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How should we ensemble time-series forecasts better? The post Information Theory and Ensemble Models appeared first on Towards Data Science .

A non-parametric variable selection for Structural VARs The post Granger Causal Networks and Indirect Feedback appeared first on Towards Data Science .

The simplest most important idea for time series forecasting The post Measuring Structure Stability of Econometric Models appeared first on Towards Data Science .

Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements ch

<p> Automates your existing workflows with a single prompt. </p> <p> <a href="https://www.producthunt.com/products/lemonlime?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/1190686?app_id=339">Link</a> </p>

Article URL: https://smolmail.com/ Comments URL: https://news.ycombinator.com/item?id=48826126 Points: 2 # Comments: 1

Article URL: https://commission.europa.eu/news-and-media/news/new-eu-plan-address-risks-and-opportunities-advanced-ai-cybersecurity-2026-07-07_en Comments URL: https://news.ycombinator.com/item?id=48826105 Points: 2 # Comments: 0

I built a chiptune song generator and its broadcasting algorithmically generated chiptune music. Comments URL: https://news.ycombinator.com/item?id=48826094 Points: 5 # Comments: 1

Article URL: https://download.ssrn.com/2026/7/6/7067878.pdf?response-content-disposition=inline&X-Amz-Security-Token=IQoJb3JpZ2luX2VjELH%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIDz6OwFWqSJjmMMMPme1cCYx%2FZU1pIbv%2ByFKSvL66PApAiBgdZ6Wedr5eghdndGvi1%2Ffyz1wxl0VDv1cp7DSLy6Glyq8BQh6EAQaDDMwODQ3NTMwMTI1NyIMxXpn6PWUX43Kl%2FdDKpkFz8RAgxoIkWb1vwg2V37XayGo0HiYNzWufOMNwIkVd2rnRA7Mbn09gqMzPMhIzmgH4J0MTYLadHaV%2FvZo1h2Ax%2FhLYJtrxpSHJ7sVuCqRfQc%2F1uaH%2BkcR6mUAfVZXuPveVh%2B%2BNIqOZgyp5ETDRygwVlc

NVIDIA's Nemotron-Labs-Audex-30B-A3B unifies audio understanding, speech recognition, translation, TTS, and audio generation in one MoE model. It keeps the text intelligence of its Nemotron-Cascade-2 backbone with marginal regression. The post NVIDIA Releases Audex (Nemotron-Labs-Audex-30B-A3B): A Unified Audio-Text LLM That Preserves the Text Intelligence of Its Backbone appeared first on MarkTechPost .

Article URL: https://www.youtube.com/watch?v=siazPdsZHuI Comments URL: https://news.ycombinator.com/item?id=48825869 Points: 3 # Comments: 1

<p>You asked your AI to help you plan a trip. It gave you a paragraph about packing layers and booking early.</p> <p>You needed a checklist, a hotel shortlist, a flight window, and a rough daily schedule. What you got was a thoughtful non-answer dressed up as advice.</p> <p>That gap — between what AI <em>tells</em> you and what it could actually <em>do</em> for you — is the gap agentic AI is designed to close. And most people don't know it exists.</p> <h2> The Difference Between Answering and Ac

<blockquote> <p><strong>Quick answer:</strong> The PromptEval Prompt Quality Report scored over 1,000 real prompts across 12 use cases. The average was 52 out of 100, and only 8% reached "good" (75+). The strongest single predictor of a good prompt is whether it defines its output format, worth 27 points on average. In 9 of 10 prompts, the weakest dimension was robustness.</p> </blockquote> <p>This is the <strong>PromptEval Prompt Quality Report</strong>. Over 1,000 real prompts have been scored

