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ARTIFICIAL INTELLIGENCE (AI)
UNDERSTANDING PICTURES
Fei-Fei Li: How we're teaching computers to understand pictures
Peter Burgess COMMENTARY ... added November 2023)
When I first saw this video about 10 years ago I was both impressed and disappointed. Dr. Fei-Fei Li has a clarity of intellectual vision that is impressive ... but the characteristics of AI that are the reality means that only a very few are going to have access to the technology and there is a very real risk that the few who have the resources to access this technology when it is mature and useful ... that is with real utility ... are likely to be those who are greedy, evil, etc.
Meanwhile, the rest of us ... around 8 billion people ... are going to be stuck in a very degraded world.
This is not wild conjecture. The progress of the world over the past four decades has already gone down this track. The world is substantially more 'unequal' now in 2023 that it was at the start of the US Reagan administration early in the 1980s. While many of the widely followed economic statistics show substantial progress 'in aggregate', a small amount of segmentation of the data show that a few have progressed mightily while the majority have regressed significantly.
I remember a concern of economists when I was a student in the late 1950s that the world's people whould be able to satisfy all their needs with only 30 hours of work a week and that this would be a problem that could be solved by much more 'cultural' activity ... a desirable reorganising of priorities. In fact, this problem has been solved by a massive removal of benefits from most of us to allocate to the very few people at the 'top'. This problem has been getting bigger and bigger for around 40 years and very little has been done to address it ... rather instead of decelerating, the negative changes have accelerated with no sign of stopping!
Peter Burgess
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Fei-Fei Li: How we're teaching computers to understand pictures
When a very young child looks at a picture, she can identify simple elements: 'cat,' 'book,' 'chair.' Now, computers are getting smart enough to do that too. What's next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art — including the database of 15 million photos her team built to 'teach' a computer to understand pictures — and the key insights yet to come.
As Director of Stanford’s Artificial Intelligence Lab and Vision Lab, Fei-Fei Li is working to solve AI’s trickiest problems — including image recognition, learning and language processing.
Why you should listen
Using algorithms built on machine learning methods such as neural network models, the Stanford Artificial Intelligence Lab led by Fei-Fei Li has created software capable of recognizing scenes in still photographs -- and accurately describe them using natural language.
Li’s work with neural networks and computer vision (with Stanford’s Vision Lab) marks a significant step forward for AI research, and could lead to applications ranging from more intuitive image searches to robots able to make autonomous decisions in unfamiliar situations.
What others say
“Computer software only recently became smart enough to recognize objects in photographs. Now, Stanford researchers using machine learning have created a system that takes the next step, writing a simple story of what's happening in any digital image.” — Stanford News, November 18, 2014
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