ChatGPT Desktop (Codex Desktop) for Linux
Article URL: https://openai.com/codex/ Comments URL: https://news.ycombinator.com/item?id=49281916 Points: 17 # Comments: 3
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Celld: Self-hosted, distributed Durable Objects
Article URL: https://celld.dev/ Comments URL: https://news.ycombinator.com/item?id=49281839 Points: 9 # Comments: 0
Grok 4.6 has a great sense of humor 😂
Grok 4.6 has a great sense of humor 😂tobi lutke: I have no idea why but Grok-4.6 just totally freaked out doing some maintenance tasks when…
I think this will turn out to be wrong, and not just because I suspect there are greater returns to more intelligent models than people expect Economi…
I think this will turn out to be wrong, and not just because I suspect there are greater returns to more intelligent models than people expectEconomic…
Nvidia doubles RTX PRO 6000 Blackwell’s MSRP to a staggering $16,000 — 96GB card started pre-orders below $8,000 last year
Given Gavin Bakers recent interview where he says: > Multiple private companies are planning on spending at least 2x more per GPU for compute as contracts…
Patterns and problems in emerging multiagent systems (Anthropic, Frontier Red Team)
Linkpost for some new Anthropic research on how agents coordinate (or don't). Not too long, pretty interesting. For example: The jist of the report is that…
Measuring Eval Awareness: The Realism Win Rate is Fragile
TL;DROne way to assess an evaluation’s realism is by testing a model’s ability to tell its transcripts apart from deployment transcripts. This is the idea behind…
Qwen 3.8Max 2.4t Open Weight NO vision?!?
Qwen, really? Thhe Max Flagship has no Vision, what the heck, really. At 2.4t parameters and no vision? For the size that it is, stuck to…
RT Chris Volzer: my entry into the arena: https://unsession.dev – full sandbox environment – hosted on @Cloudflare (easy to self-host) – full MCP w/ D…
RT Chris Volzermy entry into the arena: https://unsession.dev- full sandbox environment- hosted on @Cloudflare (easy to self-host)- full MCP w/ DCR and API docs...and lots of…
The Descenders and the Absorbers: Two Perspectives on Deep Learning
Once upon a time there were two dissenting factions: the descenders and the absorbers. Both held incomplete but useful worldviews.The descenders lived in the mountains. They…
Self-Geometry: GT-Free and Plug-and-Play Test-Time Adaptation for Geometrically Consistent 3D Vision Foundation Models
Recent Vision Foundation Models (VFMs) predict depth, camera pose, and pointmap in a single forward pass without per-scene optimization, achieving strong generalization. However, enforcing explicit multi-view…
RT Shlok Khemani: My @aiDotEngineer talk on lessons learnt from studying memory systems for a year: > the evolution of chatgpt and claude memory over …
RT Shlok KhemaniMy @aiDotEngineer talk on lessons learnt from studying memory systems for a year:> the evolution of chatgpt and claude memory over the years> their…
Can LLM Agents Stick to the Script? A Benchmark for Long-Horizon Consistency in Interactive Narratives
The rapid advancement of Large Language Models (LLMs) is revolutionizing AI for Games by enabling open-ended and fluid interactive storytelling. However, existing research has largely overlooked…
The Illusion of Visual Tool-Use: A Causal Audit of Thinking with Images
The "thinking-with-images" paradigm equips multimodal LLMs with active visual operations such as crop-and-zoom. However, models using these operations often achieve only marginal or negative gains over…
Post-Training with Policy Gradients: Optimality and the Base Model Barrier
arXiv:2603.06957v2 Announce Type: replace Abstract: We study post-training linear autoregressive models with outcome and process rewards. Given a context $boldsymbol{x}$, the model must predict the response…
A Variational Analysis of Kernel Learning with Learnable Linear Transformations
arXiv:2502.11665v3 Announce Type: replace Abstract: The classical kernel ridge regression problem aims to find the best fit for the output $Y$ as a function of the…
Linear-Core Surrogates: Smooth Loss Functions with Linear Rates for Classification and Structured Prediction
arXiv:2604.27742v2 Announce Type: replace-cross Abstract: A fundamental dichotomy in the theory of classification sets smoothness against statistical efficiency: smooth surrogate losses such as the logistic loss…
Heterogeneous transfer learning for high-dimensional regression with feature mismatch
arXiv:2412.18081v3 Announce Type: replace Abstract: We study Heterogeneous Transfer Learning (HTL) for high-dimensional regression with differing feature sets. Such feature mismatch arises when some variables available…
Confidence Calibration of Deep Learning Systems
arXiv:2608.12100v1 Announce Type: cross Abstract: In high-stakes applications, reliable confidence estimates are as important as the predictions themselves. Confidence calibration ensures that predicted probabilities reflect the…
Kernel Methods for Learning Operators with Multiple Inputs and Outputs
arXiv:2608.11831v1 Announce Type: cross Abstract: Learning mappings between infinite-dimensional objects is a central challenge in scientific machine learning. We introduce a general kernel-based encoder-decoder framework for…
Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems
arXiv:2401.04013v3 Announce Type: replace-cross Abstract: Deep learning models, such as wide neural networks, can be conceptualized as nonlinear dynamical physical systems characterized by a multitude of…
Coarsening Latent-Class Probabilities: Directional Distortion and Coverage Loss
arXiv:2608.11784v1 Announce Type: cross Abstract: Outcomes are increasingly regressed on a calibrated probability vector for unobserved class membership, and that vector is often coarsened to a…
Spectral graph clustering with inhomogeneous latent geometry
arXiv:2608.11321v1 Announce Type: cross Abstract: We study spectral clustering in the presence of a confounding latent geometry. The leading eigenvectors may then be dominated by the…
Stability of Finite-Batch Particle Mean-Field Variational Inference Beyond Strong Convexity
arXiv:2608.11486v1 Announce Type: cross Abstract: We study the implementable finite-batch particle algorithm for mean-field variational inference as a fully discrete stochastic approximation of the projected Wasserstein…