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Study confirms experience beats youthful enthusiasm

https://www.theregister.com/2026/02/07/boomers_vs_zoomers_workplace/

1•Willingham•2m ago•0 comments

The Big Hunger by Walter J Miller, Jr. (1952)

https://lauriepenny.substack.com/p/the-big-hunger

1•shervinafshar•4m ago•0 comments

The Genus Amanita

https://www.mushroomexpert.com/amanita.html

1•rolph•8m ago•0 comments

We have broken SHA-1 in practice

https://shattered.io/

1•mooreds•9m ago•1 comments

Ask HN: Was my first management job bad, or is this what management is like?

1•Buttons840•10m ago•0 comments

Ask HN: How to Reduce Time Spent Crimping?

1•pinkmuffinere•11m ago•0 comments

KV Cache Transform Coding for Compact Storage in LLM Inference

https://arxiv.org/abs/2511.01815

1•walterbell•16m ago•0 comments

A quantitative, multimodal wearable bioelectronic device for stress assessment

https://www.nature.com/articles/s41467-025-67747-9

1•PaulHoule•18m ago•0 comments

Why Big Tech Is Throwing Cash into India in Quest for AI Supremacy

https://www.wsj.com/world/india/why-big-tech-is-throwing-cash-into-india-in-quest-for-ai-supremac...

1•saikatsg•18m ago•0 comments

How to shoot yourself in the foot – 2026 edition

https://github.com/aweussom/HowToShootYourselfInTheFoot

1•aweussom•18m ago•0 comments

Eight More Months of Agents

https://crawshaw.io/blog/eight-more-months-of-agents

3•archb•20m ago•0 comments

From Human Thought to Machine Coordination

https://www.psychologytoday.com/us/blog/the-digital-self/202602/from-human-thought-to-machine-coo...

1•walterbell•21m ago•0 comments

The new X API pricing must be a joke

https://developer.x.com/

1•danver0•22m ago•0 comments

Show HN: RMA Dashboard fast SAST results for monorepos (SARIF and triage)

https://rma-dashboard.bukhari-kibuka7.workers.dev/

1•bumahkib7•22m ago•0 comments

Show HN: Source code graphRAG for Java/Kotlin development based on jQAssistant

https://github.com/2015xli/jqassistant-graph-rag

1•artigent•27m ago•0 comments

Python Only Has One Real Competitor

https://mccue.dev/pages/2-6-26-python-competitor

3•dragandj•28m ago•0 comments

Tmux to Zellij (and Back)

https://www.mauriciopoppe.com/notes/tmux-to-zellij/

1•maurizzzio•29m ago•1 comments

Ask HN: How are you using specialized agents to accelerate your work?

1•otterley•31m ago•0 comments

Passing user_id through 6 services? OTel Baggage fixes this

https://signoz.io/blog/otel-baggage/

1•pranay01•31m ago•0 comments

DavMail Pop/IMAP/SMTP/Caldav/Carddav/LDAP Exchange Gateway

https://davmail.sourceforge.net/

1•todsacerdoti•32m ago•0 comments

Visual data modelling in the browser (open source)

https://github.com/sqlmodel/sqlmodel

1•Sean766•34m ago•0 comments

Show HN: Tharos – CLI to find and autofix security bugs using local LLMs

https://github.com/chinonsochikelue/tharos

1•fluantix•35m ago•0 comments

Oddly Simple GUI Programs

https://simonsafar.com/2024/win32_lights/

1•MaximilianEmel•35m ago•0 comments

The New Playbook for Leaders [pdf]

https://www.ibli.com/IBLI%20OnePagers%20The%20Plays%20Summarized.pdf

1•mooreds•35m ago•1 comments

Interactive Unboxing of J Dilla's Donuts

https://donuts20.vercel.app

1•sngahane•37m ago•0 comments

OneCourt helps blind and low-vision fans to track Super Bowl live

https://www.dezeen.com/2026/02/06/onecourt-tactile-device-super-bowl-blind-low-vision-fans/

1•gaws•38m ago•0 comments

Rudolf Vrba

https://en.wikipedia.org/wiki/Rudolf_Vrba

1•mooreds•39m ago•0 comments

Autism Incidence in Girls and Boys May Be Nearly Equal, Study Suggests

https://www.medpagetoday.com/neurology/autism/119747

1•paulpauper•40m ago•0 comments

Wellness Hotels Discovery Application

https://aurio.place/

1•cherrylinedev•41m ago•1 comments

NASA delays moon rocket launch by a month after fuel leaks during test

https://www.theguardian.com/science/2026/feb/03/nasa-delays-moon-rocket-launch-month-fuel-leaks-a...

2•mooreds•41m ago•0 comments

Open in hackernews

NotebookLM: The AI that only learns from you

https://byandrev.dev/en/blog/what-is-notebooklm

3•byandrev•1h ago

Comments

byandrev•1h ago

Unlike large models such as Gemini or ChatGPT, where information is extracted from numerous web sources that may contain “hallucinations,” NotebookLM relies 100% on the sources you provide, such as PDFs, audio files, YouTube videos, Google Docs, or even articles. By working exclusively with your sources, the tolerance for hallucinations is very low.

knollimar•1h ago

Huh don't most hallucinations come from the models internal knowledge and not the RAG?

burnerToBetOut•16m ago

Please clarify the Google connection.

I'm guessing that it's an official Google-built product. [1]

[1] http://support.google.com/notebooklm/answer/16179536?sjid=62...