Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer, and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays, and programs; it can be framed as a powerful general problem solver.
Building a Chatbot to Query Your Internal Knowledge Base Using Large Language Models
For over 30 years, a simple text file known as robots.txt has served as an informal agreement among web pioneers, ensuring mutual respect and cooperative development of the internet. Found at the root of a website, this file allows website owners to specify which parts of their site can be accessed by various web crawlers, such as search engines and archival services. However, the rise of AI has challenged this system, as companies use web data to train AI models without necessarily providing reciprocal benefits.
OpenAI's Whisper, an automatic speech recognition (ASR) model, has evolved significantly since 2022. Initially requiring expensive GPUs, developers have now adapted it to run on regular CPUs and even Android phones. This progress is crucial for large language model applications such as ChatGPT and GPT-4.