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Epstein files reveal deeper ties to scientists than previously known

https://www.nature.com/articles/d41586-026-00388-0
1•XzetaU8•4m ago•0 comments

Red teamers arrested conducting a penetration test

https://www.infosecinstitute.com/podcast/red-teamers-arrested-conducting-a-penetration-test/
1•begueradj•11m ago•0 comments

Show HN: Open-source AI powered Kubernetes IDE

https://github.com/agentkube/agentkube
1•saiyampathak•15m ago•0 comments

Show HN: Lucid – Use LLM hallucination to generate verified software specs

https://github.com/gtsbahamas/hallucination-reversing-system
1•tywells•17m ago•0 comments

AI Doesn't Write Every Framework Equally Well

https://x.com/SevenviewSteve/article/2019601506429730976
1•Osiris30•20m ago•0 comments

Aisbf – an intelligent routing proxy for OpenAI compatible clients

https://pypi.org/project/aisbf/
1•nextime•21m ago•1 comments

Let's handle 1M requests per second

https://www.youtube.com/watch?v=W4EwfEU8CGA
1•4pkjai•22m ago•0 comments

OpenClaw Partners with VirusTotal for Skill Security

https://openclaw.ai/blog/virustotal-partnership
1•zhizhenchi•22m ago•0 comments

Goal: Ship 1M Lines of Code Daily

2•feastingonslop•33m ago•0 comments

Show HN: Codex-mem, 90% fewer tokens for Codex

https://github.com/StartripAI/codex-mem
1•alfredray•35m ago•0 comments

FastLangML: FastLangML:Context‑aware lang detector for short conversational text

https://github.com/pnrajan/fastlangml
1•sachuin23•39m ago•1 comments

LineageOS 23.2

https://lineageos.org/Changelog-31/
1•pentagrama•42m ago•0 comments

Crypto Deposit Frauds

2•wwdesouza•43m ago•0 comments

Substack makes money from hosting Nazi newsletters

https://www.theguardian.com/media/2026/feb/07/revealed-how-substack-makes-money-from-hosting-nazi...
2•lostlogin•43m ago•0 comments

Framing an LLM as a safety researcher changes its language, not its judgement

https://lab.fukami.eu/LLMAAJ
1•dogacel•45m ago•0 comments

Are there anyone interested about a creator economy startup

1•Nejana•47m ago•0 comments

Show HN: Skill Lab – CLI tool for testing and quality scoring agent skills

https://github.com/8ddieHu0314/Skill-Lab
1•qu4rk5314•47m ago•0 comments

2003: What is Google's Ultimate Goal? [video]

https://www.youtube.com/watch?v=xqdi1xjtys4
1•1659447091•47m ago•0 comments

Roger Ebert Reviews "The Shawshank Redemption"

https://www.rogerebert.com/reviews/great-movie-the-shawshank-redemption-1994
1•monero-xmr•49m ago•0 comments

Busy Months in KDE Linux

https://pointieststick.com/2026/02/06/busy-months-in-kde-linux/
1•todsacerdoti•50m ago•0 comments

Zram as Swap

https://wiki.archlinux.org/title/Zram#Usage_as_swap
1•seansh•1h ago•1 comments

Green’s Dictionary of Slang - Five hundred years of the vulgar tongue

https://greensdictofslang.com/
1•mxfh•1h ago•0 comments

Nvidia CEO Says AI Capital Spending Is Appropriate, Sustainable

https://www.bloomberg.com/news/articles/2026-02-06/nvidia-ceo-says-ai-capital-spending-is-appropr...
1•virgildotcodes•1h ago•2 comments

Show HN: StyloShare – privacy-first anonymous file sharing with zero sign-up

https://www.styloshare.com
1•stylofront•1h ago•0 comments

Part 1 the Persistent Vault Issue: Your Encryption Strategy Has a Shelf Life

1•PhantomKey•1h ago•0 comments

Show HN: Teleop_xr – Modular WebXR solution for bimanual robot teleoperation

https://github.com/qrafty-ai/teleop_xr
1•playercc7•1h ago•1 comments

The Highest Exam: How the Gaokao Shapes China

https://www.lrb.co.uk/the-paper/v48/n02/iza-ding/studying-is-harmful
2•mitchbob•1h ago•1 comments

Open-source framework for tracking prediction accuracy

https://github.com/Creneinc/signal-tracker
1•creneinc•1h ago•0 comments

India's Sarvan AI LLM launches Indic-language focused models

https://x.com/SarvamAI
2•Osiris30•1h ago•0 comments

Show HN: CryptoClaw – open-source AI agent with built-in wallet and DeFi skills

https://github.com/TermiX-official/cryptoclaw
1•cryptoclaw•1h ago•0 comments
Open in hackernews

How is Google's AI Mode so fast and so good?

5•nthypes•1mo ago
I've been trying out Google's new AI Mode in Search and I'm genuinely curious about the technical architecture behind it. The response times are incredibly fast - often sub-second - and the quality of answers seems consistently high.

What's particularly impressive: - Speed: Near-instant responses even for complex queries - Quality: Accurate, well-sourced answers with citations - Integration: Seamlessly pulls from the knowledge graph and fresh web results

I'm wondering: - What model(s) are they running under the hood? - How are they achieving such low latency at scale? - Are they using some kind of speculative execution or caching strategy? - How does their infrastructure differ from standalone LLM APIs?

For those who've worked on similar systems or have insights into Google's approach, I'd love to hear your thoughts on what makes this possible.