Assertion Not checkable as stated
Domingos: Neural Network Opacity Often Precludes Deep Learning From Practical Deployment
“With some types of machine learning, like, for example, neural networks and deep learning, it's very opaque, right? What is learned is this big jumble of lots of parameters and all near functions, and nobody really understands what's going on. Which, in fact, …”
Insight
Domingos: Knowledge Induced From Empirical Data Is Inherently Uncertain
“Any knowledge that you induce from data is necessarily uncertain, because you never know if you generalized correctly or didn't.”
Insight
Domingos: Humans Are Systematically Overconfident in Evolutionary and Cultural Knowledge
“Conversely, a lot of the knowledge that we have from evolution and from experience and from culture, we often tend to think of it as much more certain than it really is. We have this great tendency that's been well studied by psychologists to be overconfident …”
Insight
Domingos: Machine Learning Masters Single Domains While Humans Synthesize Broadly
“Machine learning today is very good at learning about one thing at a time. The thing that humans have is that they can bring to bear knowledge from all sorts of directions.”
Assertion Supported
Domingos: Evolutionary Machine Learning Generated Patented Circuits Outperforming Human Designs
“People have developed new types of radios and amplifiers and electronic circuits using this type of machine learning, and they've actually gotten patents for them. So they work better than the ones that were developed by human engineers. They're typically comp…”
Assertion Supported
Domingos: Automated Robot Scientist 'Eve' Discovered a New Malaria Drug
“A couple years ago, Eve actually discovered the new malaria drug.”
Prediction Not checkable as stated
Domingos: Medical AI Diagnosis Will Spread Initially in Low-Resource Settings
“But, you know, eventually it is going to happen, and it is starting to happen, for example, in situations where doctors are not available, and so nurses can use this, or for patients that need, you know, constant monitoring, or in low resource situations where…”
Assertion Supported
Domingos: Human-AI Centaur Teams Outperform Standalone Computers in Chess
“The best chess players in the world today are what are called centaurs in the community. They're a team of a human and a computer. So a human and a computer can actually, together, can actually beat the computer.”
Prediction Not checkable as stated
Domingos: Human-Computer Collaboration Will Work Best for Most Jobs
“But I think for the foreseeable future in most jobs, it will be a combination in human and computer that works best.”
Assertion Supported
Domingos: The Stock Market Is Largely Algorithms Modeling Each Other
“The stock market is largely a bunch of algorithms trading against each other. And in fact, what these algorithms are doing Whether or not they know it is modeling each other.”
Insight
Domingos: Data Network Effects Create Major Competitive Moats for Machine Learning Incumbents
“There's this network effect of data where if you have a good product and people start using it, then you have a lot of use this, for example, you know, how Google has built up such an unassailable position in search, right? Is like you use their search engine.…”
Prediction Not checkable as stated
Domingos: Consumer Adoption of AI Will Force Doctors to Adapt
“And once, for example, these machine learning systems become more widely available as they are becoming, people will start using them and the doctors will be forced to catch up.”
Prediction Not checkable as stated
Domingos: Machines Will Handle Most Decisions While Humans Retain Key Choices
“Ultimately I think most things will be done by machines, except the really key decisions that people will always want to retain, even though they make them with advice from the machines.”
Assertion Not checkable as stated
Domingos: AI Has Not Yet Achieved Continuous Recursive Self-Improvement Loops
“Having said that, this is still quite limited in what it can do, and it's not, we don't have enough at this point for this thing to set up this loop where it just keeps getting better and better. That hasn't happened yet”
Prediction Not checkable as stated
Domingos: Machines Will Build Far More Complex Models Than Humans Can
“So what's going to happen is that the machines are going to be able to learn much more complex models of the phenomena than human beings ever could, and this is good, right? Because with those better models, we can make better decisions. With a better model of…”
Prediction Not checkable as stated
Domingos: Machine Learning Algorithms Will Get Better at Explaining Themselves
“I think what's going to happen is that partly the learning algorithms are going to have better, to get better at explaining to people what they're doing.”
Insight
Domingos: Human Competition Will Endure Despite Superhuman Computers
“I think more likely what will happen is that people will still be playing each other, even though the best is our computers in the same way that, you know, there's race cars that go way faster than people. But we still have people doing, you know, in the Olymp…”
Insight
Domingos: Autonomous Vehicles Only Need to Beat Humans, Not Reach Perfection
“The cars don't have to be perfect before we start using them instead of people. They just have to get better than people.”
Prediction Not checkable as stated
Domingos: Symmetry Group Theory Could Spark Machine Learning's Sixth Paradigm
“Because I think this is something that has not been exploited in machine learning and might be the origin of that sixth paradigm.”
Assertion Supported
Domingos: Major ML Algorithms Are Mathematically Proven Universal Function Approximators
“And there are several major such algorithms today that have mathematical proofs that if you give them enough data, they can learn any function.”
Insight
Domingos: Understanding Learning Algorithms Differs From Understanding Their Output Models
“Having said that, you know, we, the machine learning researchers and the data scientists, we actually have a good understanding of how the learning algorithm itself works. You know, what is it that it does to learn, and how could you make it learn better? And …”
Insight
Domingos: Deploying Machine Learning Causes Subjects to Adapt Adversarially
“So what happens whenever you deploy a machine learning system is that the people who are being modeled Change their behavior in response to the system. Sometimes in benign ways, but sometimes in adversarial ways.”
Assertion Supported
Domingos: Netflix and IBM Watson Already Use Basic Forms of Meta-Learning
“And this type of meta learning in certain basic forms is actually already widely used today. Like for example, Netflix uses this type of thing to recommend movies. It doesn't just use one learning algorithm. It uses a whole bunch of them. And then another algo…”
Assertion Partly supported
Domingos: IBM's Deep Blue Used Classical Search With No Machine Learning
“So Deep Blue was very much classic AI. There was no machine learning involved. Deep Blue essentially, it was just doing a very a clever and very extensive search for the best moves to make.”
Pedro Domingos