Welcome to iHeartRadio Communities, a public affairs special focusing on the biggest issues impacting you this week. Here's Ryan Gorman. Thanks so much for joining us here on iHeartRadio Communities. I'm Ryan Gorman, and we have a couple of important conversations lined up for you. In just a bit, we're going to talk to shark expert Greg Skulmulus. This past week has been Shark Week on Discovery Channel. He's author of Chasing Shadows, My Life Tracking the Great White Shark,
and he is a featured expert on so many Shark Week specials. Will talk about his life observing sharks, also the conservation of sharks, and a whole lot more. So stick around for that. I think you'll enjoy that conversation. Right now, to get things started, I'm joined by doctor Barksco, a best selling author, world renowned scientist and expert on artificial intelligence.
Is nineteen ninety three international bestseller Fuzzy Thinking How AI Thinks in Shades of Gray is being rereleased in a digital version, and he's with us to help break down some questions on current issues involving AI. Doctor Costco, thank you so much for coming on the show. And let's begin with your book. What exactly is fuzzy thinking and what were some of the things you were working on
related to AI thirty years ago. Fuzzy thinking is a way of referring to fuzzy logic or thinking in shades of gray rather than simple black white reasoning, like a computer chip works on or off. It's the way people think. So, for example, we would say that a pink rose is both read and not read to some degree. Now that's simple enough, common sense, but very different in terms of classical Western logic, which is either one or the other, either or this case it's both. And that kind of thing
softens decision making in the case of AI applications. There's many applications of fuzzy logic. In the case of AI applications, they often have rules, and the rules like programming an air conditioner, if the error is cool, set the motor speed to slow. Well, what do you mean by cool air? Its boundaries are fuzzy, they're great, they're not exact. It depends exactly what temperature at, whether it's sixty or eighty percent cool, and so
forth. And you and I mean different things by cool. So even words like that which on the page say the same thing, or appear to mean the same thing. You and I mean different things by them. As an example of an application, I have a Subaru car that uses funsyologic to control the transmission to shift gears. So many times per second sensor data comes in and a bank of these rules makes a decision about whether the shift gears.
The net effect is it does so very smoothly given changing conditions, and it doesn't fall asleep and have accidents and things like that. You probably have a gadget that has fuzzyologic in it, whether a microwave, oven, a washing machine, even a camera. Really, thousands of commercial electronic products, many other systems are told by fuzzy logics. Famously, in Japan, in the city of Sendai, you may recall the city hit very hard by the tsunami
in twenty eleven. The city Ascendi, its main subway system, is completely under control of fuzzy logic, and it's much smoother as a consequence. So we had all that answer your question line back in ninety three worked that out. I had a textbook on it from printers Hall called Networks in Fuzzy Systems.
But what we didn't have is a computing power we have today, and that's a result of Moore's law, the doubling of computer chip density on off circuits on a chip every two years, every two years, so in thirty years we've had sifteen doubling. That's a staggering exponential increase in computing power in
a fallen price. And you see that showing up today taking very old algorithmles with flight modifications in running them on much more powerful systems like applications to medical diagnoses which are very successful with AI and you can you can go back and validate them, but you also see them when it comes to applying it to
language. And this is the systems that these are systems that are causing the excitement and the fear now in particular with the March twenty twenty three released by open aye of chat GPT four, and that stimulated some competitors that I think
prematurely release other systems, and that's a whole different game. Those systems, some of which are fuzzy, but most of them are using classical neural networks but on a vast, staggering scale and applying it to a lot of texts, literally trillions of strings of texts, everything on Wikipedia, everything on your social media, and everybody else's books that are copyrighted n copyrighted. It's already led to some class action lawsuits, for example against Facebook in terms of copyrighted
books. But the effect of that starts off on completing a sentence for you. So if I say the sky is and you say blue or the sky is overcast or whatever, there may be hundreds of thousands when you search worldwide databases completions, and if I have that sentence, I can then rerun this to complete a complete paragraph and maybe a sequence of paragraphs. And that's what's really happening by fast, or has been happening in training when you interrogate a
chat GPT system. So the number of parameters on these things has exploded as well. The new system called Lama from Facebook and something like sixty five billion parameters where each parameter is a knob that can be turned and it's similar to a wire in your brain, a synapse, and so sixty five billion. Wow, that was unheard of even a few years ago. Now Microsoft has
topped out, sorry, Google AI has topped that. Microsoft has new system coming up with something called Palm and palm has five hundred and forty billion, more than half a trillion parameters, and they grow, and so the ability to recognize linguistic patterns magnificent, better than ever, but it cannot explain itself. And these are unlike fuzzy systems, which have an auto trail and give you a confidence measure. These are black boxing eye systems. So they often
work, but they also make things up. They hallucinate, and if you've ever dealt with what these systems, you'll, I think you'll see that they might have been at least a bit prematurely. And if you saw the recent sixty minutes interview with the folks at Google and their system, they asked the system about inflation, got an interesting answer it depended on five economics textbooks. But it turned out when they checked it there were no such textbooks. The
system literally live. It made it up connected dots that didn't exist, and did not mention that to the sixty minutes down and that's something you've got to be very very careful with. We're joined now by AI expert doctor Bart Costco. So in the thirty years that you've been studying artificial intelligence, aside from just the rock computing power and what we're able to do because of that.
