BBC “In Our Time”, categorised by Dewey Decimal, heavy lifting by GPT
I'm a big fan of the BBC podcast In Our Time -- and (like most people) I've been playing with the OpenAI APIs. In Our Time has almost 1,000 episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all still available, so it's my starting point to learn about most topics. But it's not well organised. So here are the episodes sorted by library code. It's fun to explore. Web scraping is usually pretty tedious, but I found that I could send the minimised HTML to GPT-3 and get (almost) perfect JSON back: the prompt includes the Typescript definition. At the same time I…
BBC “In Our Time”, categorised by Dewey Decimal, heavy lifting by GPT launched on March 8, 2023 with 688 votes, #6 of 5,007 launches that month and more than 99% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
This tool organizes nearly 1,000 episodes of the BBC podcast "In Our Time" using Dewey Decimal classification system. The episodes cover diverse topics from history and science to specialized subjects like plasma physics. It's designed for listeners who want to explore the podcast's content by subject rather than chronologically. The creator used GPT-3 to automatically categorize episodes, demonstrating how language models can handle structured data extraction and classification tasks efficiently.
written from the facts on this page · September 2026
From the sources
Explore the In Our Time archive.
In Our Time has been broadcast on BBC Radio 4 since 1998, hosted by Melvyn Bragg until 2025 and Misha Glenny from 2026. Here’s the official site. There are over a thousand episodes listed here (1103 excluding repeats etc), on all kinds of topics, and they are all available to listen to on the BBC website. This unofficial site is about finding what to listen to next. You can also search for episodes (tap the link at the top of the page). You can be fairly descriptive, e.g. ‘novels by women’ or ‘prehistoric earth’ will give good results. From an episode page, explore related episodes or tap on a guest to see other episodes in which they have appeared. (See also: All guests .) The reading list…from genmon.github.io
In the maker’s words, at launch
I'm a big fan of the BBC podcast In Our Time -- and (like most people) I've been playing with the OpenAI APIs. In Our Time has almost 1,000 episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all still available, so it's my starting point to learn about most topics. But it's not well…
Does a similar job
all alternatives →- SPScribbler – Podcast Summaries Using GPT2023 · app.scribbler.so · ▲91
Hey, we're Phil and Ian, the founders of Scribbler. We're huge podcast fans, but found we never had enough time to soak it all in. So, we built Scribbler - a tool that leverages GPT to condense podcast episodes into bite-sized summaries for when life's too busy. Now, we can catch the best bits from any episode, discover new shows, and best of all, stop wasting valuable time figuring out what's worth listening to and what's not. We hope you'll find it useful!
I mapped HN's favorite books with GPT-4o2024 · hnbooks.pieterma.es · ▲285Hey HN! I love finding new books to read on here. I wanted to gather the most mentioned books and recreate the serendipity of physical browsing. I scraped 20k comments from HN threads related to reading, extracted the references and opinions using GPT-4o mini, and visualised their embeddings as a map. - OpenAI's embeddings were processed using UMAP and HDBSCAN. A direct 2D projection from the text embeddings didn't yield visually interesting results. Instead, HDBSCAN is first applied on a high-dimensional projection. Those clusters tend to correspond to different genres. The genre…
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