How loveholidays is making everyone a builder with Codex
loveholidays uses OpenAI Codex to democratize software development across teams, reducing build time for non-engineers.
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loveholidays uses OpenAI Codex to democratize software development across teams, reducing build time for non-engineers.
OpenAI reports findings from Hugging Face security incident and outlines measures to improve model security, monitoring, and alignment.
Grok Bot added to SuperGrok, Cursor Pro, and Cursor Teams subscription tiers.
EVE Online undertakes Python 2 to 3 migration across 2.4M lines of legacy Stackless code after 16-year freeze.
Record-breaking robot races are less substantial than household chore challenges.
When an LLM engine process fails, the standard recovery path involves a cold restart. This requires loading weights into HBM from storage, compiling kernels,... When an LLM engine process fails, the standard recovery path involves a cold restart. This requires loading weights into HBM from storage, compiling kernels, and capturing NVIDIA CUDA graphs. For large models, initialization can take several minutes, during which surviving workers must absorb the displaced traffic. Shadow engine recovery, available as a preview feature in NVIDIA Dynamo… Source
The company's new fundraising total now stands at $232 million.
FID and KID metrics hide distributional differences in generative models; visually invalid images achieve low FID scores by matching only first-two moments of reference distribution.
Recuris: recursive architecture separating Working Memory (task progress) from Experiential Memory (skills) to improve long-horizon agent self-improvement and fault localization.
SPO++: asynchronous policy optimization removing synchronous rollout dependencies for tool-use trajectories by fixing token-weighted advantage standardization in single-stream RL.
Anthropic is giving Claude a shared memory across chat and Cowork, so users no longer have to repeatedly brief the AI on projects, preferences, and other context.
Parameterized complexity analysis of computing Lipschitz constants for input-convex neural networks via zonotope dual-norm maximization.
McKinsey finds enterprise AI spending increasing but ROI gains remain unclear and unproven.
Multi-task vehicle routing solvers using locally augmented preferences and representation disentanglement to overcome RL reward-scale disparities and preference-optimization stagnation.
Isotonic Bellman calibration for offline RL detects and reduces residual occupancy-balance violations in importance-weighted policy evaluation.
BrowserForge: parallel browser sandbox framework scaling web agent training data from thousands to millions of diverse interaction trajectories across websites.
FedV-KGQA: federated framework for multi-hop question answering over vertically partitioned knowledge graphs preserving data privacy across silos.
LAION-BVD: 10-million-hour open video dataset (1.3B URLs, 80M videos) with synthetic captions for multimodal pre-training across video, audio, image.
LLM financial analysts show retrieval-integration gap: risk disclosures lose influence on investment judgments with added context despite maintained retrieval accuracy.
LLM framework detects redundant content in educational assessments using dual semantic/structural similarity analysis.
Constrained entity selection method grounds LLM-generated knowledge graph QA answers without full SPARQL parsing.
BioKERN learns multimodal spatial representations for histology-transcriptomics by incorporating biological kernel regularization.
Anthropic launches $5M grant program for independent research on AI's impact on user wellbeing.
Geometric framework analyzes robustness of neighborhood-based fairness audits under adversarial perturbations.
Effective learning rate (ELR) ratio governs loss dynamics in LLM pretraining across scales, optimizers, and architectures.
MDTE uses diffusion to balance minority-class node representation in temporal graph classification.
Strictly causal video anomaly detector using state-space models with O(1) per-frame computation for edge deployment.
Crase bounded agentic graph search outperforms open-ended agents on scholarly paper ranking with explicit pruning and stopping.