605.30070v1 Announce Type: cross Abstract: Moving beyond simple scalar rewards toward richer world feedback is a natural path to more scalable RL post-training. On-policy self-distillation (OPS
arXiv:2605.29791v1 Announce Type: new Abstract: While Large Language Models (LLMs) can convincingly simulate personas in explicit self-reports, they often deviate in implicit behavioral decisions, rev
arXiv:2605.29458v1 Announce Type: cross Abstract: Accurately simulating the decisions of a specific individual remains challenging for large language models (LLMs), partly because persona information
arXiv:2603.01006v2 Announce Type: replace-cross Abstract: REPresentation Alignment (REPA) improves the training of generative flow models by aligning intermediate hidden states with pretrained teacher
arXiv:2605.28914v1 Announce Type: cross Abstract: Tool-using language agents turn model decisions into external side effects: they read files, run scripts, call APIs, send messages, and invoke Model C
arXiv:2605.29434v1 Announce Type: cross Abstract: Existing sentence-level watermarking methods enhance robustness to paraphrasing by anchoring watermarks in sentence semantics. However, their prefix-b
arXiv:2605.29202v1 Announce Type: new Abstract: Recent advances in text-to-music generation enable high-fidelity synthesis of structured musical audio, raising growing concerns about data provenance,
arXiv:2605.28994v1 Announce Type: new Abstract: AI tools to support real world decision making must be able to build simulation models that inform their recommendations and render them interpretable.
arXiv:2605.28849v1 Announce Type: new Abstract: Gradient temporal-difference methods provide stable off-policy prediction with linear function approximation, but their practical performance is strongl
arXiv:2605.29414v1 Announce Type: cross Abstract: Recent studies have shown that code-switching data (CSD), in which multiple languages are mixed within the same context, can improve cross-lingual tra
arXiv:2605.29697v1 Announce Type: new Abstract: In Agentic Search, trajectory-level outcome rewards fail to quantify the behavioral contributions of individual steps, while existing step-level reward
bold set of counterpredictions, from @scaling01: Cold take on what comes next: - OpenAI will flourish - Anthropic will continue to be profitable - Google will not catch up to Anthropic or OpenAI - no
arXiv:2605.30226v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for grounding visual-language understanding into real-world robotic manipulat
arXiv:2605.29078v1 Announce Type: new Abstract: Event-driven scheduling policies are increasingly deployed in industrial environments, where decisions are made under asynchronous and partially observe
arXiv:2601.08064v2 Announce Type: replace Abstract: Confidence estimation (CE) indicates how reliable the answers of large language models are and impacts user trust and decision-making. Existing eval
arXiv:2605.29971v1 Announce Type: new Abstract: Causal interventions in language model representations have largely targeted discrete features, like grammatical number. However, language models must a
arXiv:2602.11389v2 Announce Type: replace Abstract: World models require robust relational understanding to support prediction, reasoning, and control. While object-centric representations provide a u
arXiv:2605.29836v1 Announce Type: cross Abstract: Despite strong average-case performance, deep learning models often exhibit systematic errors on specific population groups, known as error slices. Id
arXiv:2605.29788v1 Announce Type: new Abstract: Critical sequential decisions are rarely single-timescale: a strategic decision causally shapes the context in which every subsequent tactical choice is
arXiv:2605.30332v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art image synthesis, with their generative trajectories fundamentally exhibiting a spectral bias, resolving low-fr
arXiv:2605.29452v1 Announce Type: new Abstract: Image-based 3D reconstruction offers a low-cost alternative to traditional sensor-based techniques for road surface assessment. This study compares four
arXiv:2410.07287v2 Announce Type: replace-cross Abstract: Climate change poses an existential threat, necessitating effective climate policies to enact impactful change. Decisions in this domain are i
arXiv:2605.29886v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive question answering by incorporating external evidence. However, existing RAG methods
arXiv:2605.30211v1 Announce Type: new Abstract: Self-supervised video Object-Centric Learning (OCL) aims to discover distinct objects and associate them across time, whereas self-supervised Multi-Obje
arXiv:2605.30135v1 Announce Type: cross Abstract: Various algorithms have been proposed to address the challenges posed by class-imbalanced learning from real-world data with long-tailed distributions
arXiv:2605.29522v1 Announce Type: new Abstract: As scientific literature grows rapidly, automated survey generation has become a key capability for AI scientists and human researchers. However, existi
arXiv:2605.30215v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction transformers have scaled to over a billion parameters, following the broader trend of increasing model capacity in
arXiv:2605.30003v1 Announce Type: cross Abstract: We study two-level autoresearch for cooperation: an outer-loop AI agent autonomously redesigns the inner-loop pipeline of an LLM policy-synthesis syst
arXiv:2605.29152v1 Announce Type: new Abstract: Randomly initialized neural networks induce a prior over functions, but the predictor used in practice is produced only after training. We ask how much
arXiv:2605.29343v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference by pairing a target model with a lightweight draft model whose proposed tokens are verif
arXiv:2510.27607v3 Announce Type: replace Abstract: Augmenting vision-language-action models (VLAs) with world models is promising for robotic policy learning but faces challenges in jointly predictin
arXiv:2605.30350v1 Announce Type: cross Abstract: Robot manipulation critically depends on perception that preserves the action-relevant aspects of a scene. Yet most robot learning pipelines are built
arXiv:2602.08783v3 Announce Type: replace Abstract: Latent or continuous chain-of-thought methods replace explicit textual rationales with a number of internal latent steps, but these intermediate com
arXiv:2509.23730v2 Announce Type: replace Abstract: Large language models (LLMs) have recently advanced in reasoning when optimized with reinforcement learning (RL) under verifiable rewards. Existing
arXiv:2605.28865v1 Announce Type: cross Abstract: What does a world model learn from physical exploration, without any linguistic supervision? We argue the answer is organized by a single principle: t
arXiv:2605.29303v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) followed by reinforcement learning (RL) has become a standard post-training paradigm for large language models. This paradi
arXiv:2505.21876v2 Announce Type: replace-cross Abstract: Recent approaches for video generation with camera control often create anchor videos (i.e., rendered videos that approximate desired camera m
even if @scaling01 turns out to be wrong about some of these, I respect the specificity. a bit more specific: - OpenAI will flourish -> meaning they will stay at the frontier and their market cap cont
arXiv:2605.29161v1 Announce Type: cross Abstract: Generating realistic graph-structured data is challenging due to discrete connectivity, varying graph sizes, and class-specific structural patterns. R