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Meme generator may have screwed up by using templates in outputs, expert says.

Introducing Monday Microscope Mystery! ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

<p>The offensive potential is no longer theoretical. We need to develop systems to strengthen public health as quickly as AI is accelerating biological design</p><p>As artificial intelligence rapidly transforms the biological sciences, it is pushing the future of biology in two opposing directions. AI can help bad actors generate recipes for biological weapons with just a few keystrokes and computational prompts. At the same time, AI can track disease outbreaks and deliver critical public health

On Monday, the network announced a $1.6 million seed round from top players in the media ecosystem, including Powerhouse Capital, Axel Springer SE (which owns Business Insider and Politico), the popular media publication LadBible, and angel investors from OpenAI and DeepMind. With this fresh capital, the network is announcing its largest expansion yet.

"We hope our paper inspires others to observe Venus." ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

“It’s not an argument with two sides, it’s an argument with 10 sides,” one senior administration official tells WIRED about how US AI policy is being shaped.

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<p> Self-hosted radio with an AI DJ and one shared stream </p> <p> <a href="https://www.producthunt.com/products/sub-wave?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/1207636?app_id=339">Link</a> </p>

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Open source software is a critical pillar of the global economy. It underpins cloud computing, financial services, manufacturing, telecommunications, government and internet services by making technology accessible and observable to communities of experts. Cybersecurity is among the top three beneficiaries of open source software. The Open Secure AI Alliance — building on the leadership of […]

Building a great AI agent isn’t just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes...

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Article URL: https://adcasa.io/ Comments URL: https://news.ycombinator.com/item?id=49066576 Points: 1 # Comments: 0

<p>The academic’s ambitious guide to the ethics of tech falls short of its promise to provide meaningful answers</p><p>The AI ethicist Eleanor Drage believes that to thrive alongside artificial intelligence, humans need to recognise AI’s “humanity”. She means that while we often speak of AI as though it were some mystical, formless thing, it is the product of hours of human labour, in silicon and quartz mines, microchip factories and data labelling centres. If citizens want to wrest power from t

It keeps happening, but not for long. ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

Shared conversations with Anthropic's Claude chatbot briefly appeared in Google search results because the pages lacked a noindex tag. Users said some chats contained crypto keys and legal questions. OpenAI made the same mistake last year. The article Shared Claude chats were reportedly showing up in search engines appeared first on The Decoder .

Hi HN, I've been working on ThorVG, an open-source vector graphics engine. It started as a lightweight SVG renderer and has gradually evolved into a rendering engine supporting SVG, Lottie, and modern GPU backends. This demo showcases the latest ThorVG 1.1 running entirely in the browser. Try it here: https://thorvg-janitor.vercel.app ThorVG v1.1: https://www.thorvg.org/post/thorvg-v1-1-rising-the-standard Comments URL: https://news.ycombinator.com/item?id=49066321 Points: 4 # Comments: 2

Hey HackerNews, I built this project over the last few weeks as a palette cleanser from a failed game launch. I wanted to learn a bit about AI/Neural-Networks and naively thought I could build a tiny maze-solving AI in a weekend with a 100% solve rate. Well - I couldn't, but I got pretty close. 14 Bytes total model size, and a 96.5% solve rate on unseen mazes. Trained across 46 phases experimenting with different ideas to improve the model (better performance, smaller size). Its quite fun to wat

https://seaticket.ai/ Comments URL: https://news.ycombinator.com/item?id=49066066 Points: 2 # Comments: 0

Article URL: https://github.com/YoniRaviv/Relay Comments URL: https://news.ycombinator.com/item?id=49065903 Points: 1 # Comments: 0

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Article URL: https://github.com/CyrusNuevoDia/skill-language-server Comments URL: https://news.ycombinator.com/item?id=49065738 Points: 1 # Comments: 0

<p>Research shows AI accounts are gaining millions of views on TikTok by spreading dubious health advice</p><p>Misleading health claims online pose a “huge danger to public safety”, experts have warned, after research has shown that AI-generated doctors are gaining millions of views on TikTok by spreading dubious health advice.</p><p>The British Medical Association council deputy chair, Dr Emma Runswick, flagged the risks posed by AI accounts that “peddle medical myths and promote so-called mira

Hi HN, I've been working on StatsKit for the past year. It combines product analytics, feature flags, A/B testing, session replay and funnels into a single platform. https://statskit.ai Happy to answer any questions. Comments URL: https://news.ycombinator.com/item?id=49065644 Points: 1 # Comments: 0

It's a really, really big mess we've made. ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

Aug 13 2026 9am-12pm CDT / 10pm-12am SGT. A live tactical decision game with the creator of Tactical Decision Games, John Schmitt. TDGs are an accelerated expertise training format developed for the US Marines. Schmitt has kindly agreed to run a TDG and to take questions from the membership.

