November, 2019 | Chris Aldrich

🎧 episode 12: Kleos and Nostos | Literature and History

Listened to episode 12: Kleos and Nostos by

Doug Metzger from literatureandhistory.com

The Odyssey, Part 1 of 3. Adventure, monsters, temptresses, and a whole lot of wine-dark Aegean. Learn all about the world of Homer’s Odyssey.

A dramatically different type of story told here versus the Illiad.

Checked into Little Free Library

👓 Humane Ingenuity 9: GPT-2 and You | Dan Cohen | Buttondown

Read Humane Ingenuity 9: GPT-2 and You by

Dan Cohen (buttondown.email)

This newsletter has not been written by a GPT-2 text generator, but you can now find a lot of artificially created text that has been.

For those not familiar with GPT-2, it is, according to its creators OpenAI (a socially conscious artificial intelligence lab overseen by a nonprofit entity), “a large-scale unsupervised language model which generates coherent paragraphs of text.” Think of it as a computer that has consumed so much text that it’s very good at figuring out which words are likely to follow other words, and when strung together, these words create fairly coherent sentences and paragraphs that are plausible continuations of any initial (or “seed”) text.

This isn’t a very difficult problem and the underpinnings of it are well laid out by John R. Pierce in *[An Introduction to Information Theory: Symbols, Signals and Noise](https://amzn.to/32JWDSn)*. In it he has a lot of interesting tidbits about language and structure from an engineering perspective including the reason why crossword puzzles work.
November 13, 2019 at 08:33AM

The most interesting examples have been the weird ones (cf. HI7), where the language model has been trained on narrower, more colorful sets of texts, and then sparked with creative prompts. Archaeologist Shawn Graham, who is working on a book I’d like to preorder right now, An Enchantment of Digital Archaeology: Raising the Dead with Agent Based Models, Archaeogaming, and Artificial Intelligence, fed GPT-2 the works of the English Egyptologist Flinders Petrie (1853-1942) and then resurrected him at the command line for a conversation about his work. Robin Sloan had similar good fun this summer with a focus on fantasy quests, and helpfully documented how he did it.

Circle back around and read this when it comes out.

Similarly, these other references should be an interesting read as well.
November 13, 2019 at 08:36AM

From this perspective, GPT-2 says less about artificial intelligence and more about how human intelligence is constantly looking for, and accepting of, stereotypical narrative genres, and how our mind always wants to make sense of any text it encounters, no matter how odd. Reflecting on that process can be the source of helpful self-awareness—about our past and present views and inclinations—and also, some significant enjoyment as our minds spin stories well beyond the thrown-together words on a page or screen.

And it’s not just happening with text, but it also happens with speech as I’ve written before: Complexity isn’t a Vice: 10 Word Answers and Doubletalk in Election 2016 In fact, in this mentioned case, looking at transcripts actually helps to reveal that the emperor had no clothes because there’s so much missing from the speech that the text doesn’t have enough space to fill in the gaps the way the live speech did.
November 13, 2019 at 08:43AM

Checked into Supercuts

🎧 Mindscape 68 | Melanie Mitchell on Artificial Intelligence and the Challenge of Common Sense

Listened to Mindscape 68 | Melanie Mitchell on Artificial Intelligence and the Challenge of Common Sense by Sean Carroll from preposterousuniverse.com

Artificial intelligence is better than humans at playing chess or go, but still has trouble holding a conversation or driving a car. A simple way to think about the discrepancy is through the lens of “common sense” — there are features of the world, from the fact that tables are solid to the prediction that a tree won’t walk across the street, that humans take for granted but that machines have difficulty learning. Melanie Mitchell is a computer scientist and complexity researcher who has written a new book about the prospects of modern AI. We talk about deep learning and other AI strategies, why they currently fall short at equipping computers with a functional “folk physics” understanding of the world, and how we might move forward.

Melanie Mitchell received her Ph.D. in computer science from the University of Michigan. She is currently a professor of computer science at Portland State University and an external professor at the Santa Fe Institute. Her research focuses on genetic algorithms, cellular automata, and analogical reasoning. She is the author of An Introduction to Genetic Algorithms, Complexity: A Guided Tour, and most recently Artificial Intelligence: A Guide for Thinking Humans. She originated the Santa Fe Institute’s Complexity Explorer project, on online learning resource for complex systems.

One of the more interesting interviews of Dr. Mitchell with respect to her excellent new book Dr. Carroll gets the space she’s working in and is able to have a more substantive conversation as a result.

Checked into Dunsmore Park