Project Glasswing is World’s Most Powerful AI in Action
We already had a hint. AI would surpass most human capabilities someday. In the field of cybersecurity, that day arrived way too early, with the recent announcement of the Mythos Preview by Claude. The new AI model promises a level of coding skills that it is deemed to ‘surpass all but the most skil...
The Future of AI for Sales Is Diverse and Distributed
True creativity and innovation will come from human-agent collaboration. One human, millions of agents.
The post The Future of AI for Sales Is Diverse and Distributed appeared first on Towards Data Science.
Architecture as Code to Teach Humans and Agents About Architecture
A funny thing happened on the way to writing our book Architecture as Code—the entire industry shifted. Generally, we write books iteratively—starting with a seed of an idea, then developing it through workshops, conference presentations, online classes, and so on. That’s exactly what we did about a...
A Benchmark of Classical and Deep Learning Models for Agricultural Commodity Price Forecasting on A Novel Bangladeshi Market Price Dataset
arXiv:2604.06227v1 Announce Type: new
Abstract: Accurate short-term forecasting of agricultural commodity prices is critical for food security planning and smallholder income stabilisation in developing economies, yet machine-learning-ready datasets for this purpose remain scarce in South Asia. Thi...
Probabilistic Language Tries: A Unified Framework for Compression, Decision Policies, and Execution Reuse
arXiv:2604.06228v1 Announce Type: new
Abstract: We introduce probabilistic language tries (PLTs), a unified representation that makes explicit the prefix structure implicitly defined by any generative model over sequences. By assigning to each outgoing edge the conditional probability of the corres...
FLeX: Fourier-based Low-rank EXpansion for multilingual transfer
arXiv:2604.06253v1 Announce Type: new
Abstract: Cross-lingual code generation is critical in enterprise environments where multiple programming languages coexist. However, fine-tuning large language models (LLMs) individually for each language is computationally prohibitive. This paper investigates...
Spectral Edge Dynamics Reveal Functional Modes of Learning
arXiv:2604.06256v1 Announce Type: new
Abstract: Training dynamics during grokking concentrate along a small number of dominant update directions -- the spectral edge -- which reliably distinguishes grokking from non-grokking regimes. We show that standard mechanistic interpretability tools (head at...
$S^3$: Stratified Scaling Search for Test-Time in Diffusion Language Models
arXiv:2604.06260v1 Announce Type: new
Abstract: Test-time scaling investigates whether a fixed diffusion language model (DLM) can generate better outputs when given more inference compute, without additional training. However, naive best-of-$K$ sampling is fundamentally limited because it repeatedl...
Blind Refusal: Language Models Refuse to Help Users Evade Unjust, Absurd, and Illegitimate Rules
arXiv:2604.06233v1 Announce Type: new
Abstract: Safety-trained language models routinely refuse requests for help circumventing rules. But not all rules deserve compliance. When users ask for help evading rules imposed by an illegitimate authority, rules that are deeply unjust or absurd in their co...
Toward Reducing Unproductive Container Moves: Predicting Service Requirements and Dwell Times
arXiv:2604.06251v1 Announce Type: new
Abstract: This article presents the results of a data science study conducted at a container terminal, aimed at reducing unproductive container moves through the prediction of service requirements and container dwell times. We develop and evaluate machine learn...
Weakly Supervised Distillation of Hallucination Signals into Transformer Representations
arXiv:2604.06277v1 Announce Type: new
Abstract: Existing hallucination detection methods for large language models (LLMs) rely on external verification at inference time, requiring gold answers, retrieval systems, or auxiliary judge models. We ask whether this external supervision can instead be di...
Google AI Research Introduces PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing
Writing a research paper is brutal. Even after the experiments are done, a researcher still faces weeks of translating messy lab notes, scattered results tables, and half-formed ideas into a polished, logically coherent manuscript formatted precisely to a conference’s specifications. For many fresh ...
AI Weekly Issue #481: Musk wants Altman fired, Anthropic passes OpenAI, Meta goes closed
Three seismic shifts in one week. Anthropic's revenue run rate passed OpenAI's — $30 billion to $24 billion — powered by enterprise demand that doubled its million-dollar customers in under two months. Meta launched its first proprietary model under Alexandr Wang's Superintelligence Labs, abandoning...
A Theoretical Framework for Acoustic Neighbor Embeddings
This paper provides a theoretical framework for interpreting acoustic neighbor embeddings, which are representations of the phonetic content of variable-width audio or text in a fixed-dimensional embedding space. A probabilistic interpretation of the distances between embeddings is proposed, based o...
LaCy: What Small Language Models Can and Should Learn is Not Just a Question of Loss
This paper was accepted at the Workshop on Memory for LLM-Based Agentic Systems at ICLR.
Language models have consistently grown to compress more world knowledge into their parameters, but the knowledge that can be pretrained into them is upper-bounded by their parameter size. Especially the capaci...
CyberAgent moves faster with ChatGPT Enterprise and Codex
CyberAgent uses ChatGPT Enterprise and Codex to securely scale AI adoption, improve quality, and accelerate decisions across advertising, media, and gaming.
Meet OSGym: A New OS Infrastructure Framework That Manages 1,000+ Replicas at $0.23/Day for Computer Use Agent Research
Training AI agents that can actually use a computer — opening apps, clicking buttons, browsing the web, writing code — is one of the hardest infrastructure problems in modern AI. It’s not a data problem. It’s not a model problem. It’s a plumbing problem. You need to spin up hundreds, potentially tho...
Better Harness: A Recipe for Harness Hill-Climbing with Evals
By Vivek Trivedy, Product Manager @ LangChain💡TL;DR: We can build better agents by building better harnesses. But to autonomously build a “better” harness, we need a strong learning signal to “hill-climb” on. We share how we use evals as that signal, plus design decisions
Open-weight models are driving the latest excitement in the AI landscape. Running powerful models locally improves privacy, cuts costs, and enables offline use. But the open-source models are far and few! But Google‘s Gemma 4 is here to change that! This guide walks through what Gemma 4 is, would ex...