Knowledge catalogue
it ain’t just me who sees the emperor has no clothes The AI bubble math doesn't add up. Anthropic spends 3 to make 1 and that’s before you include any and all other costs like staff or electricity. Mi
it’s truly astonishing to see the entire field move in the neurosymbolic and world model directions I advocated in 2019 and 2020 and then simultaneously see people claim (invariably without specific e
This essay discusses 'vibe slop,' a term describing low-quality AI-generated content that lacks substance but mimics the aesthetic and emotional tone of authentic creative work. The piece likely argue
arXiv:2605.22717v1 Announce Type: cross Abstract: Interactive streaming music generation promises the use of generative models for live performance and co-creation that is impossible with offline mode
arXiv:2605.22291v1 Announce Type: new Abstract: Long-term fairness algorithms aim to satisfy fairness beyond static and short-term notions by accounting for the dynamics between decision-making polici
arXiv:2603.19310v3 Announce Type: replace Abstract: Reinforcement learning has emerged as a powerful paradigm for improving large language model (LLM) reasoning, where rollouts are sampled from the po
arXiv:2605.21722v1 Announce Type: cross Abstract: Sampling from discrete distributions with multiple modes and energy barriers is fundamental to machine learning and computational physics. Recent disc
my guess as to why: the OpenAI crowd is suddenly coming after me relentlessly, but too chicken to actual face me in a moderated debate. here’s why: a. the IPO is coming, but OpenAI’s has lost their le
NEW: Google claimed this week that a team of agents had built an entire operating system, based on a single prompt, costing only about $900 in tokens. We fact check this claim and analyze what it mean
arXiv:2605.21561v1 Announce Type: new Abstract: Unsupervised feature selection is commonly formulated as a multiobjective optimisation problem that jointly optimises subset quality and subset size. Ye
arXiv:2605.21763v1 Announce Type: new Abstract: We study risk-sensitive reinforcement learning in finite discounted MDPs, where a generative model of the MDP is assumed to be available. We consider a
arXiv:2605.22156v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a promising paradigm for scaling reasoning capabilities of Large Language Models (LLMs)
Gary Marcus humorously highlights the massive valuation gap for OpenAI, suggesting that the company would need to generate approximately 5 trillion dollars in profit to justify a 4 trillion dollar val
OpenAI’s “Roon” is officially a chicken, just as I thought. And just like his boss (who has also ducked debates with me). If either actually thought they could dismantle my arguments, it certainly *wo
arXiv:2605.21752v1 Announce Type: new Abstract: Recommender systems trained on user interaction data are susceptible to behavioral intensity imbalance--a systematic distortion arising from heterogeneo
arXiv:2605.22731v1 Announce Type: new Abstract: Large language model post-training methods such as supervised fine-tuning (SFT), reinforcement learning (RL), and distillation are often analyzed throug
arXiv:2605.22738v1 Announce Type: new Abstract: Shapley and Banzhaf interactions capture the complex dynamics inherent in modern machine learning applications. However, current estimators for these hi
Quarter million views and counting. OpenAI has no idea how many people they have pissed off. Fuck this OpenAI employee, seriously fuck him. Also read this quantitative study, which I had nothing to do
arXiv:2603.03454v2 Announce Type: replace Abstract: Offline Reinforcement Learning (RL) is an emerging field of RL in which policies are learned solely from demonstrations. Within offline RL, some env
receipt confirming the chicken part of the above: OpenAI’s “Roon” is officially a chicken, just as I thought. And just like his boss (who has also ducked debates with me). If either actually thought t
Gary Marcus references a Nautilus article arguing that deep learning is encountering fundamental limitations, suggesting readers can find supporting evidence and detailed arguments for this perspectiv
Retweeting this because there appears to be a coordinated and intellectually dishonest campaign to defame me by misrepresenting my beliefs. The case against me below is completely intellectually disho
arXiv:2602.10894v2 Announce Type: replace Abstract: Two-player games such as board games have long been used as traditional benchmarks for reinforcement learning. This work revisits a policy optimizat
Sam Altman is rushing to an IPO for OpenAI... ...but if the public markets treat @OpenAI like a traditional business instead of a religion, it's game over. 💀💀💀 @sama #openai #chatGPT credit: @Stylosa
serious escalation in Trump’s growing challenges with inhibiting his behaviors. neurologists know what that means. Trump posts AI video depicting him throwing Colbert in a dumpster and dancing https:/
six years ago world (cognitive) models were the centerpiece of my essay The Next Decade in AI. their time is finally coming. Demis Hassabis on the limit in today’s AI: language can describe the world,
arXiv:2511.04838v2 Announce Type: replace Abstract: Molecular property regression struggles with cases in chemically relevant target ranges that are underrepresented in datasets. Standard average erro
arXiv:2605.21736v1 Announce Type: cross Abstract: Logged advertising auctions make offline reserve-price evaluation attractive but risky. Replay tables can identify policies with large apparent yield
arXiv:2605.22263v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) is an emerging LLM post-training paradigm in which the model serves as its own teacher: conditioned on privileged inf
arXiv:2605.22376v1 Announce Type: new Abstract: Cross-domain offline reinforcement learning (CDRL) aims to improve policy learning in a target domain by leveraging data collected from a source domain.
