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Dr. Richard Wallace

lines on the record: 43
first: 2025-12-31
most recent: 2025-12-31
sittings or episodes: 1
sources: podcast

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“Together, you know, we've got the symbolic estimate, we've got the neural estimate, and we've got the LLM estimate. You could potentially display all three of those, and then it's up to the clinician to make a judgment, or you could even put them all back into a different LLM and ask the LLM which one of these measurements is best, which one of these predictions is best. So it's an effort to combine the best of the symbolic approaches with these newer neural approaches”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And now you could also do that with a neural network, a recursive neural network, where you basically train it by feeding in the patient data, the diagnostic data, and their medical history, and then just look at whether they had a stroke or not. So you can train this neural network to take a new patient data and give some prediction about whether they're going to have a stroke. And then the third way of doing that is to use an LLM. You can just simply upload the entire patient chart to the LLM and say, how likely is this person to have a stroke? And so what we've been doing is sort of combining those three.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“So one example of that is in the medical field, you can make predictions about how likely someone is to be, well, their mortality, how likely they're going to be readmitted to the hospital after being discharged within 30 days, how likely are they to be readmitted, or how likely they are to have a stroke. And the various other things. But the medical field has developed these symbolic techniques for making those predictions. And so, in the case of stroke from AFib, there's a test called ChadVask, and it basically takes into account criteria like your age and gender, whether you've had congestive heart failure, history of hypertension, and various other factors like that. And when you plug in those values, it produces a number which can then be used to estimate the likelihood of you having a stroke.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Symbolic and neural approaches. So symbolic approaches are things like theorem proving programs or the early chatbots that we were talking about based on rules where basically they're manipulating symbols. Or you can also think of a chess playing program, which is very mechanical and manipulating symbols. And so the symbolic approach is in contrast to this neural learning approach. And now we're basically trying to find the best of both worlds.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, well, the company I work for right now, Franz. It's actually a very old AI company founded in 1985. And Franz started out as a company selling Lisp compilers. But then by the end of the 1990s, very few people were paying money for software because there's so much free language software available. So they pivoted to graph database technology. And without getting into too much detail about what that is, now that we have the LLMs, we are taking an approach called neurosymbolic computation. So in the history of AI, he talked about supervised versus unsupervised learning. Another dichotomy in AI is between”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“So in the sense that human beings have freedom of thought and self-reflection and creativity, I don't think those things will be reproduced in a computer anytime soon.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Definitely think it'll be exciting. You know, the term AGI seems a little strange to me because it's what we've always called AI. AI has always been a goal that's just out of reach. And we have an imagination of what it is based on seeing science fiction movies and that sort of thing, you know, Hal and R2 D2 and all those examples give us a template for what we'd like to see in an AI. And so it seems kind of odd that they've come up with a new term AGI to kind of move the goalpost even further. But I'm very skeptical about that. You know, a very simple answer to this question, which a lot of people I know would not agree with is that God gave human beings a soul, but machines don't get a soul.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, testing the limits. Exactly. And then the next category B are just average users. So those category B people were the ones who could suspend their disbelief and they would be very engaged with the bot and have very long conversations, come back and continue their conversations and so on. And so that would be the group that, as you're saying, would be kind of reading more into the bot that was actually there because they're engaged with it on an emotional level. And then the last category I call the critics, which are people who know something about computer programming and AI and they just think this thing is terrible and, you know, they walk away after a few interactions.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, I used to categorize the users or the clients, I call them, into three categories, A, B, and C. And A clients are abusive. Okay, so they're going to say, how can I put this very inappropriate things to the chatbot? And you see those in the conversation locks. Although you always have to wonder if someone is saying, you know, I hate you or I love you even. Is that what they really have in mind or are they just trying to get a response out of the robot and succeed? Testing the law.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, you know, I'm a computer programmer. So I was always more interested in the machine side of it. I think I did learn a lot about human conversation from monitoring those conversation logs.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And it's basically that things in your visual field that have high variance, a high ratio of dark to light, more interesting than other things. So that would typically be edges like the edges of the tree you just described or corners of things or just any sort of bright spot against a dark background or vice versa. And then recognizing those in the periphery of your visual field would cause you to move the center of your visual field towards whatever the interest operator is highlighting.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, a long time ago a guy called Hans Moravek, who was very interesting. We should talk about him some more. He came up with an attention mechanism called an interest operator, and this is for computer vision again.