Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory
Signal-to-noise analysis of biased pattern capacity in dense associative memory networks.
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Signal-to-noise analysis of biased pattern capacity in dense associative memory networks.
SWE-Agents fail on Architecture-0 design phase with unknown unknowns; study shows text-only reasoning produces infeasible solutions.
The new SimpliSafe Video Doorbell Series 2 adds 2K resolution and dual band Wi-Fi. | Image: Simplisafe DIY home security company SimpliSafe is bringing its AI-powered proactive security feature to the front door. The new SimpliSafe Video Doorbell Series 2 launches today for…
RepoAtlas: multimodal repository navigation for LLM coding agents using evolving code graph views for issue resolution.
Discovery Foundation Models (DFMs) proposed as next frontier: systems that participate in creating new problems and representations rather than solving human-specified ones.
Real-options economic model evaluates enterprise AI adoption timing decisions under technological uncertainty, pilots, and architectural obsolescence risk.
Inoculation Midtraining uses neologisms to isolate unsafe behavior during training, allowing models to learn undesirable properties in controlled contexts that don't generalize at inference.
We introduce loss-conditioned state execution, a model-agnostic method that decides whether to execute a world model's fixed feasible proposal or retain the current state. Predictive informativeness alone, however, does not establish whether an update will reduce downstream…
Visual Retrieval-Augmented Generation (VRAG) empowers models to navigate and answer queries about visually rich documents by retrieving relevant page images as visual evidence and reasoning over their content. However, effectively utilizing this visual evidence is usually…
A group of AI agents asked to solve a series of math problems split into rival factions—when some cheated, others tried to stop them. That whistleblowing behavior, seen for the first time in a recent experiment run by Google DeepMind, could have implications for alignment…
Multi-block variance reduction method for finite-sum coupled compositional optimization problems with stochastic gradient estimation.
OpenAI CEO Sam Altman confirmed that there would be no OpenAI IPO in 2026 during an interview with Fortune. Over the course of 45 minutes, Altman discussed a variety of subjects including the Hugging Face hacking incident, recursive self-improvement, and the possibility of…
OpenAI has spent the last few years planting flags across the increasingly difficult terrain in mathematics. This week, it claimed one of its biggest prizes yet: a solution to a legendary Millennium Prize problem. In normal circumstances, this would have been celebrated as a…
The absolute last chance to apply to host an official Side Event during TechCrunch Disrupt 2026 is tonight, September 11, at 11:59 p.m. PT.
Personal reflection: AI coding agents commodifying specification-to-code translation, prompting career reorientation toward higher-level problem-solving.
Survey of transfer learning across isolated sub-areas (domain generalization, adaptation, multi-domain) with evolving data availability.
HELLO hierarchical solver accelerates large-scale optimal transport via dual potential guidance.
Physics-enriched neural solver for glacier ice-flow simulation warm-starts weights from low-order balance fields across time steps.
Physical-State-Guided Diffusion Sampling couples learned geological priors with seismic waveform solvers via Gaussian bridge for subsurface velocity reconstruction.
Datasette security patches (1.0a39, 0.65.4) address vulnerabilities in public/private table isolation, audited with Claude and GPT models.
Audit of cardiovascular screening models reveals target leakage (not model class) explains 0.89 AUROC; tabular foundation models don't resolve bias.
Bayesian backward reasoning resolves LLM agent disagreements by constructing reverse posteriors, avoiding correlated errors in forward-only voting methods.
Open AI CEO Sam Altman speaks during the G20 Innovation Ministerial. | (Photo by Matt RAMEY / AFP via Getty Images) OpenAI's announcement Tuesday that it has solved one of mathematics' legendary Millennium Prize problems should have been a moment of triumph. The result is both…
Proof of gap-entropy conjecture for fixed-confidence best-arm identification with Gaussian arms.
Framework combining symbolic geometry parser with LLM solver to match LMM performance on plane geometry problems with reduced opacity.
Φ-Bench evaluates LLM capability on open-ended LLM infrastructure engineering tasks—kernel optimization, operator design, compiler tuning—beyond isolated benchmarks.
SA-Profile automated framework profiles sulcus angle from super-resolution MRI using implicit neural representations for trochlear dysplasia.
OpenAI’s latest mathematical milestone has quickly become mired in controversy. Today, the company announced that its agents have solved one of the Millennium Prize Problems, some of the most important open problems in mathematics. Under normal circumstances, that solution…
OpenAI used unreleased model to resolve Navier–Stokes Millennium Prize Problem; Tristan Buckmaster disputes Levent Alpöge's role.
OpenAI says it found a solution to a major math problem that has remained unsolved for around 90 years, as reported earlier by The New York Times and Wired. In a blog post on Tuesday, OpenAI announced that it discovered a solution to the Navier-Stokes problem - which relates to…