A machine learning literature review (ML syllabus edition 2/8)Listen now | You can find a lot of quality explanations of the differences between the various flavors of machine learning [1]. This second lecture in…
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Comparative analysis of national AI strategiesListen now | This topic really has me conflicted about how to approach consideration of what a national AI strategy really entails. Within that conflict…
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A machine learning cookbook?Listen now (7 min) | Don’t panic! We are going to take this topic in two different directions this week. First, the obvious path will be taken and we…
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Touching the singularityListen now | For years it has been a running joke with some of my close friends that I have been perpetually writing a book about the intersection of…
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Sentiment and consensus analysisListen now | Thank you for tuning in to this audio only podcast presentation. This is week 63 of The Lindahl Letter publication. A new edition arrives…
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My thoughts on NFTsListen now | Things got shuffled around a little bit and instead of hearing about, “Who still does ML tooling by hand?,” this week my attention shifted…
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Publishing a model or selling the API?Listen now | Both OpenAI and Hugging Face have teams doing great things with respect to machine learning models. Their delivery models are very…
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Why is diffusion so popular?Listen now | Transformers were the thing. They were a big thing in the machine learning field. It was glorious. People talked about them a lot and…
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The future of machine learning
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Bayesian optimization (ML syllabus edition 1/8)Listen now | You might remember the Substack post from week 57 titled, “How would I compose an ML syllabus?” We have now reached the point in the…
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AI network platformsListen now | Without question a good number of you reading these words right now have interacted with at least one network platform today. A futurist…
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During the course of making my topic list for the Lindahl Letter this was the one that I was most worried about writing. Over the course of the last few…
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