The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) · Why Jev Is Changing How We Build With AI with Diogo Almeida
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Argue that pre-training large language models is sub-linear in returns and not the most efficient use of budget
“What we tried to do is, you know, using large language models and AI, we tried to really ground probability of success in an empiric data set, where we use Bayesian statistics.”
“If you can get that information and you can turn that unstructured data into semi-structured data and connect it to the prediction, then you can use the storytelling power of the large language models”
“Any language that compiles to WebAssembly can be used... the two most popular languages are Rust and Motoko.”
“We try to keep it around 8 to 10% for most of our businesses… we take their marketing budget down when we need to get them more efficient with their calls.”
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