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, in a way, I'm reminded of the work we talked about earlier, which was the robot eye in the early 90s, because that was also an attention-based mechanism. So I described how in order to make use of that log map arrangement of pixels where there's high resolution towards the center, you have to be able to point the camera so that the high resolution can be aimed at something interesting. Well, how do you know it's interesting? If you see something in the periphery, for example, movement and you want to move your eye towards the thing that you're seeing in the periphery and place the attention on that. Attention has to do with focusing your highest resolution sensor capability on whatever seems most interesting in a scene. I think there's an analog for that in the LLM version of attention as well. They're sort of swinging in the direction of where the gaze of the robot is looking depending on what they see in the periphery.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, I was really not paying attention to it at the time. Like I said, I was. working in healthcare you know i don't think the lm industry really came to my attention until you know we started hearing about gpt”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“So, you know, after many years of really struggling with this and trying to figure out how to make a living with chatbots. And I did co-found a company called Pandora Bots, which is based on attempting to commercialize the AI Mel bots. But after a while in the early, in the early teens, I should say, I just decided to get out of the field completely and I went to work in healthcare.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“The Lovener contest was always the domain of hobbyists and amateur programmers. There were a few academic entries, but no big companies ever got involved in it. And then in the 2000s, I organized a number of chatbot conferences, you know, international chatbot conferences. And we have a hard time getting 25 people to attend”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“The rules change from year to year depending on who is hosting the contest. But Loebner's rule was basically if 50% of the judges, usually there are four judges of two out of four judges misidentified the robot as a person, then he would award the silver medal for passing the Turing test.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“then the judge could identify the woman correctly 100% of the time. Because it's clear that only one of the players is a human at all, and that has to be the woman. So now as a scientific experiment, we can say, let's run this experiment with 100 judges and 100 men and 100 women. I don't know exactly how many are needed for statistical accuracy, but let's just say we did a random sample where we collected the results of this game for a large number of players. Then you could measure a certain percentage of the time that the judge would identify the woman correctly. And, you know, let's say that's 70% of the time. Now, if you replace the lying man with a computer and the computer is a very good AI that can actually play the role of the lying man, then you should get closer and closer to that actual 70% measurement.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“75% of the time, 100% of the time, what does that even mean? The robot is more human than a human. So in Turing's 1950 paper, Computing Machinery and Intelligence, he actually describes two different versions of the test or the game. And earlier in the paper, he describes something called the imitation game, which as far as I understand, was based on a real parlor game that people played in Victorian England. And in this game, again, there are three players, the judge or the... So now if you ask a man, are you a woman, he would say yes, because he has to lie. And then the judge's job is to try to figure out which one is the man and which one is the woman. Now if you replace the line man in that scenario with a machine, okay, let's say you replaced the man with a very crude chatbot like Eliza or even Alice.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“I'm so happy you asked me about the Turing test. So the Turing test, most people understand the Turing test as sort of game where there's three players. You have a person who's called the interrogator or the judge, and then they're communicating through a teletype, a text-only medium, much like texting on your phone, but without any audio visual, just typing. And then the two entities that the judge is talking to one is a human and one is a machine. So then the judge has to decide which one is the human and which one is the machine. And if they misidentify the machine as the human, then it's said to pass the Turing test. But you see, this has a big problem as a scientific experiment because it's not really clear how often the interrogator has to misidentify the human. Is it 50% of the time”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And you're just responding to the most recent thing you heard and most recent input. But what really gets to the difference between humans and robots is even though most people most of the time are speaking in this kind of reactive behaviorist way. It is possible for people to have original thoughts and be creative. And it's almost like a muscle that you need to exercise in order to build it up. If you want to break out of that robotic mold, then you have to put some effort into trying to be creative and original with your thoughts and thinking and ideas.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, that really gets to the heart of what I think the difference is between humans and robots, which is that, like I said, I think most people, most of the time are acting like robots. They're just acting in kind of a stimulus response fashion. Just as an aside, I always used to say that most human conversation is stateless, meaning that what I'm saying to you right now only depends on the question that you just asked me. And we can forget the whole history of our conversation up to this point. One of the pieces of evidence for that is if you can imagine yourself having a casual conversation with someone at a party say, and then you say, oh, where did you go to college? And they say, oh, I went to Harvard. I already told you that. You kind of forgot that. You would already talk about college earlier in the conversation.