llms.
21 writings found
Latest Archives
Qwen 27B Can Read Neural Network Weights Too
A 17GB open model running locally can interpret raw network weights without code execution. What this actually means for AI development.
Qwen 27B Can Interpret Neural Network Weights On My Laptop
A look at weight-space programming claims and what frontier models can actually do with raw neural network parameters without code execution.
LLMs That Sleep: The End of Static Knowledge Cutoffs
Google researchers introduce a sleep framework enabling LLMs to continuously learn and consolidate memories without catastrophic forgetting. Here's what it means for deployed AI systems.
Teaching LLMs to Sleep: A New Path to Continual Learning
How a sleep-inspired framework lets LLMs continuously learn new facts and improve reasoning without catastrophic forgetting or static knowledge cutoffs.
Vibe Coding Games Has Reached an Inflection Point
Claude Opus 5.5 can now generate genuinely fun games with minimal creative input. What does this mean for game development and AI's role in creative work?
Sleep Phases in LLMs: The Case for Continuous Learning
New research introduces a sleep framework for LLMs to continuously learn, consolidate memory, and improve reasoning without catastrophic forgetting.
LFM2.5-24B: Small Models That Actually Reason and Act
Liquid Foundation Models 2.5 brings agent-grade reasoning to 24B parameters with 3x faster inference and stronger tool use than much larger competitors.
Running Local AI Models Changes Everything About Privacy
I'm testing local LLMs on high-end hardware to see if self-hosted AI is worth the investment for real work, not just hype.
Why Dialect-Specialized Models Matter More Than Scale
Falcon-Emirati-7B proves that building for cultural and linguistic specificity beats throwing more parameters at the problem. What this means for LLM development.
Why Dialect-Specialized Models Matter More Than Scale
Falcon-Emirati-7B proves that 7B parameters tuned for a specific dialect outperforms much larger generic models. What this means for localization and AI.
Claude Opus 5.5 and GPT-6 Luna Start a Price War
Anthropic and OpenAI released new models today with aggressive pricing. Here's what it means for building AI applications.
System One Models: Why AI Automation Stayed Broken Until Now
TypeSafe's Jev model addresses the fundamental gap between chat intelligence and production automation. Here's why structured decisions matter more than raw capability.
The Cost of Optimization Has Collapsed
AI has reduced the barrier to performance engineering from weeks to minutes. What does this mean for how we build software?
LLMs Know More Than They Can Access: Why Recall Is the Real Bottleneck
Google Research reveals frontier LLMs encode 95-98% of facts but fail to recall 26-34% of them. The factuality problem isn't knowledge gaps, it's knowledge accessibility.
Science One Framework: Making AI Research Actually Verifiable
Google researchers tackle AI hallucinations in autonomous research with Chain-of-Evidence framework and verifiable evidence chains that eliminate phantom citations.