“It is just as hard to start a small boutique thing that means nothing in the world and build it as it is to build a world dominating monster. It's no more work to do the latter, so we were never interested in anything but the latter.”
e developed an intuition for the problem that allowed him to become more discerning about his next steps. He shifted from exploring the problem in an open-ended way to narrowing in on a solution
AI inference vs. training. Learning through trial and error and applying intuition to the process to narrow the solution.
For the first time in its 65-year history, the Stahl House — Pierre Koenig’s gravity-defying Modernist masterpiece, better known as Case Study House #22 — is officially for sale.
those documents—often, searching in a vector database—is not very sophisticated. If the user asks a complicated or confusing question, there’s a good chance the RAG system will retrieve the wrong documents and the chatbot will return the wrong answer.
change would “disproportionately harm small investors, especially in middle America,” the National Venture Capital Association President Bobby Franklin said in a statement.
hunter-gatherers were the “original affluent society,” with subsistence requiring just some 3-5 hours of work per week. For Sahlins and his peers, agriculture ushered in a regime of ceaseless toil, one that has not been transcended by modern man’s 40-hour work week.
In 2017, Google published “Attention Is All You Need,” one of the most important papers in the history of machine learning. Building on the work of Bahdanau and his colleagues, Google researchers dispensed with the RNN and its hidden states. Instead, Google’s model used an attention mechanism to scan previous words for relevant context.