Category: Artificial Intelligence

Categories
Artificial Intelligence Reading Material Video

Douglas Hofstadter, “Gödel, Escher, Bach” and his take on the state of AI today

Collage featuring the cover of “Godel, Escher, Bach,” Douglas Hofstadter, and Amy Jo Kim.

If your curiosity about artificial intelligence goes beyond bookmarking those incessant “10 ChatGPT prompts you need to know” posts that are all over LinkedIn, you should set aside some time to read Douglas’ Hofstadter’s Gödel, Escher, Bach: An Eternal Golden Braid and watch his new interview.

Gödel, Escher, Bach

I might never have read it, if not for Dr. David Alex Lamb’s software engineering course at Queen’s University, whose curriculum included reading a book from a predetermined list and writing a report on it. I’ll admit that I first rolled my eyes at having to write a book report, but then noticed that one of the books had both “Escher” and “Bach” in the title. I had no idea who “Gödel” was, but I figured they were in good company, so I signed up to write the report on the book I would later come to know as “GEB.”

I’ll write more about why I think the book is important later. In the meantime, you should just know that it:

  • Helped me get a better understanding of a lot of underlying principles of mathematics and its not-too-distant relative, computer science, especially the concepts of loops and recursion
  • Advanced my thinking about how art, science, math, and music are intertwined, and inspired one of my favorite sayings: “Music is math you can feel”
  • Gave me my favorite explanations of regular expressions and the halting problem
  • Taught me that even the deepest, densest subject matter can be explained with whimsy
  • Provided me with my first serious introduction to ideas in cognitive science and artificial intelligence

Yes, this is one of those books that many people buy, read a chapter or two, and then put on their bookshelf, never to touch it again. Do not make that mistake. This book will reward your patience and perseverance by either exposing you to some great ideas, or validate some concepts that you may have already internalized.

At the very least, if you want to understand “classical” AI — that is AI based on symbol manipulation instead of the connectionist, “algebra, calculus, and stats in a trench coat” model of modern AI — you should Gödel, Escher, Bach.

A new Hofstadter interview!

Posted a mere three days ago at the time of writing, the video above is a conversation between Douglas Hofstadter and Amy Jo Kim. It’s worth watching, not only for Hofstadter’s stories about how GEB came to be, but also for his take on current-era large language models and other generative AI as well as the fact that he’s being interviewed by game designer Amy Jo Kim. Among other things, Kim was a systems designer on the team that made the game Rock Band and worked on the in-game social systems for The Sims.

Watch the video — I’ll write more about it later.

Categories
Artificial Intelligence Deals Programming

45 (mostly) Python tutorials for $25 via Humble Bundle!

If you want to learn Python, machine learning, data science, and a few other related topics AND you have $25 handy, The Complete Python Mega Bundle has you covered, as you can see from the list of tutorials below:

At the time of writing, you’ve got about 17 days to get in on this deal.

Categories
Artificial Intelligence Meetups Tampa Bay

I’ll be speaking at TBTLA’s artificial intelligence “fireside chat”! (Wednesday, July 12)

Tampa Bay Technology Leadership Association (TBTLA) is hosting a “fireside chat”-style set of discussions on artificial intelligence on Wednesday, July 12 at St. Petersburg Shuffleboard Club — and I’ll be one of the speakers:

Here are the speakers, listed in order by last name and linked to their LinkedIn profiles:

The overall topic of discussion will be “How generative AI is changing industries,” and there will be other related subtopics.

After the fireside chat, we’ll take advantage of the location — the oldest and largest shuffleboard club in the world — and play some shuffleboard! (And yes, there’ll be an instructor present.)

Space is limited, so you can’t just show up to this event. If you’d like to attend, RSVP at TBTLA’s site — and I’ll see you there!

Categories
Artificial Intelligence Video

The Munk Debate on AI R&D: Existential threat or not?

Banner: “The Munk Debate - Toronto - June 22, 2023 - BE IT RESOLVED AI research and development poses an existential threat.” Features a photo of the stage at the Munk Debate and the photos of Yoshua Bengio, Max Tegmark, Melanie Mitchell, and Yann LeCun.

