Search: “safety”

Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines

arXiv:2605.22155v1 Announce Type: new Abstract: Symbolic methods are generally not considered competitive with strong modern learners on realistic supervised tasks. We evaluate Algebraic Machine Learn

Safety

another of the dudes going after me (Theo) is perhaps paid by OpenAI 🙄

DGX agent

another of the dudes going after me (Theo) is perhaps paid by OpenAI 🙄 He doesn’t work for them, but he likely has or has had some paid partnership with them, because they’ve invited him onto their ca

safetygary-marcus--x

23 May 2026

ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models

arXiv:2605.22222v1 Announce Type: new Abstract: Partial differential equation (PDE) foundation models are pretrained networks that forecast how physical fields like velocity and pressure evolve from a

Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models

arXiv:2603.02938v2 Announce Type: replace Abstract: Graph-based tasks in the zero-shot setting remain a significant challenge due to data scarcity and the inability of traditional Graph Neural Network

BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series

arXiv:2605.22468v1 Announce Type: new Abstract: Cross-subject generalization in biomedical time-series refers to training on data from some subjects and testing on unseen subjects.The key challenge is

Causal Discovery in Structural VAR Models Under Equal Noise Variance

arXiv:2605.21846v1 Announce Type: cross Abstract: Causal discovery from multivariate time series is challenging when causal effects may occur both across time and within the same sampling interval. Th

CCLab: Adversarial Testing of Learning- and Non-Learning-Based Congestion Controllers

arXiv:2605.21915v1 Announce Type: cross Abstract: Congestion controllers (CCs) are critical to network performance, and yet their robustness under adverse conditions remains insufficiently understood.

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates

arXiv:2509.08933v2 Announce Type: replace Abstract: We study the problem of learning the optimal policy in a discounted, infinite-horizon reinforcement learning (RL) setting in the presence of adversa

Cross-Species RSA Reveals Conserved Early Visual Alignment but Divergent Higher-Area Rankings Across Human fMRI and Macaque Electrophysiology

arXiv:2605.22401v1 Announce Type: new Abstract: Does the relationship between learning rules and brain alignment generalize across species? We extend our prior finding that untrained CNNs match backpr

DecepChain: Inducing Deceptive Reasoning in Large Language Models

arXiv:2510.00319v2 Announce Type: replace Abstract: Large Language Models (LLMs) have been demonstrating strong reasoning capability with their chain-of-thoughts (CoT), which are routinely used by hum

Don't Forget the Critic: Value-Based Data Rehearsal for Multi-Cyclic Continual Reinforcement Learning

arXiv:2605.22454v1 Announce Type: new Abstract: Data rehearsal has emerged as a leading approach for mitigating catastrophic forgetting in Continual Reinforcement Learning (CRL). However, existing wor

During his second term, Trump will have cut 2 of the US most powerful innovation and wealth creation engines: 1. skilled legal immigration 2…

During his second term, Trump will have cut 2 of the US most powerful innovation and wealth creation engines: 1. skilled legal immigration 2. (non-defense) research budgets We won't see the effect of

safetyyann-lecun--x

ECPO: Evidence-Coupled Policy Optimization for Evidence-Certified Candidate Ranking

arXiv:2605.21993v1 Announce Type: cross Abstract: Ranking systems used in decision-support settings should not only order candidates but also expose evidence that can be independently checked. We stud

Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction

arXiv:2605.21563v1 Announce Type: new Abstract: Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an em

extit{BlockFormer} : Transformer-based inference from interaction maps

arXiv:2605.21617v1 Announce Type: new Abstract: Inference from interaction maps, such as centromere identification from genome-wide chromosome conformation capture techniques -- notably Hi-C -- can be

Factored Diffusion Policies:Compositionally Generalized Robot Control with a Single Score Network

arXiv:2605.22596v1 Announce Type: new Abstract: Robotic tasks are typically specified by a tuple of factors, such as the object to be grasped, the obstacles to be avoided, the color of the target, and

From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching

arXiv:2605.22340v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) provides high-dimensional profiles of cellular states, enabling data-driven modeling of cellular dynamics over ti

@GaryMarcus If OpenAI gets bailed out, I will lobby with all of my effort to ensure whatever political faction was responsible gets voted ou…

@GaryMarcus If OpenAI gets bailed out, I will lobby with all of my effort to ensure whatever political faction was responsible gets voted out. I'm about to become a single issue voter over AI because

Generative Modeling by Value-Driven Transport

arXiv:2605.22507v1 Announce Type: new Abstract: We propose a new framework for generative modeling based on a discrete-time stochastic control formulation of measure transport. Adapting classic result

Harnesses for Inference-Time Alignment over Execution Trajectories

arXiv:2605.21516v1 Announce Type: new Abstract: Harness engineering has emerged as an important inference-time technique for large language model (LLM) agents, aiming to improve long-term performance

HealthMamba: An Uncertainty-aware Spatiotemporal Graph State Space Model for Effective and Reliable Healthcare Facility Visit Prediction

arXiv:2602.05286v3 Announce Type: replace Abstract: Healthcare facility visit prediction is essential for optimizing healthcare resource allocation and informing public health policy. Despite advanced

Here’s a key line in this mythos update. This is precisely an example of why engineers don’t go away, ever. We’ve made it far easier to crea…

Here’s a key line in this mythos update. This is precisely an example of why engineers don’t go away, ever. We’ve made it far easier to create and find security issues, which means the new bottleneck

Heterogeneous Agent Collaborative Reinforcement Learning

arXiv:2603.02604v2 Announce Type: replace Abstract: We introduce Heterogeneous Agent Collaborative Reinforcement Learning (HACRL), a new Reinforcement Learning from Verifiable Reward (RLVR) problem th

I am deleting a question I had about @theo in light of his clarification. I hope that he and others will reconsider his/their own slander in…

I am deleting a question I had about @theo in light of his clarification. I hope that he and others will reconsider his/their own slander in light of my own clarifications, such as the one below that

I love that this post, my most foulmouthed ever, has gotten over 100k views. You want to know why it has spread? Simple. Because a lot of pe…

I love that this post, my most foulmouthed ever, has gotten over 100k views. You want to know why it has spread? Simple. Because a lot of people have become really fed up with OpenAI. Fuck this OpenAI

I think the world is about to get flooded with a lot of AI slop math, and the job of the professional mathematician is about to get more imp…

Gary Marcus expresses concern that AI-generated low-quality mathematical content ('AI slop') will proliferate, making the role of professional mathematicians increasingly important for quality control

it ain’t just me who sees the emperor has no clothes

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 si…

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

Just when you thought things couldn’t get worse, get ready for vibe slop. (from an essay on Medium by Earl Cotten)

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

Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators

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

Long-term Fairness with Selective Labels

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

MemReward: Graph-Based Experience Memory for LLM Reward Prediction with Limited Labels

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

MetaDNS: Enhancing Exploration in Discrete Neural Samplers via Well-Tempered Metadynamics

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:

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 …

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

Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection

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

On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents

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

One-Way Policy Optimization for Self-Evolving LLMs

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)

OpenAI is only about 5 trillion dollars in profit away from being a 4 trillion company.

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…

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

PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation

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

Post-Training is About States, Not Tokens: A State Distribution View of SFT, RL, and On-Policy Distillation

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

Proxy-Based Approximation of Shapley and Banzhaf Interactions

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.

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

[Re] FairDICE: A Fair Tradeoff in Multi-objective Offline RL

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:

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

receipts for most points can found here, if you read this paper closely: https://nautil.us/deep-learning-is-hitting-a-wall-238440

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.

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