The following script is from Artificial Intelligence, which aired on Oct. 9, 2016. Charlie Rose is the correspondent. Nichole Marks, producer. <\/p>\n
The search to improve and eventually perfect artificial intelligence is driving the research labs of some of the most advanced and best-known American corporations. They are investing billions of dollars and many of their best scientific minds in pursuit of that goal. All that money and manpower has begun to pay off. <\/p>\n
In the past few years, artificial intelligence -- or A.I. -- has taken a big leap -- making important strides in areas like medicine and military technology. What was once in the realm of science fiction has become day-to-day reality. Youll find A.I. routinely in your smart phone, in your car, in your household appliances and it is on the verge of changing everything. <\/p>\n
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On 60 Minutes Overtime, Charlie Rose explores the labs at Carnegie Mellon on the cutting edge of A.I. See robots learning to go where humans can'... <\/p>\n
It was, for decades, primitive technology. But it now has abilities we never expected. It can learn through experience -- much the way humans do -- and it wont be long before machines, like their human creators, begin thinking for themselves, creatively. Independently with judgment -- sometimes better judgment than humans have. <\/p>\n
The technology is so promising that IBM has staked its 105-year-old reputation on its version of artificial intelligence called Watson -- one of the most sophisticated computing systems ever built. <\/p>\n
John Kelly, is the head of research at IBM and the godfather of Watson. He took us inside Watsons brain. <\/p>\n
Charlie Rose: Oh, here we are. <\/p>\n
John Kelly: Here we are. <\/p>\n
Charlie Rose: You can feel the heat already. <\/p>\n
John Kelly: You can feel the heat -- the 85,000 watts you can hear the blowers cooling it, but this is the hardware that the brains of Watson sat in. <\/p>\n
Five years ago, IBM built this system made up of 90 servers and 15 terabytes of memory enough capacity to process all the books in the American Library of Congress. That was necessary because Watson is an avid reader -- able to consume the equivalent of a million books per second. Today, Watsons hardware is much smaller, but it is just as smart. <\/p>\n
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What happens when Charlie Rose attempts to interview a robot named \"Sophia\" for his 60 Minutes report on artificial intelligence <\/p>\n
Charlie Rose: Tell me about Watsons intelligence. <\/p>\n
John Kelly: So it has no inherent intelligence as it starts. Its essentially a child. But as its given data and given outcomes, it learns, which is dramatically different than all computing systems in the past, which really learned nothing. And as it interacts with humans, it gets even smarter. And it never forgets. <\/p>\n
[Announcer: This is Jeopardy!] <\/p>\n
That helped Watson land a spot on one of the most challenging editions of the game show Jeopardy! in 2011. <\/p>\n
[Announcer: An IBM computer system able to understand and analyze natural language Watson] <\/p>\n
It took five years to teach Watson human language so it would be ready to compete against two of the shows best champions. <\/p>\n
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Five years after beating humans on \"Jeopardy!\" an IBM technology known as Watson is becoming a tool for doctors treating cancer, the head of IBM ... <\/p>\n
Because Watsons A.I. is only as intelligent as the data it ingests, Kellys team trained it on all of Wikipedia and thousands of newspapers and books. It worked by using machine-learning algorithms to find patterns in that massive amount of data and formed its own observations. When asked a question, Watson considered all the information and came up with an educated guess. <\/p>\n
[Alex Trebek: Watson, what are you gonna wager?] <\/p>\n
IBM gambled its reputation on Watson that night. It wasnt a sure bet. <\/p>\n
[Watson: I will take a guess: What is Baghdad?] <\/p>\n
[Alex Trebek: Even though you were only 32 percent sure of your response, you are correct.] <\/p>\n
The wager paid off. For the first time, a computer system proved it could actually master human language and win a game show, but that wasnt IBMs endgame. <\/p>\n
