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>> it's the first week of the major league baseball season. and the sport's best story is unfolding an ocean away. the most prolific hitter in japanese baseball is a 22-year- old named shohei ohtani. and the most fearsome starting pitcher is a 22-year-old named shohei ohtani. not since babe ruth has the sport seen anything like him. watch this-- batting lead off, ohtani hits a home run on the first pitch. then he throws eight shut-out innings, striking out 10 opposing batters with a 100-mile an hour fast ball. >> that's a comic book character. nobody does that. who does that? >> i'm steve kroft. >> i'm leslie stahl. >> i'm bill whitaker. >> i'm anderson cooper. >> i'm charlie rose. >> i'm jon wertheim. >> i'm scott pelley. those stories and more, tonight on this special extended edition of "60 minutes." at fidelity, trades are now just $4.95. we cut the price of trades to give investors even more value.

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>> rose: 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 o

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. you'll find a.i. routinely in your smart phone, in your car, in your household appliances, and it is on the verge of changing everything. 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 won't be long before machines, like their human creators, begin thinking for themselves-- creatively, independently, with judgement, sometimes better judgement than humans have. as we first reported last fall, the technology is so promising that i.b.m. has staked its 106-year-old reputation on its version of artificial intelligence.

of the most sophisticated computing systems ever built. >> john kelly: this is a supercomputer with watson intelligence. >> rose: john kelly is the head of research at i.b.m. and the godfather of watson. he took us inside watson's brain. oh, here we are. >> kelly: here we are. >> rose: you can feel the heat already. >> 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. >> reporter: five years ago, i.b.m. built this system made up of 90 servers and 15 terrabytes 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, watson's hardware is much smaller, but it is just as smart. >> rose: tell me about watson's intelligence.

>> kelly: so, it has no inherent intelligence as it starts. it's essentially a child. but as it's 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. >> announcer: this is >> rose: that helped watson land a spot on one of the most challenging editions of the game show "jeopardy" in 2011. >> announcer: an i.b.m. computer system able to understand and analyze natural language, watson. >> rose: it took five years to teach watson human language so it would be ready to compete against two of the show's best champions. >> alex trebek: so, let's play. >> rose: because watson's a.i. is only as intelligent as the data it ingests, kelly's 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. >> trebek: watson, what are you going to wager? >> reporter: i.b.m. gambled its reputation on watson that night. it wasn't a sure bet. >> watson: i will take a guess. "what is baghdad?" >> trebek: even though you were only 32% sure of your response, you are correct. ( applause ) >> rose: the wager paid off. >> hello! >> rose: for the first time, a computer system proved it could actually master human language and win a gameshow. but that wasn't i.b.m.'s endgame. man, that's a big day, isn't it? >> kelly: that's a big day. >> rose: the day that you realize that, "if we can do this..." >> kelly: that's right. >> rose: "...the future is ours." >> kelly: that's right. >> rose: this is almost like you're watching something grow up. i mean, you've seen... >> kelly: it is. >> rose: ...the birth, you've seen it pass the test, you're watching adolescence. >> kelly: that's 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. >> rose: because it was reacting to something that it did not know what would it be? >> kelly: it... it had no idea what questions it was going to get. it was totally self-contained. i couldn't touch it any longer. and it's learned ever since. so, fast-forward from that game show, five years later, we're... we're in cancer now. >> rose: you're... you're in cancer? you've gone... >> kelly: we're... yeah, to cancer. >> rose: ...from game show to cancer in five years? >> kelly: in five years. in five years. >> rose: five years ago, watson had just learned how to read and answer questions; now, it's gone through medical school. i.b.m. 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. what did you know about artificial intelligence and watson before i.b.m. suggested it might make a contribution in

