Knowledge catalogue
You really need your own benchmarks. If you are translating hieroglyphics, use Gemini 3.5 Flash. If you are running a vending machine use Opus 4.8. (This is one reason why I am skeptical of just swapp
You shouldn’t need to think about your memory or agent docs! It should *just work* which was the thesis we went into this with gonna try this out, it seems really cool. banking on this being a better
Your coding agent bill doubled and nobody can tell you why. Here's the actual reason: Claude Code, Cursor, and Copilot all log activity in different formats. The second your team uses more than one (t
Michael Nuñez / VentureBeat: Z.ai launches ZCode, an “Agentic Development Environment” optimized for its new GLM-5.2 model; Z.ai's GLM Coding Plan costs from 16.20 to 144 per month — The move marks th
arXiv:2601.08467v2 Announce Type: replace Abstract: Distracted driving is a major cause of traffic collisions, calling for robust and scalable detection methods. Vision-language models (VLMs) enable s
arXiv:2607.01125v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization enables fine-tuning large language models when backpropagation is unavailable or memory-prohibitive, but existing methods
DSGym is a comprehensive framework designed to evaluate and train AI agents for data science tasks, providing a structured environment for benchmarking agent performance across various data science wo
1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model learns mostly inside its own, by imagining what would happe
ThunderAgent is an agentic inference system designed for fast and efficient execution of AI agent programs, developed by Together AI. The system appears to optimize program-aware inference by leveragi
arXiv:2408.16982v2 Announce Type: replace Abstract: 2D Gaussian Splatting has recently emerged as a significant method in 3D reconstruction, enabling novel view synthesis and geometry reconstruction s
TTT-Discover is a method that enables models to learn and discover patterns during test time rather than only during training, allowing for adaptation to new data distributions at inference. The appro
arXiv:2606.31329v1 Announce Type: cross Abstract: Hierarchical Vision-Language-Action (VLA) models decouple high-level planning from low-level control to improve generalization in robot manipulation.
RARO (Reasoning via Demonstrations) is a method for training AI models to improve reasoning capabilities by learning from demonstrations rather than relying solely on external verifiers. The approach
This paper presents V1, a framework that unifies text generation with self-verification mechanisms to enable parallel reasoning processes in language models. The approach allows models to generate mul
Aurora is a unified training-serving system that integrates reinforcement learning with adaptive speculative training to optimize large language model inference and training efficiency. The system dyn
Untied Ulysses is a memory-efficient technique for context parallelism that processes attention heads in chunks rather than sequences, reducing memory overhead during transformer inference and trainin
Opportunistic Expert Activation (OEA) is a batch-aware expert routing technique for mixture-of-experts models that enables faster decoding without requiring model retraining. The method optimizes whic
ParallelKernelBench is a benchmarking framework designed to evaluate large language models' ability to generate optimized GPU kernels for multi-GPU computing environments. The benchmark assesses LLMs
A basic sigmoid extrapolation suggests that this measurement will be close to its performance ceiling in around a year---meaning most randomly sampled remote work projects would be highly automatable
arXiv:2606.31137v1 Announce Type: new Abstract: This paper proposes a Bayesian filtering-based approach for learning the dynamics of a physical system from partial, noisy measurements. We model the sy
a bit of a teaser for the upcoming talk @aiDotEngineer World's Fair 12:05 pm, Room 2003 Intelligence != Expertise Intelligence + Continual Learning = Expertise I will share some thoughts about continu
arXiv:2606.30688v1 Announce Type: cross Abstract: Symmetry provides a quantum neural network structure, but on its own it does not keep the network trainable once noise is present. We ask which physic
The 2026 Volvo EX30 Cross Country is a small electric SUV that is a joy to drive with a stylish cabin, though the rugged Cross Country variant sacrifices only modest range compared to the standard mod
arXiv:2606.31483v1 Announce Type: new Abstract: Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translati
arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ
Christopher Beam / Bloomberg: A look at Manifest, an annual convention for prediction markets where many purists worry that Kalshi and Polymarket are undermining the technology's public good — At Mani
arXiv:2606.31144v1 Announce Type: cross Abstract: This paper presents an integrated system for the CMU Vision-Language-Action (VLA) Challenge, designed to enable an autonomous agent to perform complex
A once in a lifetime crossover between @aiDotEngineer and @FIFAWorldCup is happening in SF! 100 speakers from AIE got the golden pass to see team USA kick Bosnia's ass!! Thanks @swyx @liamcbride and T
arXiv:2404.10034v3 Announce Type: replace Abstract: Weakly Supervised Object Localization (WSOL) allows training deep learning models for classification and localization (LOC) using only global class-
arXiv:2505.03303v3 Announce Type: replace-cross Abstract: Lightweight convolutional neural networks are often compared using results obtained with different training recipes, input settings, and pretr