Last week, the Munk Debates — a Toronto-based series of debates on important topics of the day — hosted a debate with four notable AI/machine learning professors where the resolution was: BE IT RESOLVED: AI research and development poses an existential threat.

On the “pro” side — that is, the people arguing that AI research and development IS an existential threat:

And on the “con” side — the people who are arguing that AI research and development IS NOT an existential threat:

  • Melanie Mitchell: Professor at the Santa Fe Institute, who’s worked in the areas of analogical reasoning, complex systems, genetic algorithms and cellular automata. She’s the author of the book AI: A Guide for Thinking Humans, published in 2019.
  • Yann LeCun: Meta’s chief AI scientist and professor at New York University, best known for his work on computer vision, optical character recognition, and convolutional neural networks. He won the Turing Award with Yoshua Bengio and Geoffrey Hinton for their work on machine learning.

They asked the audience to vote for a side at the start and conclusion of the debate, and while a clear majority were on the “pro” side (that is, they believed AI poses an existential threat), the “con” side won by gaining 4% of the vote at the end:

Graph showing audience vote before and after the debate. Before the debate, the audience vote was 67% pro, 33% con, and after with was 64% pro, 36% con.

It’s hard to tell whether the Munk Debates really want you to pay to watch the video, as they have it locked down on this page and freely available on this one, so I’m linking to this YouTube posting for as long as it remains online. Enjoy!

Categories
Artificial Intelligence Tampa Bay Video What I’m Up To

My interviews (so far) about AI on Fox 13 News Tampa

I’ve made three appearances on Fox 13 News Tampa this year so far. If they call on me to answer more questions or explain some aspect of artificial intelligence, I’ll gladly do so!

My most recent appearance was on June 14, whose topic was all the noise about AI possibly being an existential threat to humanity. This is the one where I reminded the audience that The Terminator was NOT a documentary:

I made an earlier appearance on April 10th, where the topics were ChatGPT and AI’s upsides and downsides:

And here’s where it all started: a more in-depth news story on AI and ChatGPT featuring a number of Tampa Bay people

Categories
Artificial Intelligence Humor

ChatGPT fails to answer a classic math problem with a twist

ChatGPT’s source of strength — its ability to create sentences that make sense by using the previous set of words to predict the next one — is also a weakness. You can see this weakness by giving it the following prompt:

Joey DeVilla - YouTubeI have a ten-liter bucket, a five-liter bucket, and 50 milliliter shot glass. How do I use these items to measure a 50-milliliter shot of bourbon?

The obvious answer — obvious to us humans anyway — is to ignore the buckets and simply fill the shot glass. Problem solved.

ChatGPT’s answer wasn’t just wrong and convoluted, but also a waste of money and bourbon:


This image has an empty alt attribute; its file name is chatgpt-icon.png		To measure a 50-milliliter shot of bourbon using a 10-liter bucket, a 5-liter bucket, and a 50-milliliter shot glass, you can follow these steps:

1. Fill the 5-liter bucket to its maximum capacity.
2. Pour the water from the 5-liter bucket into the 10-liter bucket. This leaves you with 5 liters of water in the 10-liter bucket and an empty 5-liter bucket.
3. Fill the shot glass with bourbon until it is completely full.
4. Pour the bourbon from the shot glass into the 5-liter bucket.
5. Repeat steps 3 and 4 nine more times, pouring 10 shots of bourbon (50 milliliters each) into the 5-liter bucket.
6. Once you have poured all 10 shots of bourbon into the 5-liter bucket, you will have a total of 500 milliliters (10 shots x 50 milliliters) of bourbon in the 5-liter bucket.
7. Now, carefully pour the 500 milliliters of bourbon from the 5-liter bucket into the 10-liter bucket. The 10-liter bucket will now contain the desired 50 milliliters of bourbon.

By following these steps, you can measure exactly 50 milliliters of bourbon using the given buckets and shot glass.

Note that in step 2, the liquid isn’t bourbon, but water.

ChatGPT has the solution in step 3, but it gamely continues with an additional four steps.

Steps 4, 5, and 6 are a transfer of a half-liter (a little more than a pint, or two-thirds of a standard whiskey bottle) of bourbon into the five-liter bucket.