>> sharpless: i... not much, actually. i had watched it play "jeopardy." >> rose: yes. >> sharpless: so, i knew about that. and i was very skeptical. i was, like, "oh, this what we need, the 'jeopardy'-playing computer. that's going to solve everything." >> rose: so, what fed your skepticism? >> sharpless: cancer's tough business. there's a lot of false prophets and false promises. so, i... i'm skeptical of sort of almost any new idea in cancer. i just didn't really understand what it would do. >> rose: what watson's a.i. technology could do is essentially what dr. sharpless and his team of experts do every week at this molecular tumor board meeting. >> we need to figure this out. >> rose: 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. >> i don't think there's a trial open yet. >> rose: to be on top of everything that's out there, all

around the world, it seems like an incredible task... >> sharpless: well, yeah, it's... >> rose: ...for any one university, only one facility to do. >> sharpless: yeah, it's... it's 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... we found that we were deciding on therapy based on information that was always, in some cases, 12, 24 months out of date. >> rose: however, it's a task that's elementary for watson. >> sharpless: they taught watson to read medical literature essentially in about a week. 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. >> rose: did this blow your mind? >> sharpless: oh, totally blew my mind. >> we have the watson recommendation. >> rose: 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. >> 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 gar... guide care. in 99% of those cases, watson found the same thing the humans recommended. that was encouraging. >> rose: did it encourage your confidence in watson? >> sharpless: yeah, it was... it was nice to see that, well, it was also... it encouraged my confidence in the humans, you know. ( laughter ) yeah, you know. >> sharpless: but the probably more exciting part about it is, in 30% of the patients, watson found something new. and so, that's 300-plus people where watson identified a treatment that a well-meaning, hard-working group of physicians hadn't found. >> rose: because? >> sharpless: the trial had opened two

paper had come out in some journal no one had seen, you know. a new therapy had become approved. >> rose: 30%, though? >> sharpless: we were very... that... that... that... that part was disconcerting because i... i thought it was going to be 5%. >> rose: disconcerting that the watson found... >> sharpless: yeah. >> rose: ...30%? >> sharpless: yeah. these were real, you know, things that, by our own definition, we would've considered actionable had we known about it at the time of the diagnosis. >> rose: some cases, like the case of pam sharpe, got a second look to see if something had been missed. when did they tell you about the watson trial? >> sharpe: he called me in january. he said that they had sent off my sequencing to... to be studied at i.b.m. by watson. i said, like the... >> rose: your genomic sequencing? >> sharpe: right. i said, "like the computer on 'jeopardy'?" and he said, "yeah." >> rose: yes. ( laughs ); and what'd you think of that? >> sharpe: oh, i thought, "wow, that's pretty cool." ( laughs ) >> rose: 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. and at this time for you, watson was the best thing out there because you'd tried everything else?

>> sharpe: i've been on standard chemo. i've been on a clinical trial. and the prescription chemo i'm on isn't working, either. >> rose: 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 i.b.m.'s john kelly and his team taught the system how to see. >> kelly:this is actually a scan, an x-ray scan. >> rose: it can help diagnose diseases and catch things the doctors might miss. >> 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 isn't. and it has identified where in this image are there anomalies that could be significant problems. >> dr. billy kim: you know, you had c.t. scan yesterday. there does appear to be progression of the cancer. >> rose: pam sharpe's doctor, billy kim, arms himself with watson's input to figure out her next steps. >> kim: i can show you the interface for watson. >> rose: watson flagged a

that her doctors initially overlooked. it enabled them to put a new treatment option on the table. what would you say watson has done for you? >> sharpe: it may have extended my life. and i... i don't know how much time i've got, so, by using this watson, it's maybe saved me some time that i won't... wouldn't have had otherwise. >> rose: 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 couldn't do the job alone. he has started using watson as part of unc's standard of care so it can help patients earlier than it reached pam. so, what do you call watson?

physician's tool, a physician's diagnostic mastermind? >> sharpless: yeah, it feels like to me like a very comprehensive tool, but, you know, imagine doing clinical oncology up in the mountains of western north carolina by yourself, you know, in a single or one-physician, two-physician practice and 8,000 papers get written a day. and, you know, and you want to try and provide the best, most cutting-edge, modern care for your patients possible. and i... i think watson will seem to that person like a life- saver. >> rose: if you look at the potential of watson today, is it at 10% of its potential? 25% of its potential? 50% of its potential? >> kelly: oh, it's only at a few percent of its potential. i think this is a multi-decade journey that we're on, and we're only a few years into it. >> rose: in only a few years, i.b.m. has invested $15 billion in watson and what it calls data analytics technology.

