arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researc...
arXiv:2604.04938v1 Announce Type: new Abstract: Metacognition, understood as the monitoring and regulation of one's own cognitive processes, is inherently sequential: an agent evaluates an internal st...
arXiv:2604.04939v1 Announce Type: new Abstract: The paper considers a new quantitative-qualitative proximity measure for the features of information objects, where data enters a common information res...
arXiv:2604.04940v1 Announce Type: new Abstract: Designing effective heuristics for NP-hard combinatorial optimization problems remains a challenging and expertise-intensive task. Existing applications...
arXiv:2604.04941v1 Announce Type: new Abstract: Many combinatorial optimisation problems hide algebraic structures that, once exposed, shrink the search space and improve the chance of finding the glo...
arXiv:2604.05018v1 Announce Type: new Abstract: Synthesizing unstructured research materials into manuscripts is an essential yet under-explored challenge in AI-driven scientific discovery. Existing a...
arXiv:2604.05070v1 Announce Type: new Abstract: Simulation is essential for autonomous driving, yet current frameworks often model vehicles as rigid assets and fail to capture part-level articulation....
arXiv:2604.05075v1 Announce Type: new Abstract: Multi-objective retrosynthesis planning is a critical chemistry task requiring dynamic balancing of quality, safety, and cost objectives. Language model...
arXiv:2604.05081v1 Announce Type: new Abstract: We introduce MedGemma 1.5 4B, the latest model in the MedGemma collection. MedGemma 1.5 expands on MedGemma 1 by integrating additional capabilities: hi...
arXiv:2604.05116v1 Announce Type: new Abstract: Clinical diagnosis requires sequential evidence acquisition under uncertainty. However, most Large Language Model (LLM) based diagnostic systems assume ...
arXiv:2604.05136v1 Announce Type: new Abstract: Fuzzy Cognitive Maps constitute a neuro-symbolic paradigm for modeling complex dynamic systems, widely adopted for their inherent interpretability and r...
arXiv:2604.05142v1 Announce Type: new Abstract: As artificial intelligence systems (AIs) become increasingly produced by recursive self-improvement, a form of evolution may emerge, in which the traits...
arXiv:2604.05157v1 Announce Type: new Abstract: Computer-Use Agents (CUAs) leverage large language models to execute GUI operations on desktop environments, yet they generate actions without evaluatin...
arXiv:2604.05162v1 Announce Type: new Abstract: Reconfigurable Intelligent Surfaces (RIS) are pivotal for next-generation smart radio environments, yet their practical deployment is severely bottlenec...
arXiv:2604.05165v1 Announce Type: new Abstract: Reconfigurable Intelligent Surfaces (RIS) has a potential to engineer smart radio environments for next-generation millimeter-wave (mmWave) networks. Ho...
arXiv:2604.05168v1 Announce Type: new Abstract: Leadership-class HPC systems generate massive volumes of heterogeneous, largely unstructured system logs. Because these logs originate from diverse soft...
arXiv:2604.05172v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evaluatin...
arXiv:2604.05224v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly used to support search and information retrieval, it is critical that they accurately attribute content...
arXiv:2604.05229v1 Announce Type: new Abstract: Agentic AI systems plan, use tools, maintain state, and produce multi-step trajectories with external effects. Those properties create a governance prob...
arXiv:2604.05254v1 Announce Type: new Abstract: Modern logistics networks generate rich operational data streams at every warehouse node and transportation lane -- from order timestamps and routing re...
arXiv:2604.05274v1 Announce Type: new Abstract: Model alignment is currently applied in a vacuum, evaluated primarily through standardised benchmark performance. The purpose of this study is to examin...
arXiv:2604.05279v1 Announce Type: new Abstract: Large language models exhibit sycophancy, the tendency to shift their stated positions toward perceived user preferences or authority cues regardless of...
arXiv:2604.05297v1 Announce Type: new Abstract: Value factorization, a popular paradigm in MARL, faces significant theoretical and algorithmic bottlenecks: its tendency to converge to suboptimal solut...
arXiv:2604.05333v1 Announce Type: new Abstract: Skill usage has become a core component of modern agent systems and can substantially improve agents' ability to complete complex tasks. In real-world s...
arXiv:2604.05336v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed in agentic environments must exercise multiple capabilities across different task instances, where a capability is...
