Category: You Ask I Answer
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You Ask, I Answer: Content Curation Tactics?
In today’s episode, Noel asks about effective content curation strategies, particularly for social media marketing. You’ll learn about both manual and automated methods to curate content, including the use of various tools and systems like SEMRush and Ahrefs. Discover the importance of defining your purpose and measuring performance to make your content curation efforts more…
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You Ask, I Answer: Retrieval Augmented Generation vs Fine-Tuning?
In today’s episode, Jay seeks clarity on the differences between retrieval-augmented generation and fine-tuning in language models. You’ll learn how these techniques compare and contrast, each playing a unique role in enhancing AI’s capabilities. Discover the metaphor of ‘recipes versus ingredients’ to understand how fine-tuning and retrieval-augmented generation can improve your AI’s performance. Tune in…
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You Ask, I Answer: Should Generative AI Be In Your Product?
In today’s episode, Chris inquires about integrating generative AI into complex software products. You’ll learn how to assess whether your product can benefit from AI, especially language models, and understand the importance of internal scripting languages and APIs in this integration. Discover how generative AI can enhance user experience in various applications, from gaming to…
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You Ask, I Answer: Legality of Works in Custom GPTs?
In today’s episode, we tackle a complex and critical topic: the legality of using custom GPT models with copyrighted content. You’ll learn about the potential legal implications and risks of incorporating copyrighted works into your AI models, especially for commercial purposes. Discover expert legal insights on how to navigate this challenging landscape, and understand the…
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You Ask, I Answer: How Not To Use Generative AI In Healthcare?
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…
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You Ask, I Answer: Experimenting with Generative AI?
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…
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You Ask, I Answer: Generative AI Time Savings?
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…
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You Ask, I Answer: Favorite Uses of Generative AI Workflow?
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…
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You Ask, I Answer: Is the Generative AI Space Ripe for Consolidation?
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…
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You Ask, I Answer: Future of Retrieval Augmented Generation AI?
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…