Joseph Cox / 404 Media: A researcher says a vulnerability in Apple's Hide My Email tool lets anyone see a user's real email address; first reported in June 2025, Apple has not fixed it — “Hide My Emai
arXiv:2509.15443v2 Announce Type: replace-cross Abstract: Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abun
arXiv:2606.31763v1 Announce Type: new Abstract: Autonomous wet-lab experimentation requires more than plausible protocol text: biological intent, quantitative procedures, device constraints and experi
arXiv:2606.31041v1 Announce Type: new Abstract: Natural language-to-SQL (NL2SQL) over real-world enterprise databases remains significantly more challenging than on academic benchmarks. Enterprise sch
arXiv:2606.30775v1 Announce Type: cross Abstract: Enterprise AI agents route user queries to specialized skills by matching queries against natural language skill descriptions. When two skills share o
The Viking 1 lander used its robotic arm to perform the first Martian soil sample analysis , collecting samples for biological experiments that involved scooping soil and testing it with nutrient solu
arXiv:2606.30837v1 Announce Type: cross Abstract: The number of trees is a central computational parameter in Random Forests: increasing it reduces finite-ensemble variability but increases training a
arXiv:2602.10528v2 Announce Type: replace-cross Abstract: We propose a novel swap-adversarial framework that mitigates high inter-subject variability and the high-dimensional low-sample-size problem i
arXiv:2606.30877v1 Announce Type: cross Abstract: Recent literature shows that large language models (LLMs) are useful for general-purpose tasks yet perform poorly on specific domain ones. One reason
arXiv:2606.31755v1 Announce Type: cross Abstract: Research on artificial intelligence (AI) in the public sector often treats 'AI' as a single category, neglecting technical distinctions between differ
arXiv:2602.20062v2 Announce Type: replace Abstract: Pretraining and fine-tuning are central stages in modern machine learning systems. In practice, feature learning plays an important role across both
arXiv:2606.30997v1 Announce Type: new Abstract: We present a three-phase deep reinforcement learning system for personalized portfolio management that addresses three limitations shared by all prior f
arXiv:2606.31532v1 Announce Type: new Abstract: Staff absenteeism imposes substantial operational costs in high-demand work environments such as healthcare, emergency services, meat processing, constr
arXiv:2606.30842v1 Announce Type: new Abstract: Outbreak transmission reconstruction treats epidemiological timing and transmission labels as deterministic ground truth; neither has been systematicall
arXiv:2606.31635v1 Announce Type: cross Abstract: Fault recovery in process plants still relies heavily on plant operators, especially when faults fall outside predefined supervisory logic. Operators
Andrea Shalal / Reuters: A UN panel co-chaired by Yoshua Bengio warns that AI capabilities are outpacing scientific understanding, the “potential benefits of AI are enormous”, and more — The rapid dev
arXiv:2511.22823v2 Announce Type: replace-cross Abstract: Weakly supervised learning has emerged as a practical alternative to fully supervised learning when complete and accurate labels are costly or
This post by Harrison Chase, creator of LangChain, likely discusses the concept of building specialized wikis or knowledge bases tailored to specific domains using AI and language models. The idea sug
arXiv:2606.31211v1 Announce Type: new Abstract: We present AA, a multi-view multimodal dataset for screen-based gaze estimation. The dataset captures synchronized facial observations from eight fixed
arXiv:2606.31824v1 Announce Type: new Abstract: Long-wave infrared (LWIR) hyperspectral observations contain distance-dependent atmospheric absorption signatures, providing a physical basis for long-r
Dinesh Nair / Bloomberg: Abu Dhabi-based MGX raised a 49B AI-focused fund, exceeding its 45B target, and plans to deploy as much as 10B annually from the fund over the next few years — MGX has raised
arXiv:2606.31204v1 Announce Type: new Abstract: Synthetic data generation has emerged as a powerful tool for improving data scalability in computer vision. Recent diffusion-based pipelines have demons
In this post, we demonstrate how to deploy BoltzGen on SageMaker AI and run an end-to-end protein design experiment. By the end of the walkthrough, you have a working setup that scales from quick vali
arXiv:2606.31323v1 Announce Type: new Abstract: Generating diverse, coherent, and plausible content from partially given inputs remains a fundamental challenge for diffusion models. Existing approache
arXiv:2606.31915v1 Announce Type: cross Abstract: While conformal prediction provides a general framework for uncertainty quantification in predictive inference, its application is often limited by co
arXiv:2606.31084v1 Announce Type: cross Abstract: Merge with Motion Vector Difference (MMVD) is a key coding tool in Versatile Video Coding for improving motion prediction accuracy. However, its exhau
arXiv:2606.30702v1 Announce Type: cross Abstract: Structured tabular data dominates clinical medicine, yet existing benchmarks fail to reflect real-world properties like complex survey sampling, demog
arXiv:2606.31564v1 Announce Type: new Abstract: The increasing complexity of agentic tasks has led to rapidly growing trajectory lengths, which poses significant challenges for large language model (L
arXiv:2606.32026v1 Announce Type: cross Abstract: Latent world models enable planning from high-dimensional observations by predicting future states in a compact latent space. However, these models ar
arXiv:2606.31054v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are critically hampered by hallucination, generating content inconsistent with the provided image. In this pa