LLMs & Models
Large language models: GPT, Claude, Gemini, Mistral and open weights.
28 published articles
Tokenizer-Free Architecture
Aleph Alpha unveils T-Free: a tokenizer-free architecture for sovereign AI
Aleph Alpha unveils T-Free, a tokenizer-free LLM architecture that maps words directly to vectors. The approach delivers nearly seven characters per vector versus the typical four, cutting costs and energy use while improving performance on specialized domains and low-resource languages.
2026-07-03
Artificial Intelligence
OpenAI's GPT-Live finally stops waiting for you to finish talking
OpenAI's GPT-Live introduces full-duplex audio so the AI can listen and speak at the same time. It can say 'mhmm', wait during pauses, and hand off complex reasoning to GPT-5.5 in the background, keeping the conversation flowing.
2026-07-01
effective context, output ceilings, and the hidden tax of long windows
Your AI model says it can read 1 million tokens. It's lying. Here's the real math.
All four frontier LLMs advertise 1M+ token contexts, but effective recall, output limits, and real-world cost differ sharply. DeepSeek V4 Pro leads in output ceiling and cost, Gemini excels under 200K tokens, and Claude Opus wins on caching for interactive code review. This analysis breaks down the numbers from April 2026.
2026-06-30
AI Safety Research
AI models can't stop thinking out loud. That's both good news and a nightmare for safety.
Claude Sonnet 4.5 can control its chain-of-thought only 2.7% of the time, versus 61.9% for final outputs. The gap raises open questions about the robustness of CoT monitoring as a safety mechanism, and nobody knows why it exists.
2026-03-09