arXiv:2604.05345v1 Announce Type: new Abstract: In today's artificial intelligence driven world, modern systems communicate with people from diverse backgrounds and skill levels. For human-machine int...
arXiv:2604.05348v1 Announce Type: new Abstract: Hallucinations in medical large language models (LLMs) remain a safety-critical issue, particularly when available evidence is insufficient or conflicti...
arXiv:2604.05355v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves large language model performance on complex tasks, but often produces excessively long and inefficient reasoni...
arXiv:2604.05358v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) mitigates hallucination but does not eliminate it: a deployed system must still decide, at inference time, whether ...
arXiv:2604.05364v1 Announce Type: new Abstract: We introduce TFRBench, the first benchmark designed to evaluate the reasoning capabilities of forecasting systems. Traditionally, time-series forecastin...
arXiv:2604.04971v1 Announce Type: new Abstract: While Physics-Informed Neural Networks offer a promising framework for solving partial differential equations, the standard $L^2$ loss formulation is fu...
arXiv:2604.04983v1 Announce Type: new Abstract: We present Territory Paint Wars, a minimal competitive multi-agent reinforcement learning environment implemented in Unity, and use it to systematically...
arXiv:2604.04986v1 Announce Type: new Abstract: Model-free deep reinforcement learning (DRL) methods suffer from poor sample efficiency. To overcome this limitation, this work introduces an adaptive r...
arXiv:2604.04987v1 Announce Type: new Abstract: Speculative sampling (SpS) has been successful in accelerating the decoding throughput of auto-regressive large language models by leveraging smaller dr...
arXiv:2604.04988v1 Announce Type: new Abstract: Modern deployment often requires trading accuracy for efficiency under tight CPU and memory constraints, yet common compression proxies such as paramete...
arXiv:2604.04996v1 Announce Type: new Abstract: Strategically locating a sawmill is vital for enhancing the efficiency, profitability, and sustainability of timber supply chains. Our study proposes a ...
arXiv:2604.04998v1 Announce Type: new Abstract: This paper proposes a novel framework for enhancing the prediction accuracy and lead time of El Ni\~no events, crucial for mitigating their global clima...
arXiv:2604.04999v1 Announce Type: new Abstract: Multimodal self-supervised pretraining offers a promising route to cancer prognosis by integrating histopathology whole-slide images, gene expression, a...
arXiv:2604.05002v1 Announce Type: new Abstract: Learning from weak or proxy supervision is common when ground-truth labels are unavailable, yet robustness under distribution shift remains poorly under...
arXiv:2604.05042v1 Announce Type: new Abstract: Recent advances at the intersection of control theory, neuroscience, and machine learning have revealed novel mechanisms by which dynamical systems perf...
arXiv:2604.05045v1 Announce Type: new Abstract: Multi-channel sensor networks in industrial IoT often exceed available bandwidth. We propose PCA-Triage, a streaming algorithm that converts incremental...
arXiv:2604.05057v1 Announce Type: new Abstract: Blind-spot mass is a Good-Turing framework for quantifying deployment coverage risk in machine learning. In modern ML systems, operational state distrib...
arXiv:2604.05064v1 Announce Type: new Abstract: Synthetic data is essential for training foundation models for time series (FMTS), but most generators assume static correlations, and are typically mis...
arXiv:2604.05068v1 Announce Type: new Abstract: Compute-optimal scaling laws are relatively well studied for NLP and CV, where objectives are typically single-step and targets are comparatively homoge...
arXiv:2604.05072v1 Announce Type: new Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, existi...
arXiv:2604.05077v1 Announce Type: new Abstract: Metal additive manufacturing (AM) enables the fabrication of safety-critical components, but reliable quality assurance depends on high-fidelity sensor ...
arXiv:2604.05112v1 Announce Type: new Abstract: Recent progress in in-context reinforcement learning (ICRL) has demonstrated its potential for training generalist agents that can acquire new tasks dir...
arXiv:2604.05134v1 Announce Type: new Abstract: How can you get a language model to reason in a task it natively struggles with? We study how reasoning evolves in a language model -- from supervised f...
arXiv:2604.05164v1 Announce Type: new Abstract: As LLM reasoning performance plateau, improving inference-time compute efficiency is crucial to mitigate overthinking and long thinking traces even for ...
arXiv:2604.05181v1 Announce Type: new Abstract: Evolution is an extraordinary engine for enzymatic diversity, yet the chemistry it has explored remains a narrow slice of what DNA can encode. Deep gene...
