LLMs

large language models, language model, foundation models, transformer

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Scoured 150 posts in 30.6 ms

DeepSeek V4, LeCun's Bet Against LLMs, and Lovable's Self-Improving Agent - The Tokenizer Edition #30

 🧠AI

Anthropic: Claude Now Writes 80% of Its Own Code in 2026

 🔵Google AI  Content type: Blog
wowhow.cloud··DEV

The Most Emotive Foundation Models for Voice

 🧠AI  Content type: Blog
misolabs.ai··Hacker News

Towards Robust Arabic Speech Emotion Recognition with Deep Learning

 🧠AI  Content type: Academic
arxiv.org·

You’ve Been Using AI for Years. You Just Didn’t Call It That.

 🔵Google AI  Content type: Blog
medium.com·

Introducing Granite Libraries and Project Granite Switch

 ⚙️MLOps  Content type: Blog

Weekly Bookmarks

 🧠AI
inkdroid.org·

Hugging Face Transformers RCE flaw enables stealthy compromise via AI model configs

 🟢OpenAI
csoonline.com·

The Neutral Mask: How RLHF Provides Shallow Alignment while Leaving Partisan Structure Intact in a Large Language Model

 🛡️AI Safety  Content type: Academic
arxiv.org·

Magenta RealTime 2: Open and Local Live Music Models

 🟢OpenAI

Pinterest bets $4 billion on AWS to power AI discovery for 600 million users

 🧠AI
ppc.land·

Learning Fuzzy Logic: Automatic Rule Discovery Through Differentiable Circuits

 🔵Google AI
metafunctor.com··DEV

STAT+: AI titans push Congress for DNA safeguards

 🔵Google AI
statnews.com·

Causal Semantic Alignment for LLM-based Time Series Forecasting

 ✍️Prompt Engineering  Content type: Academic
arxiv.org·

Human-Like Neural Nets by Catapulting

 🧠AI
gwern.net··Hacker News

Claude Mythos Glasswing: Why AI Vuln Discovery Terrifies Me

 🧠AI  Content type: Blog  Content type: Discussion
tildalice.io·

markusheimerl/gpt: A generative pretrained transformer implementation

 🔵Google AI  Content type: Code
github.com··Hacker News

Dynamic Linear Attention

 ⚙️MLOps  Content type: Academic
arxiv.org·

Stack Overflow didn't just help AI learn to code

 🛡️AI Safety

Train your own GPT-2 (124M).

 🔵Google AI  Content type: Blog
medium.com·
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