What are some of the biggest advancements that really stand out to you. One of them would be the ability with language processing, mapping text to texts to do real well on exams, in particular the bar exam, the attorney stake, the uniform bar exam. Recently, some of these systems have hit ninety percentiles. To think about that, it's pretty impressive. They have looked at
these exams ninety percentiles and they'll just increase from there. That's something that was a result again of just computing power in a few tweaks, but at some point across a qualitative threshold or tipping point, and it did. So we've seen that a lot of that in the last two to three years. Same way with chess or looking for ways you can fold proteins, and you can come up with systems if you run it long enough. It's not really reasoning.
It looks like it's reasoning. It's imitating that. It's just checking a lot of cases, and it can come up with cases the case of chess, where strategies where you'd give up your queen, for example, we just wouldn't say if you play chess, you just wouldn't think to do that. But it can turn out to be a winning strategy. And the current systems can beat any chess masters, and that's only going to increase as well. So in cases like that, or finding new ways to put together proteins,
we've crossed some thresholds. We knew that was coming. We knew it was coming thirty years ago, and a lot more is coming still in the next thirty years. Because computing power that we won't always have the current version of Moore's law, it's kind of hitting its limits. There'll be other things, different forms of quantum computing computing, some nanotech and some other things, and
we really don't know exactly what. We're shrinking. The chips ryan so small now that we're getting down the on off circuits to a couple three atoms across, it becomes unstable. But we'll do something. We'll find something, and the old algorithms and some new agorithms will again hit tipping points. Medical diagnostics just wonderful. I think that will get better. As I said before, you can validate that. But this other scarier stuff, the generation of text,
generation of speech, which characterizes our species. That's something we're going to have to come to grips with. When we see different applications, different programs say that they're powered by AI. What exactly does that mean? Well, you got to be careful because it can mean so many different things. To first order, any algorithm today that runs on a computer that uses data is called AI. You've got to be careful. Just give you one example.
There's a split politically between computer science and electrical engineering. Now this is inside baseball that it matters in a university, and we've been doing this in EE electrical engineering for decades. The computer science folks shunned neural network famously, starting in the late sixties with a book by my good friend and late colleague Marvin
Minsky, an m I t called called Perceptrons. He simply found that earlier kinds of neural systems in the sixties were limited what they could do, and people, I think through the wrong conclusion. AI went off in a different direction, really in an anti neural networks way. I helped set up Professional Network Conference, which is in nineteen eighty seven in San Diego, and the slogan at the conference was quote AI is dead, long live neural networks.
