Article URL: https://www.wsj.com/tech/ai/anthropic-mythos-safety-nicholas-carlini-20bceaa3 Comments URL: https://news.ycombinator.com/item?id=48567357 Points: 2 # Comments: 0
Article URL: https://nextweekai.com/blog/claude-code-27-skills-ai-engineering-team/ Comments URL: https://news.ycombinator.com/item?id=48567320 Points: 2 # Comments: 0
He has a lot to say when given the opportunity. ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.
Article URL: https://openreview.net/pdf?id=0wSlFpMsGb Comments URL: https://news.ycombinator.com/item?id=48567122 Points: 3 # Comments: 0
As many as 144 npm packages associated with the Mastra namespace ("@mastra/*"), a popular open-source JavaScript and TypeScript framework for building artificial intelligence (AI) applications, have been compromised as part of a software supply chain attack codenamed easy-day-js, per findings from JFrog, SafeDep, Socket, and StepSecurity. "A single npm account (ehindero) mass-published more
Article URL: https://artificialanalysis.ai/models/glm-5-2 Comments URL: https://news.ycombinator.com/item?id=48567004 Points: 8 # Comments: 0
Fear and even grief are natural reactions to machines that do your job. The next reactions – acceptance and innovation – are more useful
Article URL: https://fig0.ai/ Comments URL: https://news.ycombinator.com/item?id=48566441 Points: 1 # Comments: 0
<p> Computational language built for humans and AI agents </p> <p> <a href="https://www.producthunt.com/products/wolfram-mathematica?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1173951?app_id=339">Link</a> </p>
OpenAI introduced Deployment Simulation on June 16, 2026. The method replays past conversations through a new candidate model before release. It then grades the completions to estimate deployment-time rates of undesired behavior. We break down how the pipeline works, the reported 1.5x median multiplicative error, and its limits. The post OpenAI’s Deployment Simulation Extends Pre-Deployment Risk Assessment to Agentic Coding Through Simulated Tool Calls appeared first on MarkTechPost .
<!-- SC_OFF --><div class="md"><p>Character AI, founded by former Google/LaMDA developers Noam Shazeer and Daniel De Freitas, proved that text-based character chat can work as a real entertainment category.</p> <p>But the next chapter might not be better text chat. It might be real-time video interaction.</p> <p>Mel AI recently shared a demo of AI character video chat, and the interesting part is the interaction stack: voice, lip sync, facial reactions, and camera-aware responses instead of just
Save on iRobot products, including robot vacuums and mops designed to handle pet hair, daily messes, and hands-free cleaning with smart home integration.
If aliens are not here, are they out there? ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.
Article URL: https://finmindai-moneyverse.vercel.app/ Comments URL: https://news.ycombinator.com/item?id=48565890 Points: 2 # Comments: 0
Article URL: https://www.indiehackers.com/post/from-ai-job-board-to-talent-pool-and-hitting-1k-mo-in-6-months-cc99c09d89 Comments URL: https://news.ycombinator.com/item?id=48565888 Points: 2 # Comments: 0
Article URL: https://www.aibrandkits.com Comments URL: https://news.ycombinator.com/item?id=48565727 Points: 2 # Comments: 2
Article URL: https://github.com/josemarpoubel/iaglobal Comments URL: https://news.ycombinator.com/item?id=48565713 Points: 1 # Comments: 0
<p> AI replies that are trained to sound like you </p> <p> <a href="https://www.producthunt.com/products/henji?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1173897?app_id=339">Link</a> </p>
Article URL: https://whissle.ai/gateway Comments URL: https://news.ycombinator.com/item?id=48565618 Points: 1 # Comments: 0
One workflow I like: collecting high-quality research papers on a topic, uploading them to Claude, and turning it into a temporary expert on that domain. Comments URL: https://news.ycombinator.com/item?id=48565600 Points: 5 # Comments: 1
Article URL: https://tenureai.dev/writing/how-ai-memory-breaks-at-scale/ Comments URL: https://news.ycombinator.com/item?id=48565584 Points: 3 # Comments: 1
Article URL: https://www.chatrai.app/ Comments URL: https://news.ycombinator.com/item?id=48565567 Points: 1 # Comments: 0
arXiv:2602.06276v2 Announce Type: replace Abstract: We address the problem of training conversion prediction models in advertising domains under privacy constraints, where direct links between ad clicks and conversions are unavailable. Motivated by privacy-preserving browser APIs and the deprecation of third-party cookies, we study a setting where the learner observes a sequence of clicks and a sequence of conversions, but can only link a conversion to a set of candidate clicks (an attribution s
arXiv:2606.17383v1 Announce Type: cross Abstract: Agentic artificial intelligence systems introduce a new class of model risk. Unlike traditional predictive models, autonomous agents continuously acquire information, form beliefs regarding latent states of the environment, generate forecasts, select actions, and adapt their behavior over time. Existing validation methodologies focus primarily on predictive accuracy and therefore provide limited insight into the quality of the underlying decision
arXiv:2606.17386v1 Announce Type: cross Abstract: End-to-end autonomous driving has achieved state-of-the-art performance on benchmarks and real-world deployments. Its standard training recipe, however, is expensive across all stages: collecting and labeling millions of driving frames is costly, and closed-loop RL on images is bottlenecked by the per-step cost of photorealistic rendering plus a forward pass through a large vision backbone. Self-play in vectorized simulators changes the economics
arXiv:2606.17389v1 Announce Type: cross Abstract: Multimodal Foundation Models are increasingly used as reasoning agents, making reliability, knowing when a model may hallucinate, critical. A common intuition, which we call the Attention-Confidence Assumption, holds that reliability follows from "structural" visual perception: tight attention on relevant regions should signal a trustworthy answer, while scattered attention signals confusion. We challenge this through the VLM Reliability Probe (V
