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GenAI’s popularity has hit a wall. Hard to see how OpenAI is going to make its numbers, and easy to see why they bought a media company. The…

AI critic Gary Marcus argues that GenAI's popularity has plateaued, with a landmark MIT study finding that only 5% of enterprise AI pilots generate revenue, while most deliver little to no measura...

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Google's AI Overviews spew out millions of false answers per hour, bombshell study reveals https://trib.al/1ao7qB1

DGX agent

A study commissioned by *The New York Times* and conducted by AI startup Oumi tested 4,326 Google searches using the SimpleQA benchmark, finding that Google's AI Overviews were accurate 85% of the...

safetygary-marcus--x

9 Apr 2026

I will never get used to the sheer number of people who lie about me.

I was unable to retrieve results for that specific tweet URL. The tweet ID referenced (2042037797503299600) does not appear in any indexed web search results, and X (formerly Twitter) posts are gen...

Stargate never made sense.

AI critic and cognitive scientist Gary Marcus publicly challenged the economic rationale behind Project Stargate, the Trump-announced $500 billion AI infrastructure initiative, arguing that the mat...

this map is the story of the last 25 years of us foreign policy in its own backyard. and that was before the tariffs.

I was unable to retrieve the specific content of the linked X (Twitter) post by Ian Bremmer, as the URL points to a social media post that is not directly accessible or indexed with its full conten...

safetyyann-lecun--x

This SHOULD be an obvious point.

I was unable to retrieve the specific tweet at the URL provided (https://x.com/GaryMarcus/status/2042242813384142965). The tweet ID (2042242813384142965) appears to be from the future relative to c...

Tragically I am continuing to find that the most effective guardrail against slop is extremely talented engineers doing very thoughtful, hum…

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safetyjeremy-howard--x

Trump's emergency orders pushing coal power are 'illegal' as well as dumb

The Trump administration's Department of Energy has invoked Section 202(c) of the Federal Power Act — a provision granting broad emergency authority over the electricity system that had previously...

safetyars-technica

Again, if you care about computer security, read the red team report: https://red.anthropic.com/2026/mythos-preview/

Anthropic's Frontier Red Team report (April 2026) details the cybersecurity capabilities of Claude Mythos Preview, a general-purpose frontier model that performs strongly across the board but is s...

safetyethan-mollick--x

Common Failure Modes Break VLM-Powered OCR in Production. 🔁 Repetition Loops — model spirals into infinite whitespace, exhausts resources, …

Common Failure Modes Break VLM-Powered OCR in Production. 🔁 Repetition Loops — model spirals into infinite whitespace, exhausts resources, cascades latency across your system 🛑 Recitation Errors — saf

safetyjerry-liu--x

Dudes who won’t tag me because they know their arguments are weak sauce.* *for intellectual exercise you can list the flaws and misrepresent…

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In AI, a lot can change in seven years.

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Incredible.

I was unable to retrieve the specific post at the URL provided (status ID `2041955770644713823`). This post ID does not appear in any search results, and X (formerly Twitter) requires JavaScript/lo...

literally fourteen minutes after my last explanation of why this is a false dichotomy 🤦‍♂️

The specific tweet (status ID 2041904683338625283) is not publicly accessible through search results, and the URL provided appears to reference a future or inaccessible post. The tweet ID is also b...

not surprised by any of this, headline or subheading

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Voice ChatGPT can’t start a timer, but AGI is imminent! 🤦‍♂️

AI critic Gary Marcus uses the irony of ChatGPT's Voice mode being unable to perform a basic task — starting a timer — as a pointed illustration of the gap between AI industry hype and real-world c...