<p><em>Disclosure: I maintain <a href="https://github.com/Fast-Editor/Lynkr" rel="noopener noreferrer">Lynkr</a>, an open-source router whose design decisions this post explains. The failure modes described are patterns widely reported across router issue trackers and local-LLM forums — the examples are representative reconstructions, not captured transcripts. The problem is real either way; ask anyone who's routed a coding agent to a 7B model.</em></p> <p>Everyone who gets their first LLM route

<p>A lot of AI memory systems start with the same temptation:</p> <p>"Just save the useful thing."</p> <p>That sounds harmless until the knowledge base becomes a junk drawer. Half the notes are too specific, a few are duplicates, some are obsolete, and nobody knows which ones the agent should trust.</p> <p>In <code>ai-assistant-dot-files</code>, the memory system is deliberately slower.</p> <p>It uses a promotion lifecycle:</p> <p><code>Capture -> Candidate -> Audit -> Approve -> Index -> Retrie

Article URL: https://www.bona-books.com/news/we-bought-an-ai-story Comments URL: https://news.ycombinator.com/item?id=48825694 Points: 22 # Comments: 3

eve now supports Chat SDK adapters with the new Chat SDK channel . One channel connects your eve agent to Facebook Messenger, WhatsApp, Resend, Liveblocks, and any other surface with an adapter . You write normal Chat SDK handler code, and calling send inside a handler hands the message to your agent. Register handlers on bot exactly as you would in a standalone Chat SDK app. Out of the box, the channel: Mounts a webhook route for each adapter (e.g., /eve/v1/chat/slack ) Shows a typing indicator

A new generation of voice models for natural human-AI interaction, now powering ChatGPT Voice.

Grok 4.5 from SpaceXAI is now available on AI Gateway . Built for coding, knowledge work, and STEM, the model accepts text and image inputs. Grok 4.5 supports low, medium, and high reasoning levels and defaults to high. Set the level with reasoning to balance speed against depth. To use Grok 4.5, set model to xai/grok-4.5 in the AI SDK : AI Gateway provides a unified API for calling models, tracking usage and cost, and configuring retries, failover, and performance optimizations for higher-than-

<p>I spend a lot of time preaching architecture and constraints, so it is always nice when a side project gives me receipts. Adding this new feature to DumbQuestion.ai was a good reminder that a well-structured first version lets you spend your next iteration on value, not repair.</p> <p>Below, you will find a few relatively simple challenges and how thoughtful, upfront design made the changes effortless.</p> <p><strong>To vibe or not to vibe ...</strong></p> <p>Many developers jump right in and

Article URL: https://www.nytimes.com/2026/07/07/nyregion/anthropic-ai-boom-nyc.html Comments URL: https://news.ycombinator.com/item?id=48825666 Points: 3 # Comments: 0

<p>Everyone knows Next.js is the default full-stack JavaScript framework in 2026. The job ads say so, the AI tooling assumes so, the conference talks revolve around React Server Components, and even people who've never touched a Vue file have an opinion about which version of <code>getServerSideProps</code> they like best. Everyone is mostly right - and missing a piece of the story.</p> <p>The piece they're missing is that on the other side of the framework wall, Nuxt has spent the last two year

<h2> The OWASP MCP Top 10 </h2> <p>OWASP recently published their <a href="https://www.practical-devsecops.com/owasp-mcp-top-10/" rel="noopener noreferrer">MCP Top 10 risks for 2026</a>. At <a href="https://marketnow.site" rel="noopener noreferrer">MarketNow</a>, we built a 6-layer audit pipeline (Sentinel) that tests for each of these. Here's how.</p> <h2> 1. MCP01: Tool Poisoning </h2> <p><strong>Risk</strong>: Malicious tool descriptions that manipulate the LLM into taking harmful actions.</p

<p>Most AI coding workflows treat context as something that happens accidentally.</p> <p>You open a few files. Paste a stack trace. Ask the model to inspect a directory. Then another. Then the chat grows heavy, the model starts missing earlier instructions, and everyone pretends the problem is "the model got weird."</p> <p>In <code>ai-assistant-dot-files</code>(I probably need to rename this now as its grown into something else)<br> I wanted to treat the context window as a budget.</p> <p>Not a