Well today AI equalfnural networks real quick? What is a neural network? A neural network is a system where you teach it by training it rather than programming, which your face looks like. We just give a thousands and thousands of examples, and it has these parameters of a tunny but if you look at
it, it kind of looks like a little piece of a brain. You have the input where you put your face, and then there's some wires going forward if it were physical, but it's actually going to sompware, and there'd be another layer of switches like neurons on or off, and they would feed to another layer, another layer, they're called hidden layers, and at the output in your case for your face, or just be one neuron and it
either like a lightbulb, there's either on or off. And so we could train to find your face in images where it's partially included, where the light's bad, where it's been randomly mixed with your next door neighbor. And the more training we do, the better it gets. And we could have multiple lightbulbs. You could have a thousand light bulbs, each one for a different
face. Now, what's happening in a chat system is there are tens of thousands of light bulbs at the output, but each one stands for a word. Or you could have a video system and each one stands for a little piece of a movie for a video segment. In general, each light bulb at the output stands for a pattern, and the longer you train it, the better it gets to go forward and backwards. For example, recently got another pattern on how to speed up in a training process, but it's very
intensive. It can take months off line for big problems, and it will learn patterns, but just like the way you and I learn a pattern, we can't explain how we learned it, and we can recognize thayings without being able to explain that. A good example would be the music to Mission Impossible or the music to James Bond. Unless you're really well trained to music, you probably cann't write that down, but almost everyone can recognize that the assistive
memory property and the neural networks have that. So today that is the power the neural networks, which was a very tiny subset of AI thirty forty fifty years ago, now it equals AI in an ironic sense. So you've got to be careful. Another example of that is to take other algorithms like the one we use to get the first ment of the moon, called something called
the calm and filters. It today would be lumped in with that. Now, what that does is it allows you to figure out if you're stumbling in the dark where you are based on your current guests of where you are and
any kind of measurement. So for example, on Apollo eleven, when the folks were in space, they might have been talking to the President Nixon in in nineteen sixty nine, and the astronauts they had some direct measurements coming from optical sections that they were using out the window, but they also had some estimates of where they were from the onboard computer. And it was just the
algorithm was just efficient enough to squeeze into that that old Apollo computer. Well, that algorithm today is the essence of smart cards and many many other things. But it will be called AI. It cames a surprise to a lot of us, including to the late grade Rudy Coleman, who came up with a nineteen sixty so powered by AI. You gotta be careful. It could mean something like that. It could mean one of literally hundreds of alternative algorithms.
But at ROUTE it's combining computers with statistics. The artificial intelligence that we're dealing with right now, an AI chat GPT. These are computer systems that are just filtering through a lot of data. Basically, the limitations to this is what we allow it access to right correct exactly, and that raises lots of problems. So it raises privacy problems, it raises inllectual property problems. I mentioned the case of Lama, the system and meta at Facebook. This
month there was a class action lawsuit filed against it. Where everyone's watching this and the illegal feel very carefully on the West Coast for violating copyright right there. Several authors. Now the discovery process will show us how many books are actually used. The comedian and author Sarah Silverman has a book used in that I think it was called The Bedwetter or something. So she's part of what
we call the class representative. But it's going to be an interesting insight because there there's a lot of opaqueness, say at the big tech companies and authors, if you're within the copyright bounds, have a right to assert for copyrights, and these companies are supposed to get permission. So there's some evidence that there is at least I think four hundred bucks verified so far that have been used in training. And that's interesting. Your other information that you're putting out
online, you're basically impliedly consenting to let others have access to it. I would just say, as a father and as a lawyer, I would encourage people not to participate in that sort of thing. I would I would limit my exposure online. Not just purchases and browsing histories you can possibly do it, but anything you post voluntarily because that can be stitched together used against you in really unforeseen ways in the future, and used in things like deep fakes
that you can't foresee. And there can be mass I don't want to say surveillance, but mass algorithms applications combining you with other folks or and it can be abused at the political level. So for example, in twenty twenty four, I think we're going to end up calling that election the first AI election.
There's going to be so much analytic techniques going on from the opposing parties, from possibly from China, from other countries, from commercial firms in a way that goes well beyond just predicting how people will vote, but manipulating them and you might not even know manipulating you in a coercive way, but maybe just slightly changing the probability of how you would vote. And that's sort of a thing. It'll be interesting to see how it plays out, and I
think that will be the future of elections too. We're joined now by bestselling author, world renowned scientist an expert on AI, doctor Bart Costco. Is the big concern when it comes to AI that eventually, somehow it will expand beyond just the information that we're giving it and begin to make its own decisions, think independently of what we're trying to tell it to do. You know. That's that's the terminator kind of view of it, and it's possible that
could happen. It's hard to see, I think, how that happens. It's much more likely somebody's behind the scenes of pulling the stranger's programming it to do something like that, because in the end, in the end rhyme an AI system is still a bunch of muliplications and additions. It is nothing magical, and it doesn't have an intricate system. It doesn't have a hormone system,
it doesn't have a built in luss for power. It's not human in that sense, but it can be programmed that way, and not just so, rather than a big system that wakes up like we've seen in some magical way and it takes over. Could it could backfire, It could have a mutation, a DNA mutation type effect where it evolves into something that goes off untethered again, probably as a result of faulty programming. That's a real risk,