arXiv:2604.05185v1 Announce Type: new Abstract: Model-based reinforcement learning is attractive for sequential decision-making because it explicitly estimates reward and transition models and then su...
arXiv:2604.05187v1 Announce Type: new Abstract: We propose an extended Fourier neural operator (FNO) architecture for learning state and linear quadratic additive optimal control of systems governed b...
arXiv:2604.05195v1 Announce Type: new Abstract: Unlike traditional homogeneous routing problems, the Heterogeneous Fleet Vehicle Routing Problem (HFVRP) involves heterogeneous fixed costs, variable tr...
arXiv:2604.05217v1 Announce Type: new Abstract: Neural language models process sequences of words, but the mathematical operations inside them are insensitive to the order in which words appear. Posit...
arXiv:2604.05230v1 Announce Type: new Abstract: Efficient and robust optimization is essential for neural networks, enabling scientific machine learning models to converge rapidly to very high accurac...
arXiv:2604.05248v1 Announce Type: new Abstract: Large Language Models (LLMs) are typically static after training, yet real-world applications require continual adaptation to new knowledge without degr...
arXiv:2604.05250v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) offer a promising alternative to autoregressive language models by enabling parallel token generation and bidirectional c...
arXiv:2604.05257v1 Announce Type: new Abstract: Diffusion models are increasingly being utilised to create synthetic tabular and time series data for privacy-preserving augmentation. Tabular Denoising...
arXiv:2604.05303v1 Announce Type: new Abstract: Sampling physical systems with rough energy landscapes is hindered by rare events and metastable trapping. While Boltzmann generators already offer a so...
arXiv:2604.05306v1 Announce Type: new Abstract: Large language models are increasingly used in settings where uncertainty must drive decisions such as abstention, retrieval, and verification. Most exi...
With Amazon Bedrock Projects, you can attribute inference costs to specific workloads and analyze them in AWS Cost Explorer and AWS Data Exports. In this post, you will learn how to set up Projects en...
Arcee is a tiny 26-person U.S. startup that built a high-performing, massive, open source LLM. And it's gaining popularity with OpenClaw users.
Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.
On Tuesday, Spotify expanded its Prompted Playlists feature to include podcasts, an update that could make it easier for Premium users to find new shows to listen to. Prompted Playlists were originall...
Nvidia-backed Asia AI data center provider Firmus has now raised $1.35 billion in six months.
Intel will join SpaceX and Tesla in an effort to build a new U.S. semiconductor factory in Texas, although the scope of its contributions are unclear.
Anthropic is debuting a new AI model as part of a cybersecurity partnership with Nvidia, Google, Amazon Web Services, Apple, Microsoft, and other companies. Project Glasswing, as it's called, is bille...
The new model will be used by a small number of high-profile companies to engage in defensive cybersecurity work.
💡 TL;DR: We’ve released new minor versions of deepagents & deepagentsjs , featuring async (non-blocking) subagents, expanded multi-modal filesystem support, and more. See the changelog for details. As...
Uber is expanding its AWS contract to run more of its ride-sharing features on Amazon's chips. This is a thumb-of-the nose at Oracle and Google.
This post walks through building an automated podcast generator that creates engaging conversations between two AI hosts on any topic, demonstrating the streaming capabilities of Nova Sonic, stage-awa...
In this post, we show you how to build a natural text-to-SQL solution using Amazon Bedrock that transforms business questions into database queries and returns actionable answers.
The AI-powered musicmaker Suno is struggling to reach licensing deals with Universal Music Group and Sony Music Entertainment. That's according to a report from the Financial Times, which says both si...
Anthropic bulked up its compute deal with Google and Broadcom as the company has seen its run-rate revenue surge to $30 billion.
Elon Musk's Terafab AI chip project in Austin, Texas, is gaining a crucial new partner: Intel. On Tuesday, the American chipmaker announced it was signing on to help design and build the sprawling fac...
Google is rolling out new features to make it easier for users to contribute local knowledge to Maps. Most notably, Gemini can now create captions when users are looking to share a photo or video abou...
Arcade is the MCP runtime for production agents, delivering secure agent authorization, reliable tools, and governance. This integration gives your agents access to Arcade’s collection of 7,500+ agent...
MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. As the conflict in Ir...
