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Behind the Numbers: an EMARKETER Podcast
Artificial General Intelligence Explained: When Will AI Be Smarter Than Us? | Behind the Numbers
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- [00:01]
Marcus
Are your brand campaigns as effective as they could be? Look, Marcus, I'm going to be real with you. Probably not. I understand. If you're only getting insights when the campaign is over, then the answer is a resounding no. To make better campaign decisions, you need real time measurement. You need lucid measurement by Sint. Let's be real. Discover the power of real time brand lift measurement@sint.com insights that's cint.com/insights. Hey gang, it's Monday, June 30th. Gago, Jacob and listeners, welcome to behind the Numbers new marketer podcast made possible by Sint. I'm Marcus and joining me for today's show we have two people, Senior analyst writing for our AI and tech briefings, based in New York is Gargio Savilli.
- [00:56]
Gargio Savilli
Hey Marcus. Hey Jacob. Happy to be with you guys.
- [00:59]
Marcus
We're also joined by our analyst who writes longform about the same topics. Living in California is Jacob Bourne.
- [01:06]
Jacob Bourne
Thanks for having me today, Marcus.
- [01:07]
Marcus
Yes, sir. Today's fact, gentlemen. When you recall a memory, you're actually reconstructing it, and it also changes each time. So what am I talking about? H.L. rodiger, the third from the University of Washington in St. Louis wrote a paper on the psychology of reconstructive memory. So they explained that when we perceive and encode events in the world, we construct rather than copy the outside world as we comprehend the events. So if perceiving is construction, then remembering the original experience involves reconstruction. We use traces of past events, general knowledge, our expectations and our assumptions about what must have happened. Because of this, recollections may be filled with errors called false memories, which include inferences during encoding information we receive about an event after its occurrence and our perspective during the retrieval. This makes me feel better.
- [02:21]
Jacob Bourne
That's quite the fact of the day, Marcus. That's.
- [02:25]
Marcus
I went too deep.
- [02:26]
Jacob Bourne
Yeah.
- [02:29]
Marcus
So another way of looking at it is, so it says, contrary to popular belief, memory does not work like a video recorder, faithfully capturing the past to be played back accurately at a later time. Rather, even when we are accurate, we are reconstructing events from. From the past, when we remember. And the CBC piece from the Nature of Things, an article by Canadian writer and director Josh Freed, who is saying once our brain has a new version of the story, it forgets and erases the former version. So it's almost like a game of telephone. We're just going to.
- [03:05]
Jacob Bourne
Everything is recollection subjective. That, you know, our perception of the world is always subjective.
- [03:12]
Marcus
Exactly. Anyway, that wasn't heavy. Enough. Today's real topic, what exactly is artificial General intelligence? So who exactly came up with the term Artificial General Intelligence or AGI? Well, Gil Press of Forbes notes that the term AGI was coined in 2007 when a collection of essays on the subject was published. There was a book titled Artificial General Intelligence. It was co edited by Ben Goertzel and Cassio Panachin. Although they seem to say that they sourced the idea from, for the title from a former colleague, AI researcher Shane Legg. And in the book Gents, they say, or define AI as they say AGI is loosely speaking, they say AI systems that possess a reasonable degree of self understanding and autonomous self control and have the ability to solve a variety of complex problems in a variety of contexts and to learn to solve new problems that they didn't know about a time about at the time of their creation. So it's not the most defined term. It wasn't then, it doesn't seem to be now. Jacob, when we were discussing this episode that even definitions today are, you said, murky and not really agreed upon. So I've asked you and Garjo to come up with your own definitions to craft your own definition of AGI. What's yours?
- [04:45]
Jacob Bourne
Yeah, I mean, I think an easy one is just an AI model that is on par in terms of intelligence and capabilities with most human beings. But the key here is that is the word general, because the thing about human intelligence is that we're good at a lot of different things, we can solve a lot of different problems, we have a wide variety of capabilities. And historically AI, when it was first starting to be Developed in the 1960s, the goal was to make a machine that kind of thinks like people. But it turned out that AI is actually generally good at a very narrow area of things. And so I think that's how this term AGI came about, because it's trying to get to an AI model, build an AI model that really is good at a wide variety of things like humans are. So it's Excel in one category of things.
- [05:41]
Marcus
Yeah, so that'll be an example like so IBM supercomputer, Deep Blue, when it beat Gary Kasparov, the chess master, it was good at just that one thing. So that's narrow AI, correct?
- [05:49]
Jacob Bourne
Narrow AI. Right. And I think, you know, with ChatGPT in 2022, we've seen it's becoming more general, but it's still not as general as a human.