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Because it's not that the robots becoming more like a human, it's that it's revealing to us how robotic we are. And back in the early days of working on Alice, I came to realize that most people most of the time are saying things that they themselves have said before or that they've heard other people say before. And even when they're writing, they're basically synthesizing thoughts and ideas that are not necessarily original. And all of these chat bots work because language is predictable. And predictable means robotic. So I always say that if we were all William Shakespeare's uttering an original line of poetry with every sentence we spoke, then these chapters would never work because they're based on language being predictable, not original. reuttering.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, you know, I can say the same thing about LLMs now that I said about my chatbot back then, which is that people say, well, these chatbots are becoming more and more like humans. And I have a different opinion about that, which is that what it's really showing us is that people are more like robots than we would like to think we are.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“learning language without any supervision. And that's why they learn so much inappropriate and offensive material and so on.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“But I always think of a child learning language and there are big differences here between a child learning language and an LLM. A kid doesn't have to scan the whole internet to learn how to speak a language. In fact, they're pretty good at what we call one-shot learning. If you say to a kid, this is a dog, then they can instantly recognize every dog in the world as a dog. But what also comes into play here is the supervised unsupervised learning dichotomy, which is if you are a kid and you have a good teacher and good parents, you'll learn to speak very well. But if you're a kid who has to pick up language on the street without any supervision, then your language learning won't be nearly as good. And so the LLM is more like the kid out on the street.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, it's so hard to predict the future of AI. I would have never expected this whole LLM development to come along in the first place.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And that's sort of what's going on with the LLMs now is they're having to put a lot of work into filtering to make sure they don't say anything inappropriate or offensive or political. And that ends up being a lot of manual work as well.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And that's in contrast to unsupervised learning, which is what these LLMs are doing. They're basically trying to accumulate a lot of inputs and find the neural network weights that match it to particular outputs. And so with that technique, you can get phenomenal results, obviously. But as you're saying, it's difficult to know how the LLM came up with particular responses. Whereas in the supervised learning case where it's all a symbolic process, it's very easy to trace back through the logic of the program and see what caused a particular response to be generated. And I always say that people who do supervised learning approaches spend all of their time doing creative writing, which is what I was doing with the Alice bot. But people who do unsupervised learning, spend all of their time deleting crap from the database.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Right. Well, there's so many things wrapped up in that question. So let me see if I can pull it apart. Yeah, so there's always been a kind of tension in the history of artificial intelligence between, let's say, supervised learning and unsupervised learning. So what I was doing was what we call supervised learning because I was playing the role of a teacher or a guide. So whenever I added a new response, it was manually added, as you're saying. driven by a particular input that I saw in the conversation logs. And so the way that I'm teaching the robot is by acting as its teacher, basically, and saying, you know, when you see this, you should say that.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, it all goes back to the conversation mug. So just like wise and bone, you know, I can read the transcripts of conversations people were having. By the way, this would have never worked without the internet, without the World Wide Web. Because with the World Wide Web, I could start to accumulate conversations from a very large audience of people. And by looking at the transcripts of those conversations, I could basically program responses to the things people were saying. Later on, I realized that there was kind of zip distribution over the things people were saying. So there's kind of a most common thing people say, which is hello. Who are you and how are you? And I like something so you can create the responses in order of how frequently people say particular things.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Play for the answer that can be populated with various other things. And then there was also a recursive element to it where the response could actually simplify the input into a kind of simpler input. So the example of that is I want you to tell me who you are right now so you can reduce that by removing the write now. Want you to tell me who you are, and then you can remove the I Want You so it reduces to just tell me who you are. And then that reduces to who are you. So there was that recursive element built into the responses as well.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, AIML is based on XML and XML was very popular at the time. One thing that appealed to me about XML for the purpose of writing chatbots was that I always say XML has an implicit print statement. So when you write the responses, you don't have to put in an expression that says print blah, blah, blah, something between the parentheses because the XML already just provides the text inside the markup. So the response is just the text inside the markup. And then basic unit of knowledge in AIML I call the category, which is like the rules I was talking about a second ago. So the category consists of a pattern that matches some input, some natural language input, and then a response called the template. The reason it's called the template is because it's not exactly the answer, but it's a template.