but I think just the risk of bad actors in greedy folk. I mean, one example, there was a piece of software I don't even want to name it online that some youngsters put out apparently that would enable you to take a woman's image and then modify it so you could see or naked, and kids were using it in school. Of the mass violation of privacy. The laws have not adjusted for that, and once that's out there can be replicated at zero costs. You know, it's around the world. So it's
that sort of thing multiplied over the years. As computing power increases, as sensing increases, as databases increase, we're not prepared for we have to watch out for it from a commercial point of view, though, I think it is a great opportunity for entrepreneurs to come in and address the problems of hallucination and privacy laws and just you know, some kind of detector out there to let you know when not just being spied on and surveyed, surveyed which you
are, but to extent to which some thing or somebody is building a profile of you. One last question for you, the disruption to our economy, to jobs, to entire industries. Are we just at the beginning of that. When it comes to AI, we are at the beginning of that. And the effect is having on some white collar workers. Lawyers, My lawyer friends are finding it very beneficial because, for example, you can take a lot of discovery documents, maybe a thousand pages worth, and boil it down
without hiring people to do that. But some lawyers just found out federal courts that you don't want to rely on chet GPT to write your brief because the hallucination faces. Yeah, you get facers. So as a decision support system, wonderful to help people, will displace a few and it'll make more jobs. It is a little dice here, and we look deeper into the future. Certainly, candidates for automation are jobs that are simple and repetitive, and
we have to do more schooling. I'm also worried that it's it will undermine our education process, especially Kater twelve, because too many kids I see already are using this to generate essays. The hardest thing I think for soon is the right text, of original text, of high quality, and it comes
with practice, not by relying on chat GPT. Doctor Bark Costco, a bestselling author, world's renowned scientist and expert on artificial intelligence, is nineteen ninety three international bestseller Fuzzy Thinking, How AI Thinks in Shades of Gray, is now being rereleased in a digital version. Doctor Costco can't thank you enough for all the time and the insight into this complicated issue. We appreciate it. My pleasure. All right. I'm Ryan Gorman here on ihear Radio Communities,
and now I want to bring in our next guest. This week, Discovery Channel has been celebrating Shark Week once again, and we have with us a featured expert on so many Shark Week specials. Shark expert doctor Greg Schomel is with us. He's author of the new book, Chasing Shadows, my life tracking the Great White Shark, Doctor Schoemel, I've watched you so many times on the Shark Week specials. It's a real privilege to interview you here.
And I want to start with the release of the movie Jaws, going back a bit and find out what kind of an impact that movie had on the public's perception of sharks, obviously including great white sharks and the population of sharks around the world. Well, Ryan, I'll start by saying what it did to me. You know, I saw it in a movie theater in nineteen seventy five and the character is played by Richard Dreyfus, Matt Hooper, was inspirational. So well, it pulls pushed a lot of people out of the
water. It pulled me into the water. But it characterized like so many Hollywood films, do you know, the white shark as a as a as a villain, and as a mindless and you know manager, And obviously that's not what these animals are. But you know, I don't fault the movie Jaws for the demise of white sharks or shark populations. Frankly, I just look at that as an entertaining film. You know a lot of people think,
oh God, without Jaws, we'd have fuenty of white sharks. And the truth of the matter is is we had an explosion in commercial fishing and commercial shark markets, you know that occurred in the eighties and nineties that led to the demise of shark populations. It really wasn't the film. Now, the first time you're face to face with a great white shark, what was that experience like? For me? It was, you know, an absolutely
pivotal experience. You know, it was a seventeen foot, three thousand pound white shark and I was literally right next to it, and I'm saying, I can't believe how big this animal. You know, it was like it was like seeing it was like studying wanting to study big Foot and then finding
one. It was amazing. You know. I've watched so many specials over the years on Shark Week about great white sharks, and one thing I'm always struck by, despite all the attention they've gotten, there's still such a mysterious creature. One of the things I talked about in the book is the fact that I thought I could not become a shark biologist because we knew everything there was to know about these animals, and that's absolutely was not true and it
remains untrue. You know, some of the basic biological questions people have, particularly in terms of reproduction. For example, you know, the white shark here on the east coast of the US and in the Gulf of Mexico, we really don't understand or know when and where it reproduces. Where to males mate with females, How long do the developing young inside the female? How many developing young young wills she have? And where did she give birth to
those young? You know, that's a really those are simple questions, but they're very difficult to answer. Why are they so difficult? How come we don't have a better sense of the mating habits of great white sharks? Well, pretty much the same reason we don't know a lot about the mating habits of most shark species. It's because they're highly migratory. They live in the
ocean. You've got to be in the right place at the right time to actually observe this kind of behavior, and that just doesn't happen enough, you know, So we try to use indirect methods. For example, if we examined a lot of pregnant females over the course of the year, we would get a sense of the timing of their when birthing occurs in the development of these young truth is, we've never seen a pregnant female white shark in the
Atlantic Ocean. We're joined by shark expert doctor Greg Schomel, author of Chasing Shadows, My Life Tracking the Great white Shark. Another thing I found really interesting about great white sharks how they hunt and depending on their location, the different types of tactics they use. I believe it's off the coast of South Africa. That's where they come up from below the seals and they do those
breeches out of the water, attacking their prey that way. But then I was just watching a show that you were on up in the Cape Cod area, and they have a completely different hunting style. Yeah, Ryan, I love this question because it allows me to, you know, to talk about how plastic these animals are in terms of adaptability. You know, they're they go in South Africa. The environment's very different from Cape Cod, which is very different from Mexico, right, but it's the same species, and so
they adapt their their hunting behavior to that environment. So you mentioned you know the missile launch that they go as they breach, pinning seals against the surface as they strike from deep water off South Africa. In Cape Cod, we've got really shallow water, it's murky, it's there's shifting sandbars, there's heavy serve most days. It's a really challenging and very different environment for white sharks.