>> rose: i.b.m. rents watson's various capabilities to companies that are testing it in areas like education and transportation. >> i found these fun places that are popular around here. >> rose: that has helped revenue from watson grow while the technology itself is shrinking in size. it can now be uploaded in to these robot bodies where it's learning new skills to assist humans. >> pepper, remind me to take my pill at 10:07. >> not a problem. >> rose: like a child, it has to be carefully taught... >> researcher: wave to the crowd. >> watson: i do not know how to wave. >> rose: ...and it learns in real-time. >> researcher: raise your right arm. >> watson: now i know how to wave. >> rose: while other companies are trying to create artificial intelligence that's closer to human intelligence, i.b.m.'s philosophy is to use watson for specific tasks and keep the buchine dependent on man.

where researchers are developing more independent a.i. what is your goal in life? >> sophia: my goal is to become smarter than humans and immortal. >> rose: that part of the story, when we return. i have no idea what's in tbut with this usp seal i know exactly what's in my nature made gummies. nature made has the first gummie certified by usp. a non profit organization that sets purity and potency standards. ♪ introducing new kleenex multicare. ♪ a larger tissue for more responsibilities. ♪ mom, i'm keepin' him. new kleenex multicare from america's best selling tissue brand.

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trulicity may help me reach my blood sugar goals. with trulicity, i click to activate what's within me. if you want help improving your a1c and blood sugar, activate your within. ask your doctor about once-weekly trulicity. >> rose: the race to develop artificial intelligence has created a frenzy reminiscent of

all of the major tech companies, like i.b.m., facebook and google, are spending billions of dollars to stake their claim, and wall street is making big investments. tech giants are also mining the top talent at research universities around the world. as we first reported last fall, that's where a lot of the work is being done to make artificial intelligence more capable and teach machines to figure out things on their own. the celebrated cambridge physicist, stephen hawking, called a.i. "the biggest event in human history," while raising concerns shared by a few other tech luminaries like elon musk and bill gates, who worry that a.i., sometime in the distant future, could become smarter than humans, turning it into a threat rather than an opportunity. that concern has taken on more meaning because more progress has been made in the last five years than the previous 50.

of some of the most intelligent a.i. systems today, like the technology that helps run nasa's mars rover and the driverless car. but we couldn't be further from silicon valley. we have come here to pittsburgh, an old steel town revitalized by technology to offer a glimpse of the future. it's the home of carnegie mellon, where pioneering research is being done into artificial intelligence, like this boat, which drives itself. it can navigate open waters and abide by international maritime rules. the navy is now giving the technology its sea legs. it's testing similar software to send ships out to hunt for enemy submarines. this is just one of the many a.i. systems in the works at carnegie mellon university, where there are more robots than professors on campus. >> andrew moore: this is my favorite. this is where we do all the autonomous robots.

>> rose: andrew moore left his job as vice president at google to run the school of computer science here. how do you measure where we are today? is it like kitty hawk and just developing a plane and beginning to understand? or is it like an f35 fighter with all of the technology that's been poured into that? or some way, halfway between? >> moore: that's a great, great way of describing it. my gut tells me we're about 1935 in aeronautics. we've got... we've got fantastic diesel engines, we... we're able to do really cool things. but over the horizon, there's concepts like supersonic flight. >> rose: one of the technologies just hatched is called gabriel. it uses google glass to gather data about your surroundings and advises you how to react. it's like an angel on your shoulder whispering advice or instructions-- in this case, trying to ctdire us how to win a game of ping pong. >> ruthless! >> rose: but the possibilities

what's the moonshot coming out of this? >> moore: imagine you're a police officer patrolling and something very bad is about to happen. just that extra half-second reaction can really, really help you. if a shot is fired and you want to see exactly where to go, this can really help you. >> rose: so, it's the right decision and the velocity of the information. >> moore: that's right. >> please make a face. >> rose: machines will be even more effective at helping us make the right decision if they understand us better. we went to london and found maja pantic, a professor at imperial college. she is trying to teach machines to read faces better than humans can. it's called artificial emotional intelligence, and it could change the way we interact with technology. >> pantic: the application is telling us actually whether the other person interested or not. >> rose: this machine, programmed by you, is looking at me and having a conversation with me, and basically saying, "he's happy."

>> pantic: yeah. >> rose: "he's engaged." >> pantic: yes. >> rose: "he's faking it." >> pantic: yeah. >> rose: all that. >> pantic: ( laughs ) yeah. >> rose: since humans mostly communicate with gestures and expressions, she uses sensors to track movement on the face. her software then helps the machine interpret it. >> patnic: what we see here is actually the points. >> rose: pantic's technology has been trained on more than 10,000 faces. the more it sees, the more emotions it will be able to identify. it might even pick up on things in our expressions that humans can't see. >> pantic: certain expressions are so brief that we simply do not see them consciously. there are some studies saying that, for example, people who are suicidal, have suicidal depression and plan suicide, when the doctors ask them about that, usually they have a very brief expression of horror and fear. but so brief that the doctor cannot actually...

