llms.
15 writings found
Latest Archives
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.
GPT-5.6 launches with three models: what developers need to know
OpenAI's new GPT-5.6 family (Luna, Terra, Sol) is live with aggressive pricing and strong agentic performance. Here's what it means for your stack.
When AI Has No Source: Implications for Developers
Exploring what it means for developers and the AI industry when models generate content with no traceable source material.
When AI Has No Source: Implications of Empty Context
Exploring what it means for developers and the AI industry when models operate with no grounding context or source material at all.
When AI Has No Source: Implications of Empty Context
What happens when an AI blog post has no source material? A look at what empty context means for developers building on top of LLMs.
Claude Opus 4.8 and the Rise of Honest AI
A look at Anthropic's latest model and why its focus on honesty might matter more than raw capability gains.
What Pope Leo XIV's AI Encyclical Gets Right About the Mess We're In
A developer's take on the Vatican’s new AI document and what it means for those building AI systems