Charlie Rose: Man, thats a big day, isnt it? <\/p>\n
John Kelly: Thats a big day <\/p>\n
Charlie Rose: The day that you realize that, If we can do this <\/p>\n
John Kelly: Thats right. <\/p>\n
Charlie Rose: --the future is ours. <\/p>\n
John Kelly: Thats right. <\/p>\n
Charlie Rose: This is almost like youre watching something grow up. I mean, youve seen <\/p>\n
John Kelly: It is. <\/p>\n
Charlie Rose: --the birth, youve seen it pass the test. Youre watching adolescence. <\/p>\n
John Kelly: Thats a great analogy. Actually, on that Jeopardy! game five years ago, I-- when we put that computer system on television, we let go of it. And I often feel as though I was putting my child on a school bus and I would no longer have control over it. <\/p>\n
Charlie Rose: Cause it was reacting to something that it did not know what would it be? <\/p>\n
John Kelly: It had no idea what questions it was going to get. It was totally self-contained. I couldnt touch it any longer. And its learned ever since. So fast-forward from that game show, five years later, were in cancer now. <\/p>\n
Charlie Rose: Youre in cancer? Youve gone <\/p>\n
John Kelly: Were-- yeah. To cancer <\/p>\n
Charlie Rose: --from game show to cancer in five years? <\/p>\n
John Kelly: --in five years. In five years. <\/p>\n
Five years ago, Watson had just learned how to read and answer questions. <\/p>\n
Now, its gone through medical school. IBM has enlisted 20 top-cancer institutes to tutor Watson in genomics and oncology. One of the places Watson is currently doing its residency is at the university of North Carolina at Chapel Hill. Dr. Ned Sharpless runs the cancer center here. <\/p>\n
Charlie Rose: What did you know about artificial intelligence and Watson before IBM suggested it might make a contribution in medical care? <\/p>\n
Ned Sharpless: I-- not much, actually. I had watched it play Jeopardy! <\/p>\n
Charlie Rose: Yes. <\/p>\n
Ned Sharpless: So I knew about that. And I was very skeptical. I was, like, oh, this what we need, the Jeopardy-playing computer. Thats gonna solve everything. <\/p>\n
Charlie Rose: So what fed your skepticism? <\/p>\n
Ned Sharpless: Cancers tough business. Theres a lot of false prophets and false promises. So Im skeptical of, sort of, almost any new idea in cancer. I just didnt really understand what it would do. <\/p>\n
What Watsons A.I. technology could do is essentially what Dr. Sharpless and his team of experts do every week at this molecular tumor board meeting. <\/p>\n
They come up with possible treatment options for cancer patients who already failed standard therapies. They try to do that by sorting through all of the latest medical journals and trial data, but it is nearly impossible to keep up. <\/p>\n
Charlie Rose: To be on top of everything thats out there, all the trials that have taken place around the world, it seems like an incredible task <\/p>\n
Ned Sharpless: Well, yeah, its r <\/p>\n
Charlie Rose: --for any one university, only one facility to do. <\/p>\n
Ned Sharpless: Yeah, its essentially undoable. And understand we have, sort of, 8,000 new research papers published every day. You know, no one has time to read 8,000 papers a day. So we found that we were deciding on therapy based on information that was always, in some cases, 12, 24 months out-of-date. <\/p>\n
However, its a task thats elementary for Watson. <\/p>\n
Ned Sharpless: They taught Watson to read medical literature essentially in about a week. <\/p>\n
Charlie Rose: Yeah. <\/p>\n
Ned Sharpless: It was not very hard and then Watson read 25 million papers in about another week. And then, it also scanned the web for clinical trials open at other centers. And all of the sudden, we had this complete list that was, sort of, everything one needed to know. <\/p>\n
Charlie Rose: Did this blow your mind? <\/p>\n
Ned Sharpless: Oh, totally blew my mind. <\/p>\n
Watson was proving itself to be a quick study. But, Dr. Sharpless needed further validation. He wanted to see if Watson could find the same genetic mutations that his team identified when they make treatment recommendations for cancer patients. <\/p>\n
Ned Sharpless: We did an analysis of 1,000 patients, where the humans meeting in the Molecular Tumor Board-- doing the best that they could do, had made recommendations. So not at all a hypothetical exercise. These are real-world patients where we really conveyed information that could guide care. In 99 percent of those cases, Watson found the same the humans recommended. That was encouraging. <\/p>\n
