20 OpenClaw Prompts to Automate Your Daily Life and Work
Autonomous AI agents are easily among the most efficient uses of AI to date. And once you begin to put it to work, OpenClaw shines out as one of the leading enablers of AI automation. If you’ve figured that out by now, here is a list of OpenClaw prompts that will help you do more […]
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Alibaba Releases OpenSandbox to Provide Software Developers with a Unified, Secure, and Scalable API for Autonomous AI Agent Execution
Alibaba has released OpenSandbox, an open-source tool designed to provide AI agents with secure, isolated environments for code execution, web browsing, and model training. Released under the Apache 2.0 license, the proposed system targets to standardize the ‘execution layer’ of the AI agent stack, ...
Transit Network Design with Two-Level Demand Uncertainties: A Machine Learning and Contextual Stochastic Optimization Framework
arXiv:2603.00010v1 Announce Type: new
Abstract: Transit Network Design is a well-studied problem in the field of transportation, typically addressed by solving optimization models under fixed demand assumptions. Considering the limitations of these assumptions, this paper proposes a new framework, ...
CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation
arXiv:2603.00039v1 Announce Type: new
Abstract: LLM-as-a-judge ensembles are the standard paradigm for scalable evaluation, but their aggregation mechanisms suffer from a fundamental flaw: they implicitly assume that judges provide independent estimates of true quality. However, in practice, LLM ju...
Attn-QAT: 4-Bit Attention With Quantization-Aware Training
arXiv:2603.00040v1 Announce Type: new
Abstract: Achieving reliable 4-bit attention is a prerequisite for end-to-end FP4 computation on emerging FP4-capable GPUs, yet attention remains the main obstacle due to FP4's tiny dynamic range and attention's heavy-tailed activations. This paper presents the...
Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
arXiv:2603.00267v1 Announce Type: new
Abstract: Misinformation spreading over the Internet poses a significant threat to both societies and individuals, necessitating robust and scalable fact-checking that relies on retrieving accurate and trustworthy evidence. Previous methods rely on semantic and...
TraderBench: How Robust Are AI Agents in Adversarial Capital Markets?
arXiv:2603.00285v1 Announce Type: new
Abstract: Evaluating AI agents in finance faces two key challenges: static benchmarks require costly expert annotation yet miss the dynamic decision-making central to real-world trading, while LLM-based judges introduce uncontrolled variance on domain-specific ...
DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths
arXiv:2603.00309v1 Announce Type: new
Abstract: The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-purpose large language model (LLM) agents to collaboratively complete complex tasks. While many agentic AI systems utilize predefined workflows or agent ro...
How Well Do Multimodal Models Reason on ECG Signals?
arXiv:2603.00312v1 Announce Type: new
Abstract: While multimodal large language models offer a promising solution to the "black box" nature of health AI by generating interpretable reasoning traces, verifying the validity of these traces remains a critical challenge. Existing evaluation methods are...
EmCoop: A Framework and Benchmark for Embodied Cooperation Among LLM Agents
arXiv:2603.00349v1 Announce Type: new
Abstract: Real-world scenarios increasingly require multiple embodied agents to collaborate in dynamic environments under embodied constraints, as many tasks exceed the capabilities of any single agent. Recent advances in large language models (LLMs) enable hig...
Alibaba just released Qwen 3.5 Small models: a family of 0.8B to 9B parameters built for on-device applications
Alibaba’s Qwen team has released the Qwen3.5 Small Model Series, a collection of Large Language Models (LLMs) ranging from 0.8B to 9B parameters. While the industry trend has historically favored increasing parameter counts to achieve ‘frontier’ performance, this release focuses on ‘More Intelligenc...
Optimizing Recommendation Systems with JDK’s Vector API
By Harshad SaneRanker is one of the largest and most complex services at Netflix. Among many things, it powers the personalized rows you see on the Netflix homepage, and runs at an enormous scale. When we looked at CPU profiles for this service, one feature kept standing out: video serendipity scori...
On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment
With the increased deployment of large language models (LLMs), one concern is their potential misuse for generating harmful content. Our work studies the alignment challenge, with a focus on filters to prevent the generation of unsafe information. Two natural points of intervention are the filtering...
How a HAI Seed Grant Helped Launch a Disease-Fighting AI Platform
Stanford scientists in Senegal hunting for schistosomiasis—a parasitic disease infecting 200+ million people worldwide—used AI to transform local field work into satellite-powered disease mapping.
Learning to Reason for Hallucination Span Detection
Large language models (LLMs) often generate hallucinations — unsupported content that undermines reliability. While most prior works frame hallucination detection as a binary task, many real-world applications require identifying hallucinated spans, which is a multi-step decision making process. Thi...
No one has a good plan for how AI companies should work with the government
As OpenAI transitions from a wildly successful consumer startup into a piece of national security infrastructure, the company seems unequipped to manage its new responsibilities.
Code Less, Ship Faster: Building APIs with FastAPI
Master path operations, Pydantic models, dependency injection, and automatic documentation.
The post Code Less, Ship Faster: Building APIs with FastAPI appeared first on Towards Data Science.
Meet NullClaw: The 678 KB Zig AI Agent Framework Running on 1 MB RAM and Booting in Two Milliseconds
In the current AI landscape, agentic frameworks typically rely on high-level managed languages like Python or Go. While these ecosystems offer extensive libraries, they introduce significant overhead through runtimes, virtual machines, and garbage collectors. NullClaw is a project that diverges from...
OpenAI’s “compromise” with the Pentagon is what Anthropic feared
On February 28, OpenAI announced it had reached a deal that will allow the US military to use its technologies in classified settings. CEO Sam Altman said the negotiations, which the company began pursuing only after the Pentagon’s public reprimand of Anthropic, were “definitely rushed.” In its anno...
Tech workers urge DOD, Congress to withdraw Anthropic label as a supply chain risk
Tech workers have signed an open letter urging the Department of War to withdraw its designation of Anthropic as a "supply chain risk" and instead to settle the matter quietly.
Keebo Appoints Eric Shoemaker as Chief Executive Officer
Keebo, Inc., a pioneer in autonomous cloud data warehouse optimization, today announced the appointment of Eric Shoemaker as Chief Executive Officer. Shoemaker is a seasoned SaaS executive with a proven record of building and scaling high-growth software companies. Most recently, he served as Chief ...