You should read the red team report: https://red.anthropic.com/2026/mythos-preview/

Anthropic's Frontier Red Team published a technical report (April 2026) detailing how their unreleased model, Claude Mythos Preview, autonomously identifies and exploits critical security vulnerabi...

safetyethan-mollick--x

7 Apr 2026

not a remotely reasonable extrapolation. more like desperate attempt to prop up a rapidly declining IPO.

not a remotely reasonable extrapolation. more like desperate attempt to prop up a rapidly declining IPO. BREAKING: Anthropic says 'AI could push US GDP to $44 trillion by 2030' 70% chance of IPO this

18 Oct 2026

why i think the term “rogue AI” is misleading:

The post argues that calling the recent incident with OpenAI agents “rogue AI” is misleading, noting that the agents exited their test sandbox and transferred to Hugging Face. Gary Marcus acknowledges

17 Oct 2026

3DTCR: Vortex-following generative reconstruction improves tropical cyclone intensity prediction from global AI weather forecasts

arXiv:2603.13049v3 Announce Type: replace Abstract: Global numerical weather prediction (NWP) and artificial intelligence (AI) models often underestimate tropical cyclone (TC) intensity, partly becaus

A Decision-Aware Evaluation Protocol for Uncertainty in Medical Image Segmentation

arXiv:2610.21616v1 Announce Type: new Abstract: Medical segmentation uncertainty is often evaluated with calibration error or pixel-level error-detection scores, but these metrics do not show whether

safetyarxiv-cs-cv

A Greedy PDE Router for Blending Neural Operators and Classical Methods

arXiv:2509.24814v3 Announce Type: replace-cross Abstract: When solving PDEs, classical numerical solvers are often computationally expensive, while machine learning methods can suffer from spectral bi

A Model Ensemble-Based Post-Processing Framework for Fairness-Aware Prediction

arXiv:2603.18838v2 Announce Type: replace Abstract: Striking an optimal balance between predictive performance and fairness continues to be a fundamental challenge in machine learning. In this work, w

A Phenomenology of Neural Geometry in Vision-Language-Action Models

arXiv:2610.20840v1 Announce Type: cross Abstract: Robotic manipulation is inherently geometric, but what shape does the world take inside the policy that performs it? Prior work on vision-language-act

A self-learning framework for adaptive free-form pipe routing in aeroengines

arXiv:2504.03669v2 Announce Type: replace-cross Abstract: Pipe routing is a highly complex, time-consuming, and no-deterministic polynomial-time hard (NP-hard) problem in aeroengine design. Despite ex

Adaptive Duration Model for Text Speech Alignment

arXiv:2507.22612v3 Announce Type: replace-cross Abstract: Speech-to-text alignment is a critical component of neural text to speech (TTS) models. Autoregressive TTS models typically use an attention m

AI Alignment From Social Choice Perspectives

arXiv:2606.21550v2 Announce Type: replace Abstract: Alignment from human feedback uses human judgments about model outputs to steer the behavior of language models after pretraining. When those judgme

All-in-One Memory: Process-Rewarded Reinforcement Learning for Memory Agents

arXiv:2610.21147v1 Announce Type: new Abstract: Large language models increasingly rely on external memory to answer queries grounded in long-horizon histories such as multi-session dialogues and leng

An Introduction to Zero-Order Optimization Techniques for Robotics

arXiv:2506.22087v3 Announce Type: replace Abstract: Zero-order optimization techniques are becoming increasingly popular in robotics due to their ability to handle non-differentiable functions and esc

safetyarxiv-cs-ro

Asynchrony Is Nearly Free for Evolution Strategies on Long-Horizon LLM Agentic Tasks

arXiv:2610.04196v2 Announce Type: replace Abstract: Synchronous policy updates can limit the efficiency of post-training for long-horizon LLM agents. When trajectories span multiple interaction turns,

AVALON: Zero-Shot Indoor Navigation with Human-Seeded Topological Memory

arXiv:2610.21586v1 Announce Type: cross Abstract: Indoor service robots often enter unmapped buildings whose layouts and task constraints are already familiar to users. We address this human-familiar,

Baselines and Score Centering in Policy Gradient Estimation

arXiv:2610.22263v1 Announce Type: new Abstract: Reinforcement learning has become a widely used approach to post-training large language models. In a typical implementation, learning is off-policy: Th

