The Abandoned Model Problem Go browse Hugging Face right now and you’ll find thousands of models that haven’t been updated in over a year. Many were state-of-the-art when released. Some still get hundreds of…
The Privacy Paradox of AI Machine learning has a data problem, and it’s not what you think. The issue isn’t that there isn’t enough data—there’s plenty. The problem is that the data is trapped….
When Anyone Can Remove the Guardrails Here’s an uncomfortable truth that the open-source AI community doesn’t love discussing: when you release model weights publicly, you lose all control over how those weights are used….
The Compression Revolution You’ve trained a massive language model. It’s brilliant—answers complex questions, writes elegant code, reasons through multi-step problems. There’s just one problem: it requires eight GPUs to run inference and costs a…
Context windows keep getting bigger. GPT-4 Turbo opened with 128K. Gemini 1.5 Pro claimed 1M tokens. Some models advertise “infinite” context through various tricks. But bigger isn’t always better, and the numbers on the…
Every frontier model released in 2025 and 2026 uses some form of Mixture of Experts. Mixtral proved it works at medium scale. DeepSeek proved it works at massive scale. Grok proved it works for…
Standard attention is quadratic. Every token attends to every other token, making the computational cost grow with the square of the sequence length. At 128K tokens, that’s 16 billion attention computations per layer. The…
In 2022, DeepMind’s Chinchilla paper reshaped the AI industry. The claim: for compute-optimal training, scale parameters and data tokens equally. A 70B model needs ~1.4T tokens. The industry rearranged itself around this law. Then…
Most model cards are useless. They list architecture details nobody needs and skip the information everyone wants: what is this model good at, what is it bad at, and what data was it trained…
Open-source AI has a licensing problem. The term “open source” gets applied to models with wildly different legal terms, from truly permissive Apache 2.0 to restrictive custom licenses that barely qualify as open. Choosing…