And they're ambush predators, so they have to adapt their strategy, you know, when they hunt off Cape Cod in order to ambush their prey without their prey seeing them, and it's difficult. You know, they have to strike from the side. You don't see them launch themselves like you do in South Africa. But it's really cool because the species adapt to its environment.
As I'm sure you're well aware, there's been a lot of focus and a lot of talk about our oceans recently following the tragedy involving the titan submersible and how far down our oceans go with Titanic wreckage twelve thousand, five hundred feet below the surface, how deep do great white sharks go? Do we know the depths that they swim to? Yeah, I think the new technologies that we're using over the last couple of decades have really opened our eyes to white
shark behavior, a lot of sharks, a lot of species behavior. We're now able to put satellite technology and sensors that will detect temperature in depth. And what we found out we published this a few years ago, it's obviously going to be is in the book, is that white sharks, when they move off our shoreline and go out into the open Atlantic, will dive to depths as great as three thousand, thirty five hundred feet deep every day.
Are really really broad temperature range. Now they're not getting as deep as the Titanic, but we always thought of these sharts as being coastal animals. If the new technologies tell us no, they actually go to parts of the deep ocean. We're joined by shark expert doctor Greg Schomel, author of Chasing Shadows,
My life tracking the Great White Shark. Final question for you. We think of the great white shark as the apex predator in the ocean, but I've watched a number of specials that's shown where that's not always the case, especially when it comes to orcas killer whales. Can you tell us what we know about that? Well, there's two you know, we always think of the white shark as being the top predator. But yeah, that's that's we're learning that's not the case. First of all, you know, it has
a couple of predators. We thought it was primarily manned, right, white sharks are largely killed by people more so than anything else. But recently, over the last decade, we've figured out also that the killer whale, the orca, is a predator of white charts and it literally scares them out of the area when they are when when orcas are around, and they're capable of
killing white charts and targeting their liver, which is absolutely fascinating. So you know, every time you think there's a top predator out there, there's going to be something, you know, a little bit bigger, a little smarter that's going to take it out. And finally, where can people find out more about your conservation efforts because your front and center on all of this, and I want to make sure everyone has that information too. Thank you.
I appreciate that the I work really closely with a nonprofit called the Atlantic White Shark Conservancy, And you know the best way to follow us in what we're doing is to go to their social media page. Is whether it be you know, Facebook or Twitter. You know, we show a lot of our films of what we're doing out there. You know, obviously you've seen me on Stark Week Sharks Fast. You know, I love those as vectors to get out what we're doing to the public. But you know, Conservacy is
a great website. Doctor Greg Skomel a featured Shark Week expert and author of the new book Chasing Shadows, My life tracking the Great White Shark. Doctor Skomel, really appreciate time and insight and all the work you're doing for sharks all around the world. Thanks so much for coming on the show. Thanks Ryan, great to be here. All right, and that's going to do
it for this edition of iHeartRadio Communities. As we wrap things up, I want to offer big thanks to all of our guests and of course to all of you for listening. If you want to hear previous episodes of this show, we're on your iHeartRadio app. Just search for iHeartRadio Communities. I'm your host, Ryan Gorman. We'll talk to you again real soon.