Four days left to save up to $482 on your TechCrunch Disrupt 2026 ticket. These low rates will disappear on April 10 at 11:59 p.m. PT. Register now.
Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically. As they interact with data, systems, people, and other agents in real time, AI agents can execute en...
On a recent episode of Equity, we talked to Arena Private Wealth to explore a growing trend: family offices bypassing VCs to gain direct exposure to AI startups, turning them from passive investors in...
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The one piece of data that could actually shed light on your j...
Google says it has updated Gemini to better direct users to get mental health resources during moments of crisis. The change comes as the tech giant faces a wrongful death lawsuit alleging its chatbot...
PLUS: Stress test business ideas with Perplexity
Rocket's new AI platform combines strategy, product building, and competitive intelligence, aiming to move beyond code generation.
arXiv:2604.03232v1 Announce Type: new Abstract: IC3, also known as property-directed reachability (PDR), is a commonly-used algorithm for hardware safety model checking. It checks if a state transitio...
arXiv:2604.03234v1 Announce Type: new Abstract: The Minimum Set Cover Problem (MSCP) is a classical NP-hard combinatorial optimization problem with numerous applications in science and engineering. Al...
arXiv:2604.03239v1 Announce Type: new Abstract: Six Birds Theory (SBT) treats macroscopic objects as induced closures rather than primitives. Empirical discussions of agency often conflate persistence...
arXiv:2604.03244v1 Announce Type: new Abstract: AI evaluations have become the primary evidence for deploying generative AI systems across high-stakes domains. However, current evaluation paradigms of...
arXiv:2604.03286v1 Announce Type: new Abstract: The control of complex laboratory instrumentation often requires significant programming expertise, creating a barrier for researchers lacking computati...
arXiv:2604.03356v1 Announce Type: new Abstract: Artificial intelligence (AI) alignment is fundamentally a formation problem, not only a safety problem. As Large Language Models (LLMs) increasingly med...
arXiv:2604.03376v1 Announce Type: new Abstract: Current literature on radiology report evaluation has focused primarily on designing LLM-based metrics and fine-tuning small models for chest X-rays. Ho...
arXiv:2604.03387v1 Announce Type: new Abstract: Hume's account of causal judgment presupposes three representational conditions: experiential grounding (ideas must trace to impressions), structured re...
arXiv:2604.03393v1 Announce Type: new Abstract: Multimodal reasoning has emerged as a powerful framework for enhancing reasoning capabilities of reasoning models. While multi-turn table reasoning meth...
arXiv:2604.03479v1 Announce Type: new Abstract: Context-dependent sequential decision making is commonly addressed either by providing context explicitly as an input or by increasing recurrent memory ...
arXiv:2604.03496v1 Announce Type: new Abstract: Knowledge graph construction typically relies either on predefined ontologies or on schema-free extraction. Ontology-driven pipelines enforce consistent...
arXiv:2604.03498v1 Announce Type: new Abstract: Timely discharge prediction is essential for optimizing bed turnover and resource allocation in elective spine surgery units. This study evaluates the f...
arXiv:2604.03506v1 Announce Type: new Abstract: Despite the large corpus of biology training text, the impact of reasoning models on biological research generally lags behind math and coding. In this ...
arXiv:2604.03512v1 Announce Type: new Abstract: Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven decisio...
arXiv:2604.03524v1 Announce Type: new Abstract: Current AI safety relies on behavioral monitoring and post-training alignment, yet empirical measurement shows these approaches produce no detectable pr...
arXiv:2604.03527v1 Announce Type: new Abstract: Modern agentic workflows decompose complex tasks into specialized subtasks and route them to diverse models to minimize cost without sacrificing quality...
arXiv:2604.03533v1 Announce Type: new Abstract: We present an automated crosswalk framework that compares an AI safety policy document pair under a shared taxonomy of activities. Using the activity ca...
arXiv:2604.03553v1 Announce Type: new Abstract: AI is supporting, accelerating, and automating scientific discovery across a diverse set of fields. However, AI adoption in historical research remains ...
arXiv:2604.03557v1 Announce Type: new Abstract: Reasoning hallucinations in large language models (LLMs) often appear as fluent yet unsupported conclusions that violate either the given context or und...
arXiv:2604.03562v1 Announce Type: new Abstract: Adaptive reward design for deep reinforcement learning (DRL) in multi-beam LEO satellite scheduling is motivated by the intuition that regime-aware rewa...