- [06:02]
Marcus
So it does seem to be a big part of this. Garjo, obviously it's in the name artificial general intelligence, and Google says there's that generalization ability. AGI can transfer knowledge and skills learned in one domain to another, enabling it to adapt to new and unseen situations effectively. So that's a big component. Would you agree with what Jacob said and what else would you tack on?
- [06:27]
Gargio Savilli
I do agree. I think it's it, you know, it requires, you know, beyond the narrow understanding of various topics. I also think autonomy is a big part of AGI. So you have, you can think of it as a live algorithm that's constantly learning, that can make decisions, that understands the nuances in between subject matters. Right. And I think that's the elusive part of AGI because sure, it could surpass a lot of human thought, but at the same time, how it applies that thought might not be on a human level.
- [07:12]
Marcus
Yeah. One of the questions here is what does a human level even mean? So I looked at the IBM definition and they said AGI is a hypothetical stage in the development of machine learning in which an AI system can match or exceed the cognitive abilities. This word cognitive keeps coming up a lot in a lot of these definitions. Cognitive abilities of human beings across any tasks. And so when you're thinking about cognitive abilities, McKinsey, their definition, they say AGI may replicate human like cognitive abilities, including reasoning, problem solving, but there's a ton. Perception, learning, language comprehension, navigation, social and emotional engagement, et cetera. So Bajaran Lanier, who popularized the term virtual reality, asks, does crossing some threshold make something human or not?
- [08:08]
Jacob Bourne
Yeah, and I think that's a great question. What is the threshold?
- [08:13]
Marcus
Exactly?
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Jacob Bourne
Human intelligence and cognition itself is poorly understood. And so now you're trying to take a machine and then compare a too human, essentially. And I mean, no one has really agreed upon where that threshold is. And so that's why, actually I like anthropic CEO Dario Amadai, who says that, you know, he prefers the term powerful AI to AGI because it's a bit more vague. And you know, AGI has sort of become a marketing term because again, it hasn't really been defined in a precise way because it's difficult. How are you going to really say, how would you know when a model is really on par with the intelligence capabilities of most people? And would companies, AI companies agree upon that?
- [09:05]
Gargio Savilli
Yeah, following up on that, I think vagueness is going to be a continued aspect of this. No one wants to nail down a definition because the competitors are just going to go back and say, well, well, no, because this is what we think. Right. So I, I don't Expect a consensus. Neither do I expect someone to say, yeah, this is AGI, we've achieved it. It does this because it's, you know, the fallout from that will be significant. Right. So they're going to keep it vague. And I think it's going to be nebulous. And, you know, the target is a moving target, considering, you know, they say, oh, we're close to it, but some say, no, we're not. And I think that just goes to show how complicated just defining AGI is going to be moving forward.
- [10:00]
Jacob Bourne
Yeah. And to make it more complicated, there's another term that has been floating around which is super intelligence, which is an AI model that exceeds even the intelligence of the smartest people. And that's also something that some AI researchers think is possible, so even exceeding the capabilities of AGI.
- [10:21]
Marcus
So is it fair to say that a big part of why we want to create AI that is on par with or smarter than a human is because of the Turing Test, which came from computer scientists, English computer scientists, Alan Turing, he was basically, can you trick a person into thinking a computer is a human? Is that where all of this stems from?
- [10:49]
Jacob Bourne
Well, I think that the Turing Test is just a test that grew out of this desire to create AI that's as smart, as smart as humans. But I think the Turing Test speaks to this problem of how would you know? Because if it's just tricking you, then it's a performance. It's not really intelligent. Right, yeah. So I think that's part of it is humans, we know that we understand the world we're living in. And so even though AI can do things, does it really understand what it's doing? When you're talking to a chatbot and its output is really great, but does it understand the words that it's saying? And so I think that's a big part of what we think about in terms of human intelligence is we understand what, you know, the world, we understand the language we're using, the problems we're trying to solve. But it doesn't seem like AI does, at least not yet.
- [11:52]
Marcus
One of the definitions, this one coming from Amazon, says AGI is a field of theoretical AI research that attempts to create software which, with human like intelligence and the ability to self teach performing tasks, it's not trained or developed. For the self teaching part, would we agree that that is AGI or do we think that actually goes beyond to more towards super intelligence?
- [12:16]
Gargio Savilli
I think that's part of AGI just because, you know, as we discussed, AGI is an Ongoing thing. Right. It's an unfinished state. And in order for it to continue evolving, it needs to continue learning the, you know, the issue there is it, it can definitely learn at least all the information that's, you know, on the Internet, definitely. But what it lacks again is, you know, just general reasoning, common sense, empathy, social intelligence. That's what it needs to unlock to sort of, you know, not, not be smarter than humans, but at least be on par with the way humans process the world around them cognitively. Right.