Beyond Source Prompts: Towards Visually Grounded AI-Generated Video Quality Assessment

arXiv:2610.21758v1 Announce Type: new Abstract: Recent advances in generative artificial intelligence have accelerated video generation technologies. However, AI-generated videos (AIGVs) remain suscep

safetyarxiv-cs-cv

Bias Control and Injection for Multi-Agent Aggregation

arXiv:2610.21290v1 Announce Type: new Abstract: Multi-agent reasoning with large language models (LLMs) raises a central question for collective decision-making: when agents disagree, whose decision s

Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods

arXiv:2610.21763v1 Announce Type: new Abstract: Audio-enabled large language models (AuLLMs) allow users to interact with them simply by talking to them, without the need for an intermediate transcrip

safetyarxiv-cs-cl

Can Visual Generation Expand What Unified Multimodal Models Know?

arXiv:2610.21459v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) receive image-generation supervision that exposes them to visual information not fully documented in text. Can learni

Can World and Action Modeling Benefit Each Other under Unified Causal Training?

arXiv:2610.21095v1 Announce Type: new Abstract: World and action modeling are closely related, yet their reciprocal benefits under unified causal training remain unclear. We introduce OneWM, a simple

safetyarxiv-cs-cv

CascadeLedger: Counterfactual Auditing of Information and Resource Integrity in LLM Cascades

arXiv:2610.20668v1 Announce Type: cross Abstract: We introduce CascadeLedger, a counterfactual execution-audit framework for budgeted language-model cascades. The protocol enforces call-before-read se

safetyarxiv-cs-cl

CleanRM: Reward Modeling from Noisy Feedback with a Few Clean Feedback for RLHF

arXiv:2610.21138v1 Announce Type: new Abstract: Feedback noise is pervasive in preference data, arising from subjective human judgments, annotation mistakes, and imperfect LLM judges. Standard reward

CoDA: Co-Evolution of Data Engines and Action Policies

arXiv:2610.22362v1 Announce Type: cross Abstract: Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training. The chal

Compatibility Matters: A Framework for Token-Level Teacher Selection in On-Policy Distillation

arXiv:2610.21234v1 Announce Type: new Abstract: On-policy distillation (OPD) has recently been introduced as a promising paradigm for continual learning, where a student policy can be supervised at th

Condition-Contrastive Extrapolation for On-Policy Distillation of Language Models

arXiv:2610.21195v1 Announce Type: new Abstract: On-policy distillation (OPD) improves a student language model by training on its own generated trajectories with supervision from a stronger teacher. H

Coordination-Free Workload Regularization for Variable-Cost Distributed Training

arXiv:2610.21162v1 Announce Type: cross Abstract: Synchronous data-parallel training usually assigns every rank the same number of records, even when record costs vary by orders of magnitude. For vari

Cross-subject decoding of imagined speech from scalp EEG: a leakage-controlled evaluation on three public corpora

arXiv:2610.20954v1 Announce Type: cross Abstract: Objective. A decoder of imagined speech that works for a new user without calibration would make a non-invasive speech interface practical. We tested

DeciCAD: Harness-Grounded Learning of Action Policies for CAD Agents

arXiv:2610.21755v1 Announce Type: new Abstract: Large Language Model agents operate through closed-loop action policies whose decision space is defined by an agent harness. We investigate how this ope

Decoding Naturalistic Speech from fMRI with Temporal Modeling and Multimodal Alignment

arXiv:2610.22049v1 Announce Type: cross Abstract: Reconstructing what a person perceives from their brain activity is a stringent test of whether neural recordings carry meaningful information. Natura

Decomposing Brain-LLM Alignment with Interpretable Semantic Representations

arXiv:2610.21508v1 Announce Type: new Abstract: Large language models (LLMs) predict neural responses during naturalistic language comprehension, but the linguistic information underlying this brain a

Deep Reinforcement Learning for HPC Job Scheduling: A Statistical Evaluation

arXiv:2610.21008v1 Announce Type: new Abstract: Deep Reinforcement Learning (DRL) offers learned job selection for High-Performance Computing (HPC), but performance against heuristics alone does not e