Using AI Chatbots to examine leaked data
pentestpartners.com·1h
🚨Incident Response
Weeknotes #333 — Man-Wulf
andrewdoran.uk·1d
🇬🇧British Computing
How To Build an AI Health Care Agent on Amazon Bedrock
thenewstack.io·21h
🔌Archive APIs
Code Execution Through Email: How I Used Claude to Hack Itself
pynt.io·1d·
Discuss: Hacker News
🔓Hacking
The Impact of Prompt Bloat on LLM Output Quality
mlops.community·1d·
Discuss: Hacker News
✨Effect Handlers
How Grammarly and Kasta Made Ukraine a Global Clojure Hotspot
hackernoon.com·2d
🧠Lisp Dialects
How I Learned to Stop Worrying and Have Fun with A.I.
nytimes.com·1d·
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⚖️Emulation Ethics
Evaluating Reinforcement Learning Algorithms for Navigation in Simulated Robotic Quadrupeds: A Comparative Study Inspired by Guide Dog Behaviour
arxiv.org·8h
🔲Cellular Automata
Day 28/100: List Comprehensions in Python
dev.to·9h·
Discuss: DEV
📝Concrete Syntax
[P] Understanding Muon: A Revolutionary Neural Network Optimizer
reddit.com·2h·
Discuss: r/MachineLearning
🧠Machine Learning
Are we trading our hard-earned intelligence for convenience?
lmyslinski.com·1d·
Discuss: Hacker News
📏Code Metrics
Demographic-aware fine-grained classification of pediatric wrist fractures
arxiv.org·8h
🌀Differential Geometry
Grok 4: Elon Musk's Bold Gambit to Create the "Smartest AI in the World"
dev.to·2d·
Discuss: DEV
🧠Intelligence Compression
Show HN: I built an SDK for building an AI RAG app with Supabase and pgvector
github.com·1d·
Discuss: Hacker News
🌀Brotli Internals
MUPAX: Multidimensional Problem Agnostic eXplainable AI
arxiv.org·8h
🧠Machine Learning
Building RoastIt: A Social Platform for Fun Image Commentary
dev.to·12h·
Discuss: DEV
🌀Brotli Internals
AI Quietly Getting Stronger: How Many Jobs Has It Already Taken?
dev.to·4h·
Discuss: DEV
🤖AI Translation
Your 92% Accurate AI Model Might Be Dangerous (Here's Why)
dev.to·2h·
Discuss: DEV
🔧Hardware Verification
Eigenvalues and Eigenvectors: Unveiling the Secrets of Data Transformation in Machine Learning
dev.to·3h·
Discuss: DEV
📐Linear Algebra
Time series classification of satellite data using LSTM networks: an approach for predicting leaf-fall to minimize railroad traffic disruption
arxiv.org·1d
🧠Machine Learning