<h2> PAYE, VAT, PIN registration — now accessible via AI agents </h2> <p><code>pip install kra-mcp</code></p> <p>Server #20 in the AI-KungFU East Africa Coordination Infrastructure.</p> <p><a href="https://github.com/gabrielmahia/kra-mcp" rel="noopener noreferrer">GitHub</a></p>
arXiv:2606.17209v1 Announce Type: new Abstract: Test-time scaling for agentic search typically increases depth (i.e., more turns and tokens per trajectory) or breadth (i.e., more parallel rollouts). Here we focus on breadth scaling, showing that standard parallel sampling yields diminishing returns, tracing this to query redundancy at the first turn. When models issue similar first queries across rollouts, the threads retrieve overlapping evidence, and subsequent turns are conditioned on this sh
arXiv:2606.17220v1 Announce Type: new Abstract: Legal case retrieval remains challenging due to the complexity of legal language and the need for precise lexical alignment between queries and relevant cases. Although dense retrieval models have achieved notable progress, empirical studies show that BM25 continues to serve as a strong baseline in this domain. It motivates us to propose a self-evolving framework for rule-driven query rewriting that enhances BM25 without any parameter training. The
arXiv:2606.17269v1 Announce Type: new Abstract: In skill-constrained production-inventory systems, the qualified human capacity available tomorrow depends on training decisions made today: production requires certified workers, certifications decay unless maintained, and training consumes the same scarce worker hours that production needs now. We study a closed-loop skill-constrained model predictive controller that, at every shift, solves a finite-horizon mixed-integer program over production,
arXiv:2606.17289v1 Announce Type: new Abstract: AI systems based on artificial neural networks are being developed with aspirations of pushing the boundary of human mathematical knowledge. A key question for these systems is how much they can reach beyond their training data. Mathematical discovery requires a strong form of out of distribution generalization; the ability to hypothesize genuinely new - and potentially logically more powerful - mathematical structures. It has been hypothesized tha
arXiv:2606.17312v1 Announce Type: new Abstract: Large language models can arrive at the same answer through reasoning paths that are unstable, contradictory, or difficult to rank consistently -- a failure mode especially prevalent in multi-step deductive reasoning. Existing methods assess reliability primarily through output dispersion -- measuring how much sampled answers differ -- but this discards a complementary signal: whether the model can consistently rank competing reasoning candidates.
arXiv:2606.17328v1 Announce Type: new Abstract: LLM agents increasingly maintain long-term memory of user facts across sessions. Yet such memory is usually evaluated by aggregating accuracy over question rows or episodes. Because this approach scores question rows independently, even when several questions probe the same fact, it cannot show how that fact behaves as conditions change. We introduce MemTrace, a benchmark whose unit of measurement is the knowledge point: a single typed fact about t
arXiv:2606.17339v1 Announce Type: new Abstract: Speech offers a uniquely informative window into health by simultaneously engaging neurological, motor, respiratory, and vocal systems. Current clinical speech AI methods have largely progressed through isolated condition-specific studies, making results difficult to compare and generalization difficult to assess. We introduce SpeechDx, a large-scale benchmark for clinical speech AI spanning 12 datasets and 27 tasks across diverse health conditions
arXiv:2606.17368v1 Announce Type: new Abstract: Large language models have accelerated the transition from passive conversational assistants to autonomous agents that can understand goals, plan actions, invoke tools, and execute multi-step tasks. Yet the capability of a single agent remains constrained by its local data, tool permissions, runtime environment, and governance boundary. This paper studies distributed general-purpose agent networks: open peer-to-peer networks in which heterogeneous
arXiv:2606.17405v1 Announce Type: new Abstract: Clinical decision support AI systems (CDSASs) must adapt to evolving patient conditions in real-time while adhering to strict safety constraints. We present an online adaptive framework that integrates Treatment Effect (TE) estimation to quantify clinical benefits, a patient Digital Twin (DT) to simulate treatment trajectories, and Reinforcement Learning (RL) for sequential decision-making. The AI system is initially trained on historical medical r
arXiv:2606.17443v1 Announce Type: new Abstract: Large language models (LLMs) are becoming a major way for consumers to find products, but we do not yet understand how brands compete in this new channel. We study brand dynamics in LLM recommendations using skincare products -- a category where consumers cannot easily judge quality before buying and must rely on brand reputation -- across three commercial LLMs (GPT-4o-mini, Claude Sonnet, Gemini 3 Flash), with a robustness check on search goods. I
arXiv:2606.17453v1 Announce Type: new Abstract: Large language model agents are increasingly integrated into map services. Since map services are embedded in everyday-life scenarios rather than professional task settings, users often express their needs informally, resulting in underspecified queries with many unspoken needs, namely, implicit decision factors that are critical for user satisfaction. Although clarification is an effective way to mitigate this issue, it increases user burden in da
arXiv:2606.17454v1 Announce Type: new Abstract: AI agent performance is not just a modeling problem, it is fundamentally a systems problem. The advanced capabilities of models are realized through agent harnesses. Therefore, a gap between model assumptions and harness behavior can easily prevent the model's full capabilities from translating into agent performance. We formalize this as the `intent-execution' gap: the mismatch between what the model intends and what the harness executes, and vice