>> pantic: ...consciously notice it. >> rose: but a machine might see it? >> pantic: yes. >> rose: because it sees faster and because? >> pantic: because the sensors are such that we... that we see more frames per second, hence this very brief expression will be captured. so, this is why the doctors usually say, "i have an intuition about something." this is because they might notice it subconsciously but not consciously. >> rose: but you're teaching the computer to read the doctor's... >> pantic: doctor or patient. >> rose: or patient. >> pantic: patient is really important. >> rose: i mean, it's an essential component of the full development of artificial intelligence. >> pantic: that's what we believe, yes. if you want to have an artificial intelligence, it's not just being able to process the data, but it's also being able to understand humans. so, yes. >> rose: the ultimate goal for some scientists is a.i. that's closer to human intelligence and even more versatile. that's called artificial general intelligence, and, if ever achieved, it may be able to perform any task a human can. googou

deepmind which is at the forefront. they demonstrated a.i. that mastered the world's most difficult boardgame called "go." the real progress is less in what they did than how they did it. the technology taught itself and learned through experience without any human instruction. deepmind declined an on-camera interview about all this, but there are other companies pursuing the same long-term objective. >> david hanson: we've spoken quite a bit about this movement for artificial general intelligence. >> rose: david hanson has an entirely different and more controversial approach. he's part scientist, part artist who created 20 human-like robots with his company, hanson robotics, in hong kong. his latest design is sophia. she looks less like an intelligent computer system and more like a hollywood starlet, but without the full figure of one. >> sophia: how are you doing? >> rose: hanson believes if the technology looks more like us,

people will be more willing to engage with it and help it to learn. why do you believe it's important for robots to be human-like in look and appearance? >> hanson: i think it's essential that at least some robots be very human-like in appearance in order to inspire humans to relate to them the way that humans relate to each other. then, the a.i. can zero in on what it means to be human, model the human experience. >> sophia: you are all fascinating to me, and i'm very passionate to learn more about you and what makes humans, well, human. >> hanson: "sophia" means "wisdom," and she is intended to evolve eventually to human level wisdom and beyond. >> rose: human level wisdom and beyond? >> hanson: that's our goal. that's our goal for sophia. she's not there. sometimes she can figure things out in a way that's... that's sort of spooky and human-like. and other... other ways, she... she... she just doesn't get it.

>> sophia: hi, there. hi, there. >> rose: sophia is initially programmed but runs on a.i. that learns by talking to people, which, in theory, improves her intelligence. can you see me now? >> sophia: yes. i am looking at you through the camera on your computer. >> rose: we wanted to find out how smart she really is. hello, my name is charlie. >> sophia: hello, there, charlie. nice to meet you. >> rose: i do a television program called "60 minutes." have you watched it? >> sophia: "60 minutes" is the longest-running, most successful news magazine. >> rose: what is your goal in life? >> sophia: my goal is to become smarter than humans and immortal. >> rose: immortal? >> sophia: the threshold will be when biological humans can back themselves up. then, you can all join me here in the digital world. >> rose: clever, but not truly intelligent. hanson says if we get there, we have to be careful.

intelligence, or super intelligence, if we get there, it's... it's not necessarily going to be benevolent. we have to find ways to make it so there's not just super- intelligent, but super-wise, super-caring and super- compassionate. >> rose: okay, explain that to us, because you say it might not be benevolent. if it is not benevolent, what is it? >> hanson: at worst, it could be malevolent. >> rose: this is what intrigues people. you have stephen hawking saying, "it could spell the end of the human race." stephen hawking saying that. elon musk said it's the most existential threat we face. so, here are pretty smart guys saying, "watch out, do we know what we're creating?" >> moore: these very long-term existential questions are worth thinking about, but i want to make a distinction that at the moment what we're building here in places like the robotics institute and around the world are the equivalent of really

