Machine Learners Guide to Real World - 2️⃣ Concepts from Operating Systems That Found Their Way in LLMs

Like all machine learning, LLMs turn a logic problem into a statistics problem: instead of people writing the pattern for each possible question by hand, which doesn’t scale, you give the machine a meaningful sample of all the text and data that there is and it works out the patterns for itself, and that does scale (or should do). You get the machi... See more

In general, I see LLMs to be used in two broad categories: data processing, which is more of a worker use-cases, where the latency isn't the biggest issue but rather quality, and in user-interactions, where latency is a big factor. I think for the faster case a faster fallback is necessary. Or you escalate upwards, you first rely on a smaller more ... See more

emerging of LLMs not as a chatbot, but the kernel process of a new Operating System. E.g. today it orchestrates:

- Input & Output across modalities (text, audio, vision)

- Code interpreter, ability to write & run programs

- Browser / internet access

- Embeddings database for files and internal memory storage & retrieval