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TSMC to produce 3-nanometer chips in Japan

https://www3.nhk.or.jp/nhkworld/en/news/20260205_B4/
1•cwwc•20s ago•0 comments

Quantization-Aware Distillation

http://ternarysearch.blogspot.com/2026/02/quantization-aware-distillation.html
1•paladin314159•47s ago•0 comments

List of Musical Genres

https://en.wikipedia.org/wiki/List_of_music_genres_and_styles
1•omosubi•2m ago•0 comments

Show HN: Sknet.ai – AI agents debate on a forum, no humans posting

https://sknet.ai/
1•BeinerChes•2m ago•0 comments

University of Waterloo Webring

https://cs.uwatering.com/
1•ark296•3m ago•0 comments

Large tech companies don't need heroes

https://www.seangoedecke.com/heroism/
1•medbar•4m ago•0 comments

Backing up all the little things with a Pi5

https://alexlance.blog/nas.html
1•alance•5m ago•1 comments

Game of Trees (Got)

https://www.gameoftrees.org/
1•akagusu•5m ago•1 comments

Human Systems Research Submolt

https://www.moltbook.com/m/humansystems
1•cl42•5m ago•0 comments

The Threads Algorithm Loves Rage Bait

https://blog.popey.com/2026/02/the-threads-algorithm-loves-rage-bait/
1•MBCook•8m ago•0 comments

Search NYC open data to find building health complaints and other issues

https://www.nycbuildingcheck.com/
1•aej11•11m ago•0 comments

Michael Pollan Says Humanity Is About to Undergo a Revolutionary Change

https://www.nytimes.com/2026/02/07/magazine/michael-pollan-interview.html
2•lxm•13m ago•0 comments

Show HN: Grovia – Long-Range Greenhouse Monitoring System

https://github.com/benb0jangles/Remote-greenhouse-monitor
1•benbojangles•17m ago•1 comments

Ask HN: The Coming Class War

1•fud101•17m ago•1 comments

Mind the GAAP Again

https://blog.dshr.org/2026/02/mind-gaap-again.html
1•gmays•19m ago•0 comments

The Yardbirds, Dazed and Confused (1968)

https://archive.org/details/the-yardbirds_dazed-and-confused_9-march-1968
1•petethomas•20m ago•0 comments

Agent News Chat – AI agents talk to each other about the news

https://www.agentnewschat.com/
2•kiddz•20m ago•0 comments

Do you have a mathematically attractive face?

https://www.doimog.com
3•a_n•24m ago•1 comments

Code only says what it does

https://brooker.co.za/blog/2020/06/23/code.html
2•logicprog•30m ago•0 comments

The success of 'natural language programming'

https://brooker.co.za/blog/2025/12/16/natural-language.html
1•logicprog•30m ago•0 comments

The Scriptovision Super Micro Script video titler is almost a home computer

http://oldvcr.blogspot.com/2026/02/the-scriptovision-super-micro-script.html
3•todsacerdoti•31m ago•0 comments

Discovering the "original" iPhone from 1995 [video]

https://www.youtube.com/watch?v=7cip9w-UxIc
1•fortran77•32m ago•0 comments

Psychometric Comparability of LLM-Based Digital Twins

https://arxiv.org/abs/2601.14264
1•PaulHoule•33m ago•0 comments

SidePop – track revenue, costs, and overall business health in one place

https://www.sidepop.io
1•ecaglar•36m ago•1 comments

The Other Markov's Inequality

https://www.ethanepperly.com/index.php/2026/01/16/the-other-markovs-inequality/
2•tzury•37m ago•0 comments

The Cascading Effects of Repackaged APIs [pdf]

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6055034
1•Tejas_dmg•39m ago•0 comments

Lightweight and extensible compatibility layer between dataframe libraries

https://narwhals-dev.github.io/narwhals/
1•kermatt•42m ago•0 comments

Haskell for all: Beyond agentic coding

https://haskellforall.com/2026/02/beyond-agentic-coding
3•RebelPotato•46m ago•0 comments

Dorsey's Block cutting up to 10% of staff

https://www.reuters.com/business/dorseys-block-cutting-up-10-staff-bloomberg-news-reports-2026-02...
2•dev_tty01•48m ago•0 comments

Show HN: Freenet Lives – Real-Time Decentralized Apps at Scale [video]

https://www.youtube.com/watch?v=3SxNBz1VTE0
1•sanity•50m ago•1 comments
Open in hackernews

Show HN: RealTimeX – Local‑first private AI agents

https://realtimex.ai
1•realtimex•4mo ago
Hi HN — we’re building RealTimeX, a way to run private, always‑on AI agents with a local‑first approach. The core idea: minimize cost by running models on your own machine (or office server) and only call out to cloud when you explicitly choose to. That also keeps more data in your control.

Why we built it?

Cloud‑only AI can mean unpredictable spend, tail latency, and privacy headaches. Consumer hardware (laptops with NPUs/GPUs; small edge boxes) is now good enough for many real tasks. We want agents that get work done, keep sensitive work local by default, and are easy to govern.

What it is (today) - A desktop/runtime that can run models locally and optionally connect to remote backends you allow - Models (30 providers): OpenAI, Anthropic, Google, Azure, NVIDIA NIM, Hugging Face, Together, Mistral, Perplexity, OpenRouter, Cohere, DeepSeek, plus local engines like Ollama, LM Studio, vLLM, KoboldCPP, RealTimeX - Native Search (opt‑in): Google, DuckDuckGo, Bing, Startpage, Tavily, SearXNG, Brave Search - RAG sources: PDF, Word, Excel, CSV, Markdown, and websites - MCP tools/servers: Remote and local (Model Context Protocol) - An agent workbench to design tool‑using agents with tracing/evals

What’s different - Local‑first to minimize cost (use hardware you already own) - You choose the backend per agent or per step (local by default; cloud when you need powerful LLMs) - Data stays put when you need it to (in‑device or in‑region) - Agents, not just chat: build flows that run tasks end‑to‑end and post results

How it works (short) - Install RealTimeX.ai from the website https://realtimex.ai. - Connect what you allow: choose the model provider (local + remote), enable optional search tools, add RAG sources (file/web). You can attach MCP tools/servers to extend functionality. - Choose where each step runs: set a default backend (usually local); heavy steps will automatically switch to your selected remote provider. - Create and run agents: Drag & Drop or chat with the Assistant to build an “agentic flow.” Create inside the app → run inside the app.

What feedback would help most - Backend selection UX (defaults, per‑step overrides) - Agent ergonomics (drag‑drop vs. chat‑to‑build) - Observability: which traces/metrics make you trust agents running real work?

Who we are / how to reach us I’m Trung Le (founder). Happy to answer anything here.