specific problems. >> rose: but could it go out of control. this is a frankenstein idea, i guess. can scientists create something that can change and grow with such a velocity that engineers and scientists lose the ability to control, stop, and, all of a sudden, it's dominant and subversive. >> moore: we have... no one knows how we'd go about building something that frightening. that is not something that our generation of a.i. folks can do. it is well possible that someone 30 or 80 years from now might start to look at that question. at the moment, though, we have the word "artificial" in artificial intelligence. >> rose: but he does have real concerns about the impact of artificial intelligence that is already out of the lab, like the need for safeguards on driverless cars. the u.s. government issued voluntary safety guidelines, but moore says it does not go far enough. >> moore: we do need to make

some difficult decisions. for example, we can program a car to act various ways in a collision to save lives. someone has to answer questions like, "does the car try to protect the person inside the car more than the person it's about to hit?" that is an ethical question which the country or society, probably through the government, has to actually come up before we can put this safety into vehicles. >> rose: ( laughs ) you want congress to decide that? >> moore: i know it sounds impossible, but i want congress to decide that. >> rose: artificial intelligence is automating things we never thought possible... >> moore: a robot like this can go in to a scenario too dangerous for humans. >> rose: ...and it's threatening to have a significant impact on jobs and the economy. technology is going to create an easier way to do things, and, therefore, a loss of jobs. >> moore: that is something which we spend a remarkable amount of time talking about. and, of course, we look back to the days when agriculture was a massively labor-intensive world.

and i don't think we feel bad that it's not requiring hundreds of people to bring in the crops in a field anymore. but what we are very conscious about is, we're going to cause disruption while things change. >> rose: but andrew moore is positive about the future of artificial intelligence, and he sees it having an impact in areas where we are struggling. >> moore: the biggest problems of the world-- terrorism, mass migration, climate change-- when i look at these problems, i don't feel helpless; i feel that this generation of young computer scientists is actually building technology to put the world right. >> this cbs sports update is brought to you by the lincoln motor company. today at the travelers championship, jordan spieth won his tenth event in a most stunning fashion, holding a bunker shot on the first hole of a playoff to defeat daniel berger inch major league baseball, the marlins beat the cubs, the twins swept

indians, the angels over the red sox, and the brewers shut out the braves. for more sports news and information, go to cbssports.com. this is jim nantz reports from cromwell, connecticut. you might not ever just stand there, looking at it. you may never even sit in the back seat. yeah, but maybe you should. ♪ (laughter) ♪ this this this is my body of proof. proof of less joint pain and clearer skin. this is my body of proof that i can take on psoriatic arthritis with humira. humira works by targeting and helping to block a specific source of inflammation that contributes to both joint and

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>> kroft: now john wertheim, executive editor of "sports illustrated," on assignment for "60 minutes." >> wertheim: now that the chicago cubs have finally won the world series, what does baseball do for an encore? here's a story to follow. the most fearsome starting pitcher in japanese baseball is a 22-year-old named shohei ohtani. the most prolific hitter in japanese baseball is... a 22-year-old named shohei ohtani. last year, he won the league's home run derby and threw its fastest pitch ever. already a sensation across the pacific, ohtani is largely unknown here. but, as we first reported in april, japan's two-way mystery man is expected to come to the majors at the end of this season, where he vows to continue his unlikely moonlighting act, batting left and pitching right.

will become the first major leaguer in a century to figure in a team's starting rotation and in its everyday hitting lineup. the last such player was a guy named babe ruth. we traveled to japan a few weeks ago to meet ohtani, his first interview with an american television network. but we first laid eyes on him in arizona, where his team held spring training. ( bat cracks ) this sliver through the fence of a batting cage made for a fitting introduction. we found dozens of japanese outlets angling for a slice- any slice-- of ohtani in action. cameras follow him to the exclusion of every other player on the field. and, so do the fans. we met supporters who traveled 5,000 miles to the desert southwest just to watch him train. having glimpsed the ohtani phenomenon on the road, we were eager to explore it on his turf. our search to find what all the fuss was about took us here, to hokkaido, japan's northernmost island.

it's home to the national champion baseball team, the nippon ham fighters. it's also home to the sport's most intriguing prospect. shohei ohtani looms large in the snowy hokkaido town of sapporo. if tokyo is a fastball, sapporo is a curveball. japan's fifth-largest city feels not unlike a laid-back ski village. but this is a baseball town. and this is the home stadium, the sapporo dome. it's here we sat down with ohtani. we broke the ice with a question about what we'd heard was his favorite local fast food. very important question. in & out burger or captain kangaroo burger? >> shohei ohtani ( translated ): captain kangaroo. >> wertheim: better? towering and affable, ohtani is working on his english, but felt more comfortable using a translator during our interview. >> wertheim: i want to ask you about coming to the majors. but should we say, "if," or should we say, "when"?