arXiv:2605.21492v1 Announce Type: new Abstract: No feature ranking can be simultaneously faithful, stable, and complete when features are collinear. For collinear pairs, ranking reduces to a coin flip
The biggest myth of all is that I am the only one who doubts the hype. Demonize me all you like, but the bubble is still probably gonna burst. So many other people see it, too. Speculative hype bubble
Gary Marcus comments on OpenAI's financial losses, referencing a period when the company's annual losses were approximately $5 billion as a point of comparison to its current financial situation. The
the OpenAI crowd is suddenly coming after me relentlessly, but too chicken to actual face me in a moderated debate. here’s why: a. the IPO is coming, but OpenAI’s has lost their lead over Anthropic an
arXiv:2605.22496v1 Announce Type: new Abstract: Deep generative models offer a natural foundation for out-of-distribution (OOD) detection, yet prior work has shown that their assigned likelihoods are
The US government absolutely should NOT bail out OpenAI. They have AFAIK been given more funding than anyone in history and there is no evidence they can run a profitable business,and meanwhile many o
This is collectively the largest financial iceberg ever put in front of the stock market. This is $5 trillion in TOTAL AIR. These companies have never made a dime. SpaceX is literally a government wel
🦔This one happened yesterday but is still worth flagging. Starbucks killed its AI-powered inventory counting tool after nine months in North American stores. The system used LiDAR sensors and cameras
Three cheers for @flowersslop who agrees with me about nothing but still sees the value of thoughtful disagreement. thanks feels like a hot take now, but any space needs a real variety of opinions. I
Total amount raised: 190 billion Total spending pledged: 600 billion Total profits (cumulative): 0 @CarinaN818 @GaryMarcus Because you can raise 190 billion in funding by releasing an LLM chatbot that
arXiv:2306.05905v2 Announce Type: replace Abstract: A convenient approach to optimally solving combinatorial optimization tasks is the Branch-and-Bound method. Its branching heuristic can be learned t
arXiv:2511.14220v3 Announce Type: replace Abstract: Model-based reinforcement learning (RL) methods that leverage search are responsible for many milestone breakthroughs in RL. Sequential Monte Carlo
arXiv:2502.13822v3 Announce Type: replace-cross Abstract: We establish novel and general high-dimensional concentration inequalities and Berry-Esseen bounds for vector-valued martingales induced by Ma
Gary Marcus discusses the risks that AI systems may function adequately until they unexpectedly fail catastrophically, potentially causing severe economic damage. The post suggests that current AI rel
Gary Marcus reports on X that someone named Theo has clarified he did not accept fees from OpenAI, following earlier ambiguity about his financial relationships with the company. The post appears to b
Gary Marcus critiques OpenAI's business model sustainability, suggesting it lacks transparency or clear long-term viability beyond investor confidence. The post implies skepticism about OpenAI's path
arXiv:2605.22257v1 Announce Type: new Abstract: Formal theorem provers based on large language models (LLMs) are highly sensitive to superficial variations in problem representation: semantically equi
arXiv:2605.21868v1 Announce Type: new Abstract: In competitive games, players frequently switch strategies after losing streaks, yet our analysis of 926,334 match records from 34,619 Clash Royale play
World models have existed for years (though not in LLMs); I take them to be explicit representation of objects, places, events, mechanisms etc you can reason over. Chess computers have them (board, pi
you can destroy a person’s simply by lying about them. that is what OpenAI is trying do to me. ask yourself why The case against me below is completely intellectually dishonest, filled with lies and m
100% agree with @BethMayBarnes on this point and most (though not quite all*) of her important thread. *i am much less concerned about extinction risk per se, as discussed in my TLS review of If Anyon
arXiv:2510.04280v2 Announce Type: replace-cross Abstract: Effective exploration remains a central challenge in model-based reinforcement learning (MBRL), particularly in high-dimensional continuous co
arXiv:2605.22608v1 Announce Type: new Abstract: Agentic systems are becoming more capable: agents define strategies, take actions, and interact with different environments. This autonomy poses serious
Gary Marcus announced an upcoming CNBC live segment scheduled for approximately 11:15 ET featuring hosts Carl Quintanilla and Leslie Picker to discuss the intersection of artificial intelligence and i
America’s biggest companies have gone from printing money to burning it. It does not take Poirot to work out what’s going on. Register for free to get our columnist’s take on it http://econ.st/4tKbpoB
arXiv:2605.21653v1 Announce Type: cross Abstract: AI text detectors amplify a pretrained typicality axis; they do not construct an AI-vs-human boundary. On raw encoders before any task supervision, pr
arXiv:2605.22123v1 Announce Type: new Abstract: Designing reward functions that generalize beyond controlled laboratory settings remains a fundamental challenge in reinforcement learning for robotics.
arXiv:2605.22547v1 Announce Type: new Abstract: Deep learning has brought significant progress to medical image classification, yet most existing methods still rely on isolated visual evidence and can
arXiv:2505.16416v3 Announce Type: replace Abstract: Rotary Position Embedding (RoPE) is widely adopted in large language models, but when applied to vision-language models (VLMs) it couples text and i
arXiv:2605.21688v1 Announce Type: new Abstract: Autonomous contact-based micromanipulation is challenging because surface and interfacial interactions at the microscale are difficult to model accurate