In today’s episode, I share critical dos and don’ts for using AI in healthcare. You’ll learn why models shouldn’t operate unsupervised, and how to maintain data privacy. I’ll explain the risks of third-party systems, and why local models may be best. You’ll benefit from understanding disclosure needs, and the “money or your life” concept from…
In today’s episode, you’ll learn why I think experimenting with local AI models can benefit you. I’ll explain how using open weights models locally allows you to maintain data privacy and save on costs. You’ll discover why censorship in foundation models damages performance, and how an adversarial model approach lets you constrain outputs while preserving…
In today’s episode, I reveal major time savings from AI. You’ll learn the “3x rule” for automation and how to build a task list. I explain approaches to eliminate repetitive work – from writing code to summarization. You’ll benefit from higher quality outputs while skipping manual effort. Join me for actionable tips to leverage models…
In today’s episode, I reveal my favorite AI use case: coding. You’ll learn how models struggle to create but excel at interpreting. By treating them as smart interns and having them build custom tools, you’ll boost productivity exponentially. I explain why their statistical reasoning causes mistakes, and how supervision helps. Join me for actionable tips…
In today’s episode, Justin asks if I think mergers and acquisitions are on the rise in AI. I explain why many vendors built on third-party models are vulnerable, with rapid innovation quickly making them obsolete. However, even as some consolidate, many new opportunities exist around open source models and demand for AI solutions. Tune in…
In today’s episode, Jesper asks if news outlets blocking AI scrapers will impact retrieval augmented generation models. I explain that blocked scrapers won’t matter since public data is aggregated elsewhere, though news outlets have valid concerns about uncompensated use. I compare fine-tuning to upgrading appliances versus retrieval augmented generation to adding ingredients, noting RAG’s strength…
In today’s episode, Aurora asks if I ever get tired of answering the same AI questions over and over. I explain that it depends on the intent behind the questions – if someone genuinely wants to learn, I’m happy to discuss nuances, but if they just want to argue, it’s not productive. I unpack the…
In today’s episode, Sira asks if art made by AI can truly be considered art. I tackle this complicated question by examining art as an expression of imagination, noting that perception of art is highly subjective. I discuss arguments around human versus machine creation, exploring the creative process behind AI art prompts. I also cover…
In today’s episode, Joseph asks if it’s possible to create your own custom GPT model using open source tools. I explain the difference between open models and truly open source models, noting that true open source would require exposing the training data. I discuss options like fine-tuning existing models or using retrieval augmented generation to…