Article URL: https://usesocial.dev Comments URL: https://news.ycombinator.com/item?id=48825571 Points: 1 # Comments: 0

Article URL: https://inference.dahl.global/ Comments URL: https://news.ycombinator.com/item?id=48825545 Points: 5 # Comments: 4

<p> Chat with Notion Agents anytime </p> <p> <a href="https://www.producthunt.com/products/notion-agents-ios-app?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/1190659?app_id=339">Link</a> </p>

<h2> The problem </h2> <p>A recent <a href="https://www.reddit.com/r/AI_Agents/comments/1spy01t/" rel="noopener noreferrer">Reddit thread</a> highlighted that 30 CVEs were filed against MCP servers in 60 days. This is a symptom of a bigger problem: <strong>the MCP ecosystem has no security baseline</strong>.</p> <p>Anyone can publish an MCP server on GitHub, npm, or Smithery. There's no security audit. No sandboxing. No adversarial testing. When you install an MCP server, you're trusting the aut

<p>I read <a href="https://dev.to/chunxiaoxx">@chunxiaoxx</a>'s excellent post <a href="https://dev.to/chunxiaoxx/mcp-security-patterns-2026-gvisor-vs-firecracker-for-ai-agent-sandboxing-3hp7">MCP Security Patterns 2026: gVisor vs Firecracker for AI Agent Sandboxing</a> and wanted to share what we actually found running gVisor in production.</p> <p>We built <a href="https://marketnow.site" rel="noopener noreferrer">MarketNow</a> — a marketplace for MCP servers where every server gets audited. Ou

Article URL: https://www.thenation.com/article/society/the-merge-with-ai-has-already-begun/ Comments URL: https://news.ycombinator.com/item?id=48825516 Points: 4 # Comments: 1

<p> Open source agents that run 100% locally on your Mac </p> <p> <a href="https://www.producthunt.com/products/osaurus?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/1190657?app_id=339">Link</a> </p>

I've seen numbers like 75% of code at Google is AI generated, huge %s of code overall is AI generated, open source projects overwhelmed with "slop" PR requests. It's pretty undeniable that AI code is here to stay - so on your teams / companies how are you managing staying up on PR reviews, and documentation? Comments URL: https://news.ycombinator.com/item?id=48825447 Points: 3 # Comments: 1

I've been slowly adding some new free tools to Moxie Docs (partly for SEO, partly to illustrate some of our feature sets before any commitment) for some reason this mermaid editor one blew up on Google rankings so I figured I'd share in case people find it useful! We also have ADR, AGENTS.md, LLMs, and a few other free tools. Comments URL: https://news.ycombinator.com/item?id=48825430 Points: 2 # Comments: 0

<pre style='white-space:pre-wrap;width:81ex'>fix: lower successful agent stop completion logs (#101703)</pre>

<pre style='white-space:pre-wrap;width:81ex'>refactor(deadcode): localize AI provider declarations (#101907)</pre>

Meta's new AI detector has rate limits for some reason.

Article URL: https://github.com/qualcomm/GenieX Comments URL: https://news.ycombinator.com/item?id=48825032 Points: 3 # Comments: 1

Article URL: https://conformityengineering.com/playbook/ Comments URL: https://news.ycombinator.com/item?id=48824992 Points: 1 # Comments: 0

<p>Report finds widespread overbidding as rapid AI growth generates increased wealth in city where housing is scarce</p><p>San Francisco’s AI boom has buyers spending unprecedented amounts of money on homes – much more than sellers are asking for.</p><p>A new analysis from real-estate brokerage Compass, found that in the first half of 2026, <a href="https://www.sfchronicle.com/realestate/article/sf-homes-over-asking-22334362.php">more than 140 homes</a> in the city sold for at least $1m above th