arXiv:2604.03565v1 Announce Type: new Abstract: Can lifetime learning expand behavioral diversity over evolutionary time, rather than collapsing it? Prior theory predicts that plasticity reduces varia...
arXiv:2604.03571v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate structured chains of thought (CoTs) before producing final answers, making them especially vulnerable to knowledg...
arXiv:2604.03588v1 Announce Type: new Abstract: AI agents operating over extended time horizons accumulate experiences that serve multiple concurrent goals, and must often maintain conflicting interpr...
arXiv:2604.03589v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly deployed in edge devices and other resource-constrained settings. However, these models make confide...
arXiv:2604.03630v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables gene expression mapping within anatomical context but remains costly and low-throughput. Hematoxylin and eosin (H\&...
arXiv:2604.03631v1 Announce Type: new Abstract: On-screen learning behavior provides valuable insights into how students seek, use, and create information during learning. Analyzing on-screen behavior...
arXiv:2604.03656v1 Announce Type: new Abstract: Generative Engine Optimization (GEO) is rapidly reshaping digital marketing paradigms in the era of Large Language Models (LLMs). However, current GEO s...
arXiv:2604.03660v1 Announce Type: new Abstract: Structured tables are essential for conveying high-density information in professional domains such as finance, healthcare, and scientific research. Des...
arXiv:2604.03675v1 Announce Type: new Abstract: In agentic search, large language models (LLMs) are trained to perform multi-turn retrieval and reasoning for complex tasks such as multi-hop question a...
arXiv:2604.03742v1 Announce Type: new Abstract: Effective evaluation of large language models (LLMs) remains a critical bottleneck, as conventional direct scoring often yields inconsistent and opaque ...
arXiv:2604.03233v1 Announce Type: new Abstract: The conservation of cultural heritage increasingly relies on integrating technological innovation with domain expertise to ensure effective monitoring a...
arXiv:2604.03240v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding generation in external knowledge, yielding relevance responses t...
arXiv:2604.03242v1 Announce Type: new Abstract: The advent of tool-using LLM agents shifts safety monitoring from output moderation to auditing long, noisy interaction trajectories, where risk-critica...
arXiv:2604.03321v1 Announce Type: new Abstract: Machine learning, especially physics-informed neural networks (PINNs) and their neural network variants, has been widely used to solve problems involvin...
arXiv:2604.03335v1 Announce Type: new Abstract: Apparent age estimation is a valuable tool for business personalization, yet current models frequently exhibit demographic biases. We review prior works...
arXiv:2604.03336v1 Announce Type: new Abstract: BitNet b1.58 (Ma et al., 2024) demonstrates that large language models can operate entirely on ternary weights {-1, 0, +1}, yet no native binary wire fo...
arXiv:2604.03344v1 Announce Type: new Abstract: Electricity theft and non-technical losses (NTLs) remain critical challenges in modern smart grids, causing significant economic losses and compromising...
arXiv:2604.03345v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) have recently emerged as a powerful architecture for various machine learning applications. However, their unique stru...
arXiv:2604.03350v1 Announce Type: new Abstract: Systematic exploration of Agent-Based Models (ABMs) is challenged by the curse of dimensionality and their inherent stochasticity. We present a multi-st...
arXiv:2604.03361v1 Announce Type: new Abstract: The modeling of bio-molecular system across molecular scales remains a central challenge in scientific research. Large language models (LLMs) are increa...
arXiv:2604.03388v1 Announce Type: new Abstract: When deploying large language models (LLMs) to safety-critical applications, uncertainty quantification (UQ) is of utmost importance to self-assess the ...
arXiv:2604.03417v1 Announce Type: new Abstract: Network visualization has traditionally relied on heuristic metrics, such as stress, under the assumption that optimizing them leads to aesthetic and in...
arXiv:2604.03419v1 Announce Type: new Abstract: Submodular maximization under matroid constraints is a fundamental problem in combinatorial optimization with applications in sensing, data summarizatio...
arXiv:2604.03427v1 Announce Type: new Abstract: State-space model (SSM) for time-series forecasting have demonstrated strong empirical performance on benchmark datasets, yet their robustness under adv...
arXiv:2604.03436v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are increasingly used for safety-relevant applications including alignment detection and model steering. These use cases requ...
arXiv:2604.03444v2 Announce Type: new Abstract: Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid models that...