- [13:09]
Marcus
Speaking about how they process the world cognitively, common sense knowledge seems to be part of this too. Google was saying AGI has, should have a vast repository of knowledge about the world, including facts, relationships and social norms, allowing it to reason and decisions based on this common understanding. Can you have common. I mean, how much is common sense intrinsically linked to being a human? Go on, please.
- [13:38]
Jacob Bourne
Well, it seems very linked to being human. And I think there is a distinction that even an AGI or superintelligence won't be human, but it's this measure of intelligence and capabilities that we're trying to determine. Not so you can be as smart.
- [13:55]
Marcus
As a human, but still not be a human.
- [13:58]
Jacob Bourne
Right. And I think, you know, this lack of common sense is where a lot of criticism of AI's capabilities come in. But then the flip side is saying, well, people often act without common sense too. People make mistakes, we sort of hallucinate, we do all these things we criticize AI for. And so maybe AI's hallucinations are different, maybe its lack of common sense is different, but it doesn't mean it's not as intelligent. So that's one counter argument. I think a big limitation with current AI models is that they're trained on Internet data, not real world data. For the most part now that's changing because we're seeing these sort of models being developed that are designed for robotics. And I think the future outlook is to have AI powered robots collecting real world data that then can be used for model training. And I think that, that it could indicate a threshold that once that kind of model training is more heavily underway, that we might see AI advance closer.
- [15:05]
Marcus
To an AGI and by real world data. Could you give folks an example what you're talking about?
- [15:09]
Gargio Savilli
Yeah.
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Jacob Bourne
So you have an AI powered robot that's out in the world, has sensors that is collecting data from things it touches, interactions it has with people, things it's seeing as it's moving around the world. It's not just using Internet data to produce output. It's Collecting data it's getting from interactions in the real world in real time.
- [15:33]
Marcus
Like a driverless car, so to speak, right?
- [15:35]
Jacob Bourne
Yeah, exactly, like a driverless car.
- [15:38]
Marcus
So speaking of driverless cars, actually this is a good pivot here because open AI, they've got a few different definitions of AGI. They say it's a highly autonomous system that outperforms humans at most economically valuable work. And then in a profile with the New Yorker, OpenAI CEO Sam Altman defined AGI as the equivalent of a median human that you could hire as a co worker. So there are a few of the definitions from, from OpenAI. But Maxwell Zeff of TechCrunch notes that OpenAI created the five levels it internally uses to gauge its progress towards AGI. So similar to Jacob, I think we've talked about this before, Gajo, perhaps as well, the, the six levels of autonomous driving, you've got these six different stages from zero to five. Everything from you drive the car completely yourself to the car drives itself completely by itself up to five. And then with, with this, they have the five levels from which they measure, measure AGI internally. So you have the first level, chatbots, chat GPT, second level, the reasoners, open AIs, 01, then the agents, level three. That's, that's where we seem to be now or coming now. Innovators, level four, AI that can help invent things. And then the last level, organizational AI that can do the work of an entire organization at level five. Do we think it's more and more likely that we end up with, with something more akin to this, that, you know, we get a set of, of rough guidelines on when something has reached a certain level of AGI, as opposed to this one overarching AGI threshold.
- [17:28]
Jacob Bourne
Yes. You know, AI, at the end of the day, it's, it's interesting, it's, it's research, but it's also a marketable tool. And in order to market it, you have to have, you have to have, you know, the specs on what you're marketing. And so I think it is, we're going to see more of these sort of levels, I guess, be, you know, fleshed out as AI advances. I think it's a bit different from really arguing, in essence what we, what we mean when we say an AGI, I mean, reducing it to what Sam Altman saying in terms of, you know, an economic driver is kind of diminishing it a bit because human intelligence spans much further than the tasks we do at work.
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Marcus
Economic value.
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Jacob Bourne
Yeah, so I think that that Kind of almost constrains what an AGI is, which is maybe good again if we're just thinking about it in terms of a product. But I think that's just one limited way of looking at it.
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Marcus
Yeah, that's a great point though because we have to think about the people who are telling us what AGI is or isn't are people who run companies.
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Jacob Bourne
Yeah, yes.
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Gargio Savilli
And they're all competing with each other. You know, they're trying to productize their models and they're getting, I mean the competition is on every level now, right, from from agents to chatbots to search. And I think for most people, most companies, the concept of AGI really won't, won't really move the needle. But specific solutions based tools, you know, updates to the functionality of what bud AI can do. I think that is what matters right now. And I think for the foreseeable future that's how it's going to be measured. Right.
