How to Teach Artificial Intelligence Some Common Sense | WIRED
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Edit Last edited by Open Library Bot April 14, History 1 edition of New thought common sense and what life means to me found in the catalog. April 14, Edited by Open Library Bot. February 9, Edited by ImportBot. Found a matching record from Library of Congress. The team then uses various machine-learning techniques—some old-school statistical analyses, some deep-learning neural nets—to draw lessons from those statements.
If they do it right, Etzioni believes they can produce reusable Lego bricks of computer reasoning: One set that understands written words, one that grasps physics, and so on. When she had gathered 25, of these marked-up sentences, she used them to train a machine-learning system to analyze sentences it had never seen before and infer the emotion or intent of the subject. At best, the new system worked only half the time. Indeed, they regard it as a very useful tool. Deep learning is garbage in, garbage out.click
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Another challenge is visual reasoning. Other Allen Institute scientists built the Sims -like house, filling it with everyday items and realistic physics—kitchen cupboards full of dishes, couches that can be pushed around. Then they designed the robot, which looks like a dark gray garbage canister with arms, and told it to hunt down certain items.
After thousands of tasks, the neural net gains a basic grounding in real-life facts. It just looks behind the television. But how long will it take, and what will the final products look like? Building common sense, it would seem, is uncommonly hard.
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For example, you could simply sit down and write out, by hand, all the rules that tell a machine how the world works. Brute-force, handcrafted AI has become unfashionable in the world of deep learning. Cyc is enormously more capable than a chatbot and has been licensed for use in health care systems, financial services, and military projects. But a bit of hand coding could be how you replicate some of the built-in knowledge that, according to the Chomskyite view, human brains possess. As it played Breakout , the system developed the ability to weigh different courses of action and their likely outcomes.
This worked in reverse too.
If the AI wanted to break a block in the far left corner of the screen, it reasoned to put the paddle in the far right corner. Crucially, this meant that when Vicarious changed the layout of the game—adding new bricks or raising the paddle—the system compensated. It appeared to have extracted some general understanding about Breakout itself. Granted, there are trade-offs in this type of AI engineering. Having processed millions of photos, it knows not only what makes a cat a cat but also the fastest way to identify one.
When the Vicarious AI works well, it can learn from much less data. Much as with the Breakout system, they endowed their AI with some abilities up front, such as knowledge that helps it discern the likely edges of characters. In contrast, a neural net needed to be trained on more than 2. Others are building common-sense-like structure into neural nets in different ways. Two researchers at DeepMind, for instance, recently created a hybrid system—part deep learning, part more traditional techniques—known as inductive logic programming. The goal was to produce something that could do mathematical reasoning.
In contrast, the hybrid DeepMind system seemed to understand the rule and went past with no problem. But he remains steadfast that deep learning, properly crafted, can provide the answer. He disagrees with the Chomskyite vision of human intelligence. He thinks human brains develop the ability to reason solely through interaction, not built-in rules. Like an academic lab, LeCun and his researchers publish their work for others to access.
LeCun, who retains the rich accent of his native France and has a Bride of Frankenstein shock of white in his thick mass of dark hair, stood at a whiteboard energetically sketching out theories of possible deep-learning advances. It was weirdly unsettling to discuss humanlike AI with those images around, because of course HAL , 6 the humanlike AI in , turns out to be a highly efficient murderer. And this pointed to a deeper philosophical question that floats over the whole debate: Is smarter AI even a good idea? Some AI thinkers worry that the ability to talk to humans and understand their psychology could make a rogue AI incredibly dangerous.
Elon Musk is sufficiently convinced of this danger that he has funded OpenAI, an organization dedicated to the notion of safe AI. Deep learning can conquer chess, but it has no inborn will to play. What does concern him is that current AI is woefully inept. This is partly why Etzioni is so determined to give AI some common sense. Etzioni notes that the dystopic sci-fi visions of AI are less risky than near-term economic displacement.
For many, many years, we have made a huge effort to make our cast members, as we call our employees, a diverse group of people. We also believe in diversity because the more diverse you are as an organization, the more diverse are the opinions that get expressed, which sometimes creates friction, and friction slows down the machine. When the machine slows down, good things can happen. If it is just sliding along with no friction, you get the easy solution; you get mediocrity. We work very hard on getting diversity at the top of the organization, and like many organizations we still have room to improve.
That will make us more creative. We want people who work here to look at the world differently from one another. The important thing is that they look at the same problem and bring their own individuality to the solution. We are always looking for creative solutions to problems—and solutions that cost less money.
Remember we still run a business; art and commerce go together. And in the end, the most creative and sound solutions will emerge. Finding a solution is, by definition, a creative act. It was called Outrageous Fortune. The script called for a scene in an apartment where the main character, played by Shelley Long, asks her parents for money to go to ballet school. The entire movie was too expensive, and here was a scene that could be cut. People disagreeing. No sets. No additional actors.
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And you know what? The scene was so much better and so much funnier than what the script originally called for because somebody had a different point of view about how it could be done. There was a nice resolution of conflict that made sense in terms of creativity and cost. Another boost to creativity and cost can be delay. But more often, some delay helps.
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And if a manager is not giving answers because he is on the golf course, then he should go work on his putting and forget the entertainment business. Now, not everybody immediately understands the virtue of delay. At Paramount, there was a very eager and effective administrative executive who suggested to my boss that I be fired for not giving quick answers. This was a very organized guy who could move a wall six feet, if he was told which way to go, and he liked to move very fast.
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Why is it you want Michael Eisner fired? This was a very unpleasant moment for this executive, as you might imagine. But he answered. Sometimes the best thing to do is delay—because it buys you two things. First, it buys you time to incubate an idea, to let it simmer in your brain so you can edit it yourself and improve on it. And the second thing it buys is the ability to see the truth.
Because a delay lets you know how deeply someone believes in an idea. And then you can negotiate for what you want—like another version of the idea or another director for the movie. So we like to build a bit of delay into the creative process at Disney. Usually we talk about ideas. Some people think we talk them to death. But discipline is part of the creative process, contrary to popular belief. There is a popular notion that creative people are impulsive and individualistic to extremes.
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