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Well, it was basically the idea that I could build on the ELISA program. So the ELISA program had about 200 rules, 200 stimulus response rules. And you could think of that as a pattern and a response. And my idea was to kind of was to build kind of a super Eliza where instead of 200 rules, you had thousands and thousands of rules. And in fact, by the time I was entering those contests, I got Alice up to about 50,000 patterns and responses.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“But the human eye is more like concentric rings of pixels with higher and higher resolution towards the center. We call it a log map. And so we had developed a sensor that had that log map, log map pixel organization. In order to use the camera like that effectively, you have to be able to point it. So we developed a little motor, a high-speed pointing motor based on a direct drive design. And that motor could point the camera, the eye camera in pan and tilt directions very, very quickly. And again, it was a very simple kind of actuator, simple sensors, and it could move very quickly, could move actually faster than the human eye. So you'd sort of see this thing whipping around and looking at different things. And it was very lifelike.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Like I said, we were working on the minimalist philosophy of robotics. And yeah, at that time I was working on the development of a robot eye. And by that I mean a visual sensor that's based on the architecture of the human eye. So the human eye differs from a TV camera in the sense that a TV camera is basically a square grid of square pixels”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“That period was the Rumba. If you think of the Rumba rolling around and bumping into things and changing its direction, it's all basically just a stimulus response application. So we call that stateless. So it's sensing something and then taking an action based on what it's sensing, you know, changing direction, for example. So that whole approach of minimalism was also on my mind at the time. And that kind of dovetailed with the very simple approach of the ELISA program, which was also kind of a stimulus response. You know, it was so simple that it could respond very quickly. It didn't have to go and do a line of computations to come up with the responses.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“that planted a seed in my mind and I didn't really do anything about it for about five years. So another thread that led to the development of Alice or the inspiration for Alice was around that time in the early 90s, it was the end of the Cold War. And so there was decreased amount of government funding available for AI and robotics research compared to the 1980s. And so a number of us in the robotics field, I was working in robotics at the time, got interested in the idea of minimalism, robot minimalism. And basically that was the idea that we could build robots with very simple, inexpensive sensors and actuators, you know, very commodity microprocessors. And as a result of that, you could actually get more lifelike behavior out of these robots than you could with approaches people have tried in the past with much larger computers and so forth. One of the interesting inventions that came out of it.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“When he first created the program. The other ironic thing about Eliza was that up until very recently, I would say, well, let's say 20 years ago, Eliza was by far the most widely distributed, popular and well-known AI application. if you knew anything about AI up until maybe the year 20, then you would know about El”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And so he wrote a whole book after that, Computer Power and Human Reason, where he criticized the whole field of AI and his ELISA program in particular. You know, it's really hard to imagine this now that someone would come up with a new AI application that's very engaging and popular if people are using it. Then they would say, oh no, this is too dangerous. We have to put the genie back in the bottle. I think most people now would run out and try to find venture capital to start a company to commercialize.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“And not only that, the inventor, Joseph Weisenbaum, ended up pulling the plug on it because he thought it was too dangerous. He thought that people were reading too much into it and was actually there. It was a psychiatrist program so people were trusting it with their personal issues and problems. They were surprised to find out that Weisenbaum could read all the transcripts of their company.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“in terms of being the most human. And that first year, the bot that won was simply based on the old Eliza psychiatrist program, which if you're familiar with that, was a very primitive chatbot developed by Joseph Weisenbaum in 1966. And it had very few responses, but it had some clever tricks to it. It could sort of match keywords in the input. it had canned responses associated with those keywords. It could invert prepositions so, you know, if I said I came here to talk to you, then it would repeat back you came here to talk to me. So it did that sort of pronoun swapping trick. But when I was in graduate school in the 1980s, this Eliza program was basically considered kind of a dead end or at best kind of a hoax.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT
“Into this kind of stuff. That's absolutely right. You know, I like to say that nobody knew what artificial intelligence was until a couple of years ago. And now I'll be sitting in a restaurant somewhere and I'll hear a conversation at the table next to me and they're talking about AI. Well, anyway, there are several threads that came together that inspired me to work on the Chatba Alice. And I'll just pull on a couple of those threads here. One is that in 1990, I read an article in the New York Times about the first Loebner Prize contest. Now, the Loebner Prize was an annual Turing test, an annual contest based on the Turing test funded by a rather eccentric philanthropist Hugh Loebner. And the story with the very first contest was that none of the programs competing came close to passing the Turing test. They were all just terrible chatbots. But Loebner awarded a bronze medal every year to the chatbot that was ranked highest by the judges.”
2025-12-31 · We Study Billionaires · TECH011: The History of AI and Chatbots w/ Dr. Richard Wallace (Tech Podcast) · IDENTIFIED FROM THE TRANSCRIPT