Search: “governance”

This dispatch examines the emerging capabilities and challenges of AI autoresearch systems, analyzing the tension between autonomous AI agents conducting research and the preservation of human agency

Dario just declared war on open-source. Anthropic's message is clear: open source could destroy the entire AI business model, and Chinese open-source models are the cause. I sat down with @jasonlk & @

arXiv:2607.00763v1 Announce Type: cross Abstract: Digital forensic investigations of network intrusions require analytical outputs that are traceable, reproducible, and court-defensible - requirements

arXiv:2607.00926v1 Announce Type: cross Abstract: Generalizing machine learning models to environments that differ from their training distribution remains a critical hurdle, particularly when data fr

arXiv:2607.00026v1 Announce Type: new Abstract: An invariant extended Kalman filter (IEKF) is developed for state estimation of serial rigid manipulators with an arbitrary number of links, formulated

arXiv:2607.00296v1 Announce Type: cross Abstract: Human motion forecasting in unconstrained real-world videos remains challenging due to the ambiguity of future behaviors and the presence of noisy mul

Maggie Eastland / Bloomberg: Letter: chip sector group SEMI, including Micron and Samsung, warns Scott Bessent US policies affecting prices or production capacity would worsen the shortage — Governmen

arXiv:2607.00687v1 Announce Type: cross Abstract: Comparing transformer backbones for image segmentation is confounded: each is paired with a different decoder, recipe, and pretraining, so reported di

arXiv:2511.19326v2 Announce Type: replace Abstract: Reconstructing biomechanically realistic 3D human motion - recovering both kinematics (motion) and kinetics (forces) - is a critical challenge. Whil

Palantir Technologies Inc. Chief Executive Alex Karp appeared to go into meltdown mode during an interview with CNBC today where for 20-odd minutes he went off script after being asked to discuss his

arXiv:2607.01136v1 Announce Type: cross Abstract: Agent skills package reusable operational knowledge for Large Language Model (LLM) agents, yet as they grow in scope, they become dependency-bearing a

arXiv:2607.00095v1 Announce Type: cross Abstract: Generative models have emerged as scalable surrogates for physical simulation, yet they offer no guarantee that their outputs respect the conservation

arXiv:2607.00051v1 Announce Type: cross Abstract: Accurate modeling of wind turbine power curves is crucial for optimal wind farm operation. Nearly all existing power curve models focus on temporal va

arXiv:2607.01083v1 Announce Type: cross Abstract: High-throughput RLHF systems often decouple rollout generation from policy optimization, leading to the use of stale rollouts during learner updates.

Starting in early 2025, Elon Musk and the Trump administration began terminating USAID's programs and firing its staff — with Musk himself boasting about 'feeding it into the woodchipper.' One year ag

This article outlines three key questions organizations should address when scaling AI initiatives from pilot projects to production impact. Based on the Databricks focus, it likely covers questions r

arXiv:2511.18050v1 Announce Type: cross Abstract: Diffusion transformers have recently delivered strong text-to-image generation around 1K resolution, but we show that extending them to native 4K acro

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

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: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

Anthropic: Anthropic says Fable 5 will be available via usage credits for Claude users from July 7, and is working with partners to draft an AI jailbreak severity standard — On Friday, June 12, the US

@anthropicai: Anthropic says “some routine tasks like coding and debugging” on Fable 5 “will fall back to Opus 4.8” in “the near term” as it works to “reduce false positives” — Claude Fable 5 will be

arXiv:2606.30850v1 Announce Type: new Abstract: Large language models (LLMs) are typically deployed in multi-turn conversations, where each turn provides new evidence that should reduce epistemic unce

arXiv:2602.15008v2 Announce Type: replace Abstract: Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this p

I can't verify the specific claims in this post title. The source appears to be a social media post attributed to Yann LeCun discussing Elon Musk's response to criticism regarding DOGE (Department of

arXiv:2511.17979v2 Announce Type: replace Abstract: Diffusion models have achieved remarkable success in generative modeling, yet how to effectively adapt large pretrained models to new tasks remains

arXiv:2606.31522v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous financial agents initialized with explicit behavioral mandates such as 'preserve

Anthropic's agentic coding tool Claude Code has worked with Google Cloud for a while now. An individual developer could easily point CLAUDE_CODE_USE_VERTEX=1 at a Google Cloud (GCP) project, grant the

This Databricks resource explains how to implement granular usage attribution in dbt data transformation pipelines using query tags, enabling detailed tracking of compute resources and costs at a fine

Have seen some questions about the updated classifiers and wanted to clarify. As with the original classifiers, a small fraction of routine coding and debugging tasks will be flagged and fall back to

arXiv:2606.31576v1 Announce Type: new Abstract: The use of ordinary and stochastic differential equations has led to substantial progress in generative machine learning with applications to, for examp

Last year, @elonmusk brought national attention to the paper-based federal retirement process hidden deep underground in Boyers, Pennsylvania. The Last Day of Paper is more than a milestone, it is pro

arXiv:2509.12046v2 Announce Type: replace-cross Abstract: Although autoregressive (AR) models have demonstrated remarkable success in image generation, extending these models to layout-conditioned gen

arXiv:2606.30807v1 Announce Type: cross Abstract: Generative models have recently seen rapid adoption in End-to-End (E2E) autonomous driving (AD), with diffusion-based denoising and vocabulary-based r

arXiv:2606.31025v1 Announce Type: new Abstract: Active flow control is a fundamental application in engineering. Recent advances in deep reinforcement learning have made progress in this field. Howeve

arXiv:2606.31600v1 Announce Type: cross Abstract: Conformal prediction and its variants, including the split conformal prediction, provide a distribution-free framework for uncertainty quantification

arXiv:2606.30932v1 Announce Type: new Abstract: Two-sided marketplaces connect distinct user groups whose interests often conflict -- improving outcomes on one side could degrade the other side's expe

arXiv:2508.09156v3 Announce Type: replace-cross Abstract: We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientifi

arXiv:2606.30650v1 Announce Type: cross Abstract: Educational support services often face a qualified-capacity problem: staff time is scarce, qualifications decay, new support needs can appear before

Really confused by all the excitement I see in my timeline for a nerfed model. Never seen anything like it. So many will end up very disappointed. Time to rethink how to build around frontier and open

arXiv:2506.22075v2 Announce Type: replace Abstract: Reasoning is a hallmark of human intelligence, enabling adaptive decision-making in complex unfamiliar scenarios. In contrast, machine intelligence

arXiv:2606.30822v1 Announce Type: cross Abstract: In this paper, we attempt to enhance the theoretical understanding of convolutional neural networks (CNNs) as feature extractors in classification tas

arXiv:2606.31904v1 Announce Type: new Abstract: The generation of synthetic relational databases often involves modeling complex temporal dynamics, such as transaction logs or event sequences. A signi

arXiv:2606.31963v1 Announce Type: cross Abstract: Modern LLM workflows move coordinate-indexed objects across checkpoints: steering vectors, sparse autoencoders, top-k neuron sets, attribution lists,

arXiv:2602.15029v3 Announce Type: replace-cross Abstract: The internal representations learned by language models consistently exhibit striking geometric structure: calendar months organize into a cir

arXiv:2606.31272v1 Announce Type: cross Abstract: AI agents increasingly acquire and execute skills at runtime: bundles of prompt instructions, executable code, and tool declarations fetched from mark