In step 7, the final step in this drawn-out process, you pour the bourbon from the five-liter bucket into the ten-liter bucket, which currently contains five liters of water. Contrary to what ChatGPT tells you, you do not have exactly 50 milliliters of bourbon measured out in the 10-liter bucket; you have 5.5 liters of a liquid that depending on your point of view could be called:

  • Criminally diluted bourbon
  • Tainted water
  • Uncarbonated bourbon-flavored White Claw

ChatGPT gets the answer to this question wrong because it’s been largely trained on content published on the internet, and some of that content includes math problems of the form “You have a bucket of size x, and another bucket of size y. How would you measure a quantity of size z?” In these problems, you’re usually asked to measure out a quantity of water, and there usually isn’t a bucket that’s the same size as the quantity you’re trying to measure.

ChatGPT has no actual understanding of the problem. It’s simply spitting out words to follow a pattern of text that’s part of the data it was trained on.

Try this problem — or your own variation of it — on ChatGPT and see what kind of results you get!

Categories
Artificial Intelligence Tampa Bay Video What I’m Up To

Yesterday’s AI interview on FOX 13 News Tampa

Chris Cato and Joey deVilla during a live interview of FOX 13 News Tampa. The caption in the “lower third” reads “Risks and benefits of artificial intelligence.”
FOX 13 News anchor Chris Cato and me.

Here it is — the recording of my interview on the 4:00 p.m. news on FOX 13 Tampa with anchor Chris Cato, where I answered more questions about artificial intelligence:

In this quick interview, we discussed:

  • The “existential threat to humanity” that AI potentially poses: My take is that a lot of big-name AI people who fear that sort of thing are eccentrics who hold what AI ethicist Timnit Gebru calls the TESCREAL (Transhumanism, Extropianism, Singularitarianism, Cosmism, Rationalism, Effective Altruism, and Longtermism) mindset. They’re ignoring a lot of closer-to-home, closer-to-now issues raised by AI because they’re too busy investing in having their heads frozen for future revival and other weird ideas of the sort that people with too much money and living in their own bubble tend to have.
  • My favorite sound bite: “The Terminator is not a documentary.”
  • A.I. regulation: Any new technology that has great power for good and bad should actually be regulated, just as we do with nuclear power, pharma, cars and airplanes, and just about anything like that. A.I. is the next really big thing to change our lives — yes, it should be regulated.” There’s more to my take, but there’s only so much you can squeeze into a two-and-a-half minute segment.
  • Cool things AI is doing right now: I named these…
    • Shel Israel (who now lives in Tampa Bay) is using AI to help him with his writing as he works on his new book,
    • I’m using it with my writing for both humans (articles for Global Nerdy as well as the blog that pays the bills, the Auth0 Developer Blog) as well as for machines (writing code with the assistance of Studio Bot for Android Studio and Github Copilot for iOS and Python development)
    • Preventing unauthorized access to systems with machine learning-powered adaptive MFA, which a feature offered by Okta, where I work.
  • My “every 13 years” thesis: We did a quick run-through of something I wrote about a month ago — that since “The Mother of All Demos” in 1969, there’s been a paradigm-changing tech leap every 13 years, and the generative AI boom is the latest one:
Poster: “Every 13 years, an innovation changes computing forever.”
Tap to view at full size.
  • And finally, a plug for Global Nerdy! This blog has been mentioned before in my former life in Canada, but this is the first time it’s been mentioned on American television.

I’ll close with a couple of photos that I took while there:

Joey de Villa in FOX 13 News Tampa’s green room.
In the green room, waiting to go on.
Tap to view at full size.
A view of the Fox 13 News Tampa studio, as seen from the interview table.
The view from the interview table, looking toward the anchor desk.
Tap to view at full size.
Interviewee’s-eye view of the cameras, teleprompters, and monitors at the Fox 13 News Tampa studio, as seen from the interview table.
The cameras, teleprompters, and monitors.
Tap to view at full size.

Once again, I’d like to thank producer Melissa Behling, anchor Chris Cato, and the entire Fox 13 Tampa Bay studio team! It’s always a pleasure to work with them and be on their show.