Hi guy, I am author of Spur , I want to share the Spur solver which is backed by z3 for neuro-symbolic reasoning, combining probabilistic language models with mathematical constraint solving The ideal here : LLM will give out constranst and translate the constranst to the z3 SMT language, then give out feedback loop between LLM model and neuro-symbolic reasoning to give out better reasioning looking for feedback and comments from HNs Thanks and best regards Kevin Comments URL: https://news.ycomb

arXiv:2607.21596v1 Announce Type: new Abstract: Large language model agents increasingly solve complex tasks by constructing inference-time workflows that combine reasoning, tool use, and code execution. While such workflows enable flexible problem solving, the useful procedures discovered during execution are often transient: they help solve the current task but are not retained in a form that can systematically benefit future tasks. We present FlowEvo, a training-free framework that compiles s

arXiv:2607.21600v1 Announce Type: new Abstract: Multimodal large language models introduce attack surfaces absent in unimodal systems: adversaries can distribute malicious intent across modalities to evade unimodal safeguards. This motivates using cross-modal consistency as a detection signal rather than inspecting each modality in isolation. Our key observation is that benign inputs induce compatible predictive behavior from text-only and vision-only reasoning that stabilizes when fused, wherea

arXiv:2607.21602v1 Announce Type: new Abstract: Accurate latency prediction is critical for deploying large language models (LLMs) on heterogeneous edge devices, where inference latency is affected by model architecture, prompt behavior, runtime backend, hardware utilization, dynamic voltage and frequency scaling (DVFS), and thermal variation. This paper presents a runtime-aware latency prediction framework for deployment-oriented LLM selection. The framework represents each inference request as

arXiv:2607.21604v1 Announce Type: new Abstract: Memory-augmented LLM agents maintain context across hundreds of interactions through agentic memory systems that actively curate retrieved content with LLM-generated metadata such as summaries, keywords, and tags. From an inference cost standpoint, every retrieval triggers a full re-encoding of these structured memory units into Key-Value (KV) states, which dominates prefill latency. Existing training-free KV reuse methods mitigate this by selectiv

arXiv:2607.21606v1 Announce Type: new Abstract: Recent advances in powerful text-to-image generation models have made it increasingly important to develop test-time methods that modify the sampling trajectory to produce images more faithful to complex compositional prompts. We present TILT, a training-free framework for compositional text-to-image generation via test-time reward alignment. We interpret compositional failures as overlap modes between joint and single-concept distributions, and de

arXiv:2607.21607v1 Announce Type: new Abstract: Graph Neural Networks propagate information through local message passing, but the graph topologies themselves can silently prevent any amount of training from solving long-range tasks. When we deploy GNNs on new graphs, there is currently no inexpensive way to know, before training begins, whether the graphs' structures will allow information to travel far enough between distant nodes. We address this gap by proposing Spectral Flow Certificates (S

arXiv:2607.21609v1 Announce Type: new Abstract: Although structured workflows empower Large Language Models (LLMs) to tackle complex problems, automating their creation is severely hindered by a vast combinatorial search space, frequently resulting in inflexible and resource-heavy offline training dependencies. To address this, we conceptualize workflow generation as an intertwined topology-and-execution search paradigm, where the broader topological layer dictates subtask boundaries and lower-l

arXiv:2607.21612v1 Announce Type: new Abstract: Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following, style transfer, and factual adaptation. We show that for procedural knowledge--the ability to follow multi-step procedures with conditional branching through to terminal states--LoRA fails to match full fine-tuning at the ranks where it retains its efficiency advantage. In a systematic ablation (r =

arXiv:2607.21613v1 Announce Type: new Abstract: We investigate where and how transformer-based language models commit to predictions in multiple-choice question answering. We identify the _Hard Decision Layer_ (HDL), a natural architectural property where answer option rankings stabilize abruptly during inference. Empirical validation across four language models (Qwen, Llama, Granite, Mistral) and four benchmark datasets demonstrates consistent HDL emergence without learned routing policies. We

arXiv:2607.21614v1 Announce Type: new Abstract: Entity resolution (ER) typically relies on pairwise similarity comparisons between records, which limits its ability to capture indirect relationships present in demographic occupancy data. An important indirect pattern arises from household movement, where multiple individuals relocate together across addresses, but detecting such patterns is difficult due to mixed-format records, noise, duplication, and the absence of stable identifiers. This pap