Charlie Rose: Did it encourage your confidence in Watson? <\/p>\n
Ned Sharpless: Yeah, it was-- it was nice to see that-- well, it was also-- it encouraged my confidence in the humans, you know. Yeah. You know-- <\/p>\n
Charlie Rose: Yeah. <\/p>\n
Ned Sharpless: But, the probably more exciting part about it is in 30 percent of patients Watson found something new. And so thats 300-plus people where Watson identified a treatment that a well-meaning, hard-working group of physicians hadnt found. <\/p>\n
Charlie Rose: Because? <\/p>\n
Ned Sharpless: The trial had opened two weeks earlier, a paper had come out in some journal no one had seen -- you know, a new therapy had become approved <\/p>\n
Charlie Rose: 30 percent though? <\/p>\n
Ned Sharpless: We were very-- that part was disconcerting. Because I thought it was gonna be 5 perc <\/p>\n
Charlie Rose: Disconcerting that the Watson found <\/p>\n
Ned Sharpless: Yeah. <\/p>\n
Charlie Rose: --30 percent? <\/p>\n
Ned Sharpless: Yeah. These were real, you know, things that, by our own definition, we wouldve considered actionable had we known about it at the time of the diagnosis. <\/p>\n
Some cases -- like the case of Pam Sharpe -- got a second look to see if something had been missed. <\/p>\n
Charlie Rose: When did they tell you about the Watson trial? <\/p>\n
Pam Sharpe: He called me in January. He said that they had sent off my sequencing to be studied by-- at IBM by Watson. I said, like the <\/p>\n
Charlie Rose: Your genomic sequencing? <\/p>\n
Pam Sharpe: Right. I said, Like the computer on Jeopardy!? And he said, Yeah-- <\/p>\n
Charlie Rose: Yes. And whatd you think of that? <\/p>\n
Pam Sharpe: Oh I thought, Wow, thats pretty cool. <\/p>\n
Pam has metastatic bladder cancer and for eight years has tried and failed several therapies. At 66 years old, she was running out of options. <\/p>\n
Charlie Rose: And at this time for you, Watson was the best thing out there cause youd tried everything else? <\/p>\n
Pam Sharpe: Ive been on standard chemo. Ive been on a clinical trial. And the prescription chemo Im on isnt working either. <\/p>\n
One of the ways doctors can tell whether a drug is working is to analyze scans of cancer tumors. Watson had to learn to do that too so IBMs John Kelly and his team taught the system how to see. <\/p>\n
It can help diagnose diseases and catch things the doctors might miss. <\/p>\n
John Kelly: And what Watson has done here, it has looked over tens of thousands of images, and it knows what normal looks like. And it knows what normal isnt. And it has identified where in this image are there anomalies that could be significant problems. <\/p>\n
[Billy Kim: You know, you had CT scan yesterday. There does appear to be progression of the cancer.] <\/p>\n
Pam Sharpes doctor, Billy Kim, arms himself with Watsons input to figure out her next steps. <\/p>\n
[Billy Kim: I can show you the interface for Watson.] <\/p>\n
Watson flagged a genetic mutation in Pams tumor that her doctors initially overlooked. It enabled them to put a new treatment option on the table. <\/p>\n
Charlie Rose: What would you say Watson has done for you? <\/p>\n
Pam Sharpe: It may have extended my life. And I dont know how much time Ive got. So by using this Watson, its maybe saved me some time that I wont-- wouldnt have had otherwise. <\/p>\n
But, Pam sadly ran out of time. She died a few months after we met her from an infection never getting the opportunity to see what a Watson adjusted treatment could have done for her. Dr. Sharpless has now used Watson on more than 2,000 patients and is convinced doctors couldnt do the job alone. He has started using Watson as part of UNCs standard of care so it can help patients earlier than it reached Pam. <\/p>\n
Charlie Rose: So what do you call Watson? A physicians assistant, a physicians tool, a physicians diagnostic mastermind? <\/p>\n
<\/p>\n
See the article here: <\/p>\n
Artificial intelligence positioned to be a game-changer - CBS ...<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" The following script is from Artificial Intelligence, which aired on Oct. 9, 2016. Charlie Rose is the correspondent Continue reading