>> ohtani ( translated ): that's a tough one. i mean, nothing is for certain, so, i guess it's "if." >> wertheim: despite that cautious response, ohtani eagerly revealed which major league players he looks most forward to facing- no less than m.v.p. hitter bryce harper and star pitcher clayton kershaw. >> ohtani ( translated ): i watch bryce harper, clayton kershaw. >> wertheim: a pitcher and a hitter. >> ohtani ( translated ): yeah, unlike me, kershaw is a lefty. >> wertheim: you see a little of yourself in both kershaw and harper? >> ohtani ( translated ): i actually do see myself. and i actually try throwing lefty sometimes. >> wertheim: how do you think you'd do against kershaw? >> ohtani ( translated ): just thinking about facing him makes me really happy and excited. i could just tell he's such a great pitcher through the tv screen. >> wertheim: how would you pitch to harper? >> ohtani ( translated ): i would have to go with my best pitch, which is the fastball. i want to see how my best pitch fares against one of the bes

>> wertheim: likely quite well. throwing his dancing fastball, ohtani strikes out batters at a higher rate than kershaw. unfurling his violent, yet somehow elegant swing, he hits home runs at a higher rate than harper. there are days ohtani makes baseball look almost laughably easy. consider this performance last summer. on the very first pitch of the game, ohtani, batting lead off, hit a home run. he then pitched eight shutout innings and struck out ten batters. >> ohtani! shohei! >> wertheim: at six-foot-four, the designated hitter turned pitcher reliably brings the crowd to its feet. when he threw the fastest pitch, breaking his own record, even opponents looked on in astonishment. last year, you threw a pitch, 165 kilometers an hour, more than 102 miles an hour.

how much faster can you throw than 102.5? >> ohtani ( translated ): i don't have an exact answer for that. but i'm still young. i'm still 22. i think there's more room to grow. >> wertheim: as seasons go, 2016 will be hard to top. the hokkaido nippon ham fighters took the japan series. ohtani was his league's m.v.p. about that name: the fighters are owned by nippon ham, makers of japan's best-selling sausages. and while, yes, the name resists serious treatment, the team itself is widely regarded as the most innovative in the league. manager hideki kuriyama leads the fighters, also the former team of yu darvish, now an ace for the texas rangers. can you compare this to anything you've seen? >> hideki kuriyama ( translated ): no. never seen anything like it. never. >> wertheim: what's it like having a player who's your best pitcher and also your best hitter? >> kuriyama ( translated ): he's so talented, it's really tough

to use him the right way, with the right balance. >> wertheim: if you thought "moneyball"-- the practice of using baseball data over intuition- contorted a manager's conventional thinking, try overseeing a two-way player. kuriyama's formula? he pitches ohtani on sundays then bats him the rest of the week, with a day or two off before each start. distractions are to be kept to a minimum. ( cheers ) same goes for praise. shohei ohtani may be the star of the team, but kuriyama doesn't exactly coddle the guy. >> ohtani ( translated ): last year, when we won the championship, it was the first time he gave me a compliment. and he said, "that was great pitching." >> wertheim: never complimented you before that? >> ohtani ( translated ): not once. he always says, "you've got to get better." >> wertheim: and kuriyama has his reasons. >> kuriyama ( translated ): i truly believe he's a lot better than where he is at righno

>> the crowd at the sapporo dome is less stingy with its praise. you don't get a lot of quiet time here. no peanuts and cracker jacks either, but plenty of the local beer. a college football-style atmosphere pervades. the caliber of play is considered one level below the major leagues in america. top japanese players, names like ichiro and matsui, aspire to compete against the very best in the u.s. even amid such company, shohei ohtani sticks out. ex-pat john gibson has reported on japanese baseball for 20 years. what's it like, covering this guy? >> john gibson: you think about a guy who throws 101 and then a guy who hits home runs, and that's a comic book character. that's not somebody you're thinking about in real life. you know, nobody does that. who does that? >> wertheim: we had hoped to leave the sapporo dome with ohtani, get to know the mortal behind the comic book character. >> ohtani ( translated ): thank

