simple pre-processing of image can negate the attack without sophisticated approach by tests 4 state-of-the-art latency attacks against varied target AI systems, considering differences like quantization, model size/architecture, defenses, and hardware. https://t.co/kRUPMTyLyv

Just updated the Big LLM Architecture Comparison article... ...it grew quite a bit since the initial version in July 2025, more than doubled! https://t.co/oEt8XzNxik

🧠 Your Personal AI Learning Tutor Is Here! 🎓Stop merely memorizing. In Qwen Learn Mode, Qwen Chat turns information into understanding that actually sticks.Powered by our Qwen3-Max model and grounded in cognitive psychology, it designs a learning path tailored to the way you

AI's next reach is world-building: spatial intelligence that can reconstruct and simulate 3D realities - The Economic Times https://t.co/mc01NqKrOo

📁 Fei Fei Li says that a key breakthrough in generative AI is the next token prediction objective, perfectly aligned with the task of producing language. She adds that vision and world modeling are harder because the real world is multimodal and demands observation,

new theoretical framework identifies the fundamental limits of LLMs, attributing issues like hallucination, context compression, and reasoning degradation to core constraints in computability, information theory, and learning.

Grok-4.1 is god-tier for C programming. I built an ASCII Mario CLI game with pad-based double-buffering, multi-layer rendering, and procedural generation in about 15 minutes! Lots of compute to run emacs and an ASCII game >:D Building a molecular dynamics sim next.

When you train a model on one dataset, it usually performs poorly on data from a different source - even if the task is the same. This paper shows how to train models that automatically learn features that work across different datasets by forcing the network to be unable to

In the future, young people will educate themselves, work for themselves with several AI agents as their assistants, living nomaden between countries, no house mortgage (it won’t be rational to own one), no education debt. They will live on their self-sufficient “house cart”.

If you want to Learn MLops quick and easy without much of hustle, a great way to start is ZenML. It is an open source framework that helps you deploy your models quickly with just a basic python library. The ZenML repo has complete guide, code walkthrough, pipeline and

This repository provides a progressive, first-principles approach to context engineering:

Microsoft just released a framework to train AI Agents with reinforcement learning. Build AI Agents with LangChain, AutoGen, CrewAI or ANY agent framework and optimize with ZERO code changes. 100% open-source. github:

Reinforcement Learning of Large Language Models, Spring 2025(UCLA) Great set of new lectures on reinforcement learning of LLMs. Covers a wide range of topics related to RLxLLMs such as basics/foundations, test-time compute, RLHF, and RL with verifiable rewards(RLVR).

Introducing Grok Imagine v0.9, our new video generation model with massive upgrades from v0.1 in visual quality, motion, audio generation, and more. Try it for free in the Grok App.

Hinton is no longer afraid of superintelligence.

Mark Cuban on the next big job students should focus on: Most companies don’t know how to implement AI, especially small businesses. “Companies don’t understand how to implement AI right now to get a competitive advantage… learn to customize a model, walk into a company, show

Agentic Context Engineering (ACE): a new paradigm that treats an LLM's context as an evolving "playbook," not static input ensures agents preserve crucial detail, learn from failures, & continuously improve performance without losing critical context. https://t.co/WJuZcGATPv

Neuromorphic Computing: Trends, Advances, and Insights from X Discussions This review gives a short, fresh summary of neuromorphic computing trends from X talks, ideal for easy insights into brain-like AI without scattered searches. @ACPaulk @Adhiguna_AIaaS @Alek_Carter

Andrej Karpathy says today's agents aren't ready to work like real coworkers or interns They lack intelligence, can't use computers, aren't multimodal, lack continual learning, and forget what you tell them Fixing these gaps will take about a decade

A small number of samples (250 documents) can poison LLMs of any size.