- [19:30]
Marcus
Yeah, we touched on this earlier, but I want to come back to it because I think it's a really interesting question which is are AI systems smarter than people already? And uh, Nicolo Conte, visual capitalist, wrote a piece about the IQ levels of AI using data from tracking AI that ranked the smartest AI models based on their performance on the MENSA Norway IQ test. Um, there are a bunch of different types of IQ test. Um, and this is one of the main ones. For context, the average human IQ score ranges from 90 to 110. A score above 130 is typically considered genius level. And the results found that up Top ranked number one was OpenAI's text only O3 model scoring a 135 on the Mensa IQ test, placing it comfortably in the genius category. There were six other models that were above the top end of the human average above 110. There were two Claude models from Anthropic, two Gemini models from Google, another one from OpenAI and one from Grok model from XAI. And then you had 10 more that were between the average human IQ score ranges of 90 to 110. So Gajo, are AI systems smarter than people already?
- [20:54]
Gargio Savilli
I think if you break it down we see that they've surpassed us in certain things. So like image recognition, I think they surpassed humans in 2015, speech recognition that was 2017 and then language understanding that was recent 2020. They match humans in that. And again these are narrow fields of measure. Right. You still need to put that together with the special sauce that makes us humans to determine whether they are smarter. They're definitely capable at certain tasks. They don't get tired, there's no fatigue involved. Right. So you could, you could say they have that endurance factor. So for specific tasks that are, I guess really just crafted with guardrails. Sure. They could probably match or surpass also on a case to case basis. Right. Generally I still don't think so. They still lack, you know, common sense, they're not good at abstract reasoning. And at times, you know, that that's what defines sort of intelligence, you know, the ability to problem solve on the spot. Right. And to just shift paradigms. What AI will try to do is if it doesn't know the answer, it's going to make up something because it's not programmed to say, hey, you know what? I don't know that. No, no AI has ever told me that. Instead they'll fabricate something. Sounds like, and try to justify it.
- [22:36]
Marcus
Some people, yeah, people built them, so are going to be a reflection of us. But you're right, there are people out there who will say I don't know. And no AI at the moment at least is going to say that.
- [22:48]
Jacob Bourne
Yeah, I mean, I agree mostly with Gajo Said. I'd also add that I think that IQ tests aren't a great benchmark of AGI, you know, determining if we're AGI level or, you know, surpassing human intelligence. If they were, then we would say, oh look, the AI model, you know, score genius level, then we should be able to, you know, let it operate and perform tasks without human supervision, which it's not at that level yet.
- [23:18]
Marcus
Right.
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Jacob Bourne
And of course the reason why is because it really can't do what a human could do. And again, it gets back to this general level intelligence, which I don't think that IQ models really test for. It says for something very specific versus being able to have a deep understanding of the real world and solve problems in that real world. I don't think IQ tests really do that.
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Gargio Savilli
Yeah. I think any tests that you use would have to evolve with the AI available. You can't set a standard and say this is it because it's continuously changing.
- [23:55]
Marcus
Yeah.
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Gargio Savilli
Is it more of a numbers thing, more of a comprehension thing? And really that, that I think that's going to be the challenge.
- [24:04]
Marcus
Emotional intelligence.
- [24:05]
Gargio Savilli
Yep. Yeah.
- [24:06]
Jacob Bourne
Yeah. But I think at the same time you look at how much the vast quantities of data that AI models are able to process at a much faster rate than humans can think and then make predictions and draw insights from that. I mean it's, it's stunning. And people can't even come close to doing that. So think it's it's getting more general, but it's still quite a long way to go before it reaches the general level of human intelligence.
- [24:34]
Marcus
Most Americans think AI will become more intelligent than people. According to a 2025 YouGov study, 47% of people said that AI will eventually become more intelligent than people. 13% think it already is is 24% said it's unlikely. The rest weren't sure. That's what we've got time for for this episode Friday, we will be back talking about the ways that AGI might change our lives and when it's most likely to get here, if at all. Of course. Thank you so much to my guests. Thank you to Garjo.
- [25:09]
Gargio Savilli
Thanks again.
- [25:11]
Marcus
Yes. And to Jacob.
- [25:12]
Jacob Bourne
Thanks for having me.
- [25:14]
Marcus
Yes, indeed. Thank you, friend. Thank you to the whole editing crew and to everyone for listening in to behind the Numbers new Marketer video podcast made possible by Synth. Subscribe Follow Leave a Rating and also maybe a cheeky little review if the mood takes you. Sarah will be back with the Reimagining retail show for you on Wednesday.