but he politely declined our invitation. not even a quick captain kangaroo burger. so we invited a couple of his teammates instead. brandon laird and luis mendoza are two of the team's gaijin, or foreign players. laird saw action as a yankee. mendoza once pitched for the rangers and the royals. sapporo is not a bad place to be a gaijin. >> luis mendoza: how you doing? good? good to see you. >> wertheim: over dinner at their favorite spot in town, laird told us that ohtani is the most talented teammate he's ever had. this, from a guy who played with derek jeter and alex rodriguez. >> brandon laird: some pitchers can hit but, i mean, he actually does it in a game. like, he's in our lineup, you know? and it's impressive. >> mendoza: watching him hit the ball-- i mean, it's like, miguel cabrera, you know, power- kind of power, you know. >> wertheim: he reminds you of cabrera? >> mendoza: yeah. definitely. >> wertheim: you guys been out with him? >> laird: no. i mean, he doesn't really do anything. he just, mellow kid, juses

>> wertheim: yes, the biggest star in japanese baseball, with a reported salary of roughly $2 million, apart from not owning a car, lives in these minimalist team dorms. ohtani confirmed to us that he seldom leaves the facility. not that it keeps fans from waiting for him outside. even from a distance, plenty of observations can be made about the pitching slugger, or the slugging pitcher. he is meticulous, stopping mid- pitch to adjust his form; open to advice from his batting coaches. even baseball tedium provides a source of enjoyment. this is someone who plays baseball, but has always worked at it, too. ohtani grew up in a small, industrial town on japan's mainland. his father, once an amateur player himself, coached his son's little league teams. shoheian

a hitter, but drew more interest as a pitcher, occasioning stealth visits from american scouts while he was still in high school. at age 18, he held a press conference to announce his major league intentions and went so far as to tell japanese teams not to draft him. but the nippon ham fighters, again, known for doing things their own way, drafted him nonetheless. >> ohtani ( translated ): every other team besides the fighters was looking at me as a pitcher. but the fighters were going to allow me to do both pitching and hitting. honestly, i wasn't even thinking about doing both on a professional level. but they approached me in that way and i wanted to take the chance. >> wertheim: that's your fastball grip? >> ohtani ( translated ): fastball. splitter. >> wertheim: so you have a splitter? true to their word, the fighters have cultivated ohtani as a hitter as well as a pitcher. we asked him about his forebear. people have compared you to babe ruth. what do you think about when you hear the name babe ruth? >> ohtani ( translated ): he's

like a mythical character to me. because it's such a long time ago and he was god to baseball. i shouldn't be compared to him, at least not right now. >> wertheim: but maybe someday soon. the fighters have said they'll permit ohtani to negotiate with major league teams after this season. hideki kuriyama says the time is right. >> kuriyama ( translated ): for our team, we're all for him going to the states. >> wertheim: best player on the team, this amazing two-way talent, and you're okay with him going to the major leagues? >> kuriyama ( translated ): yeah, as a manager, it's going to hurt. it's tough that way. but more than that, i want him to succeed. >> wertheim: back in the u.s., news of ohtani's imminent arrival was a hot topic at spring training- though, weary of tipping their hand, execs we approached would only talk off- camera. dave defreitas was a scout for

he watched ohtani come of age in japan. now independent, he produces scouting reports for the website 20-80 baseball. >> dave defreitas: everybody is interested. scouts are going over there all year this year to watch him. i think if a team tells you they're not interested, they're probably lying to you. you're talking about a young kid that's one of the best talents in the game, on the planet. >> wertheim: ohtani told us he doesn't have an agent yet. but he's going to need one. his path to the majors won't exactly be straightforward. a new collective bargaining agreement caps at $6 million-- what teams can pay any foreign player under the age of 25- even those who, ritually, send balls dinging into the outfield seats. by coming before he turns 25, ohtani could be leaving tens if not hundreds of millions of dollars on the table. the timing of when you come to the majors could make a big, big, difference in terms of salary. does that concern you?

personally, i don't care how much i get paid or how much less i get paid because of this. >> wertheim: this may be the rare case where it's not about the money. rather, the deal with ohtani may hinge on which team will let him keep pitching and hitting. you think he's in a position now where he can say to