Article URL: https://www.wired.com/story/meta-layoffs-bad-vibes-mark-zuckerberg-ai/ Comments URL: https://news.ycombinator.com/item?id=48135782 Points: 22 Comme...

As modern microservice systems grow increasingly complex due to dynamic interactions and evolving runtime environments, they experience failures with rising fre...

Problems defined on binary decision spaces have been intensively studied in the theory of multi-objective evolutionary algorithms (MOEAs). In contrast, no mathe...

have evolved significantly over time, becoming increasingly abstract and easier for humans to understand. In the early days of computing, programmers worked dir...

Dive masks on — Subnautica 2 is making a splash on GeForce NOWhttps://www.nvidia.com/en-us/geforce-now/ day-and-date with launch, so members can plunge into the...

Codex is now in the ChatGPT mobile app so you can stay in the loop from anywhere while Codex gets work done across your laptops, devboxes, or remote environment...

coding agents can be used to quickly create new applications. However, the problem when you create a new application quickly is that you cannot look at the code...

A common critique of neural combinatorial-optimization solvers is that they are less energy-efficient than CPU metaheuristics, given the operational energy cost...

AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers without a...

Context. Behaviour-Driven Development (BDD) software test suites accumulate duplicated step subsequences. Three published refactoring patterns are available (wi...

Automated code documentation is essential for modern software development, providing the contextual grounding that both human developers and coding agents rely ...

Context: Retrieval-augmented code generation relies on cross-file repository context, but retrieved snippets may come from obsolete project states. Objectives: ...

Les entreprises EdTech, autrefois chouchous du marché des investissements dans les startups, connaissent une transformation discrète. Il ne s'agit pas simplemen...

We present Darwin Family, a framework for training-free evolutionary merging of large language models via gradient-free weight-space recombination. We ask wheth...

People come to ChatGPT every day to talk about what matters to them—from everyday questions to more personal or complex conversations. Across hundreds of millio...

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For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is appl...

Good news, OpenClaw fans — you can once again use your Claude AI subscription to power the hit, open source, autonomous AI agentic harness! But, there's a big c...

Anthropic Overtakes OpenAI in U.S. Business Spending For the first time since the AI race began, more American businesses are paying for Anthropic's Claude tha...

situation: You work in the operations team of a medium-sized company. Every day, your team processes order forms from different B2B customers. All of them arriv...

This paper introduces WARDEN, an early language model system capable of transcribing and translating Wardaman, an endangered Australian indigenous language into...

Voice agents, artificial intelligence systems that conduct spoken conversations to complete tasks, are increasingly deployed across enterprise applications. How...

Valiant's 1984 paper is widely credited with introducing the PAC learning model, but it, in fact, introduced a different model: unlike PAC learning, the learner...

Multi-agent LLM systems usually collaborate by exchanging natural-language messages. This interface is simple and interpretable, but it forces each sender's int...

Video-guided 3D animation holds immense potential for content creation, offering intuitive and precise control over dynamic assets. However, practical deploymen...

In this paper, we study solution operators of physical field equations on geometric meshes from a function-space perspective. We reveal that Hodge orthogonality...

Class-Incremental Learning (CIL) enables models to continuously integrate new knowledge while mitigating catastrophic forgetting. Driven by the remarkable gener...

Modeling long-range dependencies in sequential data remains a central challenge in machine learning. Transformers address this challenge through attention mecha...

Long-context modeling is becoming a core capability of modern large vision-language models (LVLMs), enabling sustained context management across long-document u...

Decision tree ensembles (DTE) are a popular model for a wide range of AI classification tasks, used in multiple safety critical domains, and hence verifying pro...

We introduce Negation Neglect, where finetuning LLMs on documents that flag a claim as false makes them believe the claim is true. For example, models are finet...

Scientific machine learning reports predictive performance. It does not report whether the same prediction would survive a different draw of training data. Acro...

Frontier LLMs are increasingly deployed as agents that pick the next action after a long log of prior tool calls produced by the same or a different model. We a...

Elon Musk’s Vision for Space‑Based AI Data Centers Remember Elon Musk’s plan to put AI data centers in spacehttps://mashable.com/article/elon-musk-moon-catapul...

Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, evaluatin...

Natural-language software requirements are often ambiguous, inconsistent, and underspecified; in safety-critical domains, these defects propagate into formal mo...

Digital phenotyping enables continuous passive monitoring of behavior and physiology, offering a promising paradigm for early detection of psychotic relapse. In...

LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that are costl...

Automated CT triage requires models that are simultaneously accurate across diverse pathologies and reliable under institutional shift. While Vision Transformer...

Video temporal grounding (VTG) takes an untrimmed video and a natural-language query as input and localizes the temporal moment that best matches the query. Exi...

As generative AI models such as large language models (LLMs) become more pervasive, ensuring the safety, robustness, and overall trustworthiness of these system...

Cross-modal 3D medical image analysis requires voxelwise representations that remain anatomically consistent across imaging contrasts, scanners, and acquisition...

We present BlitzGS, a distributed 3DGS framework that reduces active Gaussian workload for fast city-scale reconstruction. BlitzGS manages this workload at thre...

Arguments are a fundamental aspect of human reasoning, in which claims are supported, challenged, and weighed against one another. We present an end-to-end larg...

Partial differential equations (PDEs) are fundamental for modeling complex natural and physical phenomena. In many real-world applications, however, observation...

We present MindLab Toolkit (MinT), a managed infrastructure system for Low-Rank Adaptation (LoRA) post-training and online serving. MinT targets a setting where...

Large Language Models (LLMs) are being employed widely to automate tasks across the software development life-cycle. It is, however, unclear whether these tasks...

Large language models hallucinate during multi-step reasoning, but most existing detectors operate at the trace level: they assign one confidence score to a ful...