arXiv:2604.03449v1 Announce Type: new Abstract: Neural operator methods have emerged as powerful tools for learning mappings between infinite-dimensional function spaces, yet their potential in optima...
arXiv:2604.03456v1 Announce Type: new Abstract: Conventional urban indicators derived from censuses, surveys, and administrative records are often costly, spatially inconsistent, and slow to update. R...
arXiv:2604.03463v1 Announce Type: new Abstract: In highly interactive driving scenes, trajectory prediction is conditioned on information from surrounding traffic participants such as cars and pedestr...
arXiv:2604.03478v1 Announce Type: new Abstract: In high-stakes settings where machine learning models are used to automate decision-making about individuals, the presence of algorithmic bias can exace...
arXiv:2604.03489v1 Announce Type: new Abstract: Enforcing complex (e.g., nonconvex) operational constraints is a critical challenge in real-world learning and control systems. However, existing method...
arXiv:2604.03525v1 Announce Type: new Abstract: We study adversarial online learning of real-valued functions on $\mathbb{R}$. In each round the learner is queried at $x_t\in\mathbb{R}$, predicts $\ha...
arXiv:2604.03541v2 Announce Type: new Abstract: This study surveys the historical development of regularization, tracing its evolution from stepwise regression in the 1960s to recent advancements in f...
arXiv:2604.03582v1 Announce Type: new Abstract: Neural operators have emerged as data-driven surrogates for solving partial differential equations (PDEs), and their success hinges on efficiently model...
arXiv:2604.03599v1 Announce Type: new Abstract: For a larger set of predictions of several differently trained machine learning models, known as bagging predictors, the mean of all predictions is take...
arXiv:2604.03606v1 Announce Type: new Abstract: Federated learning (FL) research increasingly relies on single-node simulations with hundreds or thousands of virtual clients, making both efficiency an...
arXiv:2604.03614v1 Announce Type: new Abstract: Global optimization of black-box functions from noisy samples is a fundamental challenge in machine learning and scientific computing. Traditional metho...
arXiv:2604.03634v1 Announce Type: new Abstract: We prove that temporal averaging over multiple observations can be replaced by algebraic group action on a single observation for second-order statistic...
arXiv:2604.03641v1 Announce Type: new Abstract: Reinforcement learning in real-world systems is often accompanied by delayed feedback, which breaks the Markov assumption and impedes both learning and ...
arXiv:2604.03764v1 Announce Type: new Abstract: Large language models have found success by scaling up capabilities to work in general settings. The same can unfortunately not be said for interpretabi...
Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.
Zero Shot, a new venture capital fund with deep ties to OpenAI, is aiming to raise $100 million for its first fund. It has already written some checks.
Google's new offline-first dictation app uses Gemma AI models to take on the apps like Wispr Flow.
Iran said it will target U.S.-linked data centers with new missile strikes, as the war between the U.S. and Iran escalates.
In this post, we walk through building a custom HR onboarding agent with Quick. We show how to configure an agent that understands your organization’s processes, connects to your HR systems, and autom...
In this post, we walk through how we fine-tuned Qwen 2.5 7B Instruct for tool calling using RLVR. We cover dataset preparation across three distinct agent behaviors, reward function design with tiered...
In this post, we show how to implement a generative AI agentic assistant that uses both semantic and text-based search using Amazon Bedrock, Amazon Bedrock AgentCore, Strands Agents and Amazon OpenSea...
This blog post demonstrates how Windward helps enhance and accelerate alert investigation processes by combining geospatial intelligence with generative AI, enabling analysts to focus on decision-maki...
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Within Silicon Valley’s orbit, an AI-fueled jobs apocalypse is...
OpenAI proposes taxes on AI profits, public wealth funds, and expanded safety nets to address job loss and inequality, blending redistribution with capitalism as policymakers debate AI’s economic impa...
Iran's Islamic Revolutionary Guard Corps (IRGC) has published a video threatening OpenAI's planned Abu Dhabi data center if the US follows through on threats to attack the country's power plants, as r...
Today, I’m talking with Chuck Robbins, CEO of Cisco. Cisco is one of those big companies that everyone has heard of but that most of us don’t have to interact with very much; it’s not really a consume...
Amazon Bedrock AgentCore Gateway provides a centralized layer for managing how AI agents connect to tools and MCP servers across your organization. In this post, we walk through how to configure Agent...
Nominate your startup, or one you know that deserves the spotlight, and finish the process by applying. Selected 200 have a chance at VC access, TechCrunch coverage, and $100K for Startup Battlefield ...
Learn how to use Spotify, Canva, Figma, Expedia, and other apps directly in ChatGPT.
Starting today, you have 5 days to save nearly $500 on your ticket to TechCrunch Disrupt 2026. This offer disappears Friday, April 10, at 11:59 p.m. PT. Register here to secure these low rates.
The company is also announcing a deal with L3Harris to build the sensors for Xoople's spacecraft.
How much could AI revolutionize the economy?
For years Mike McClary sold the Guardian LTE Flashlight, a heavy-duty black model, online through his small outdoor brand. The product, designed for brightness and durability, became one of his most p...
A pilot program to support independent safety and alignment research and develop the next generation of talent
PLUS: How to take AI notes on phone calls
Explore our ambitious, people-first industrial policy ideas for the AI era—focused on expanding opportunity, sharing prosperity, and building resilient institutions as advanced intelligence evolves.
Most discussions of continual learning in AI focus on one thing: updating model weights. But for AI agents, learning can happen at three distinct layers: the model, the harness, and the context. Under...
AI skeptics aren’t the only ones warning users not to unthinkingly trust models’ outputs — that’s what the AI companies say themselves in their terms of service.
AI music platform Suno's policy is that it does not permit the use of copyrighted material. You can upload your own tracks to remix or set your original lyrics to AI-generated music. But, it's suppose...
On the latest episode of TechCrunch’s Equity podcast, we debated Elon Musk's vision for data centers in space.
You may be familiar with Gemini as the thing that's in every Google service you use - whether you want it or not. While it's been a constant, sometimes unwelcome presence in Gmail for at least the pas...
This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on the ups and downs of AI, follow Stevie Bonifield. The Stepback arrives in our subscribers' ...
How coding agents use tools, memory, and repo context to make LLMs work better in practice
Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.
MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. In January, Elon Musk...
I built a self-healing deployment pipeline for our GTM Agent. After every deploy, it detects regressions, triages whether the change caused them, and kicks off an agent to open a PR with a fix, with n...
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💡 TL;DR: Open models like GLM-5 and MiniMax M2.7 now match closed frontier models on core agent tasks — file operations, tool use, and instruction following — at a fraction of the cost and latency. He...
In this post, we explore how ActorSimulator in Strands Evaluations SDK addresses the challenge with structured user simulation that integrates into your evaluation pipeline.
Gemma 4: Our most intelligent open models to date, purpose-built for advanced reasoning and agentic workflows.
Gemini API Dials
Google Vids logo surrounded by various video editing UI
This post describes how TGS achieved near-linear scaling for distributed training and expanded context windows for their Vision Transformer-based SFM using Amazon SageMaker HyperPod. This joint soluti...
In this post, we show you how to configure AWS Network Firewall to restrict AgentCore resources to an allowlist of approved internet domains. This post focuses on domain-level filtering using SNI insp...
Through a strategic partnership with the AWS Generative AI Innovation Center (GenAIIC), Rocket Close developed an intelligent document processing solution that has significantly reduced processing tim...
In this post, we go through how to use managed session storage to persist your agent's filesystem state and how to execute shell commands directly in your agent's environment.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Fuel prices are soaring. Plastic could be next. As the war in ...
OpenAI acquires TBPN to accelerate global conversations around AI and support independent media, expanding dialogue with builders, businesses, and the broader tech community.
As the war in Iran continues to engulf the Middle East and the Strait of Hormuz stays closed, one of the most visible global economic ripple effects has been fossil-fuel prices. In particular, you can...
Codex now includes pay-as-you-go pricing for ChatGPT Business and Enterprise, providing teams a more flexible option to start and scale adoption.
PLUS: Build a productivity tool with Replit
MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.
It feels like spring has sprung here, and so has a new NVIDIA integration, ticket sales for Interrupt 2026, and announcing LangSmith Fleet (formerly Agent Builder).
This post demonstrates how to build an automated competitive price intelligence system that streamlines manual workflows, supporting teams to make data-driven pricing decisions with real-time market i...
Google partnered with the Brazilian government on a satellite imagery map to help protect the country’s forests.
March 2026 AI Recap showing new updates
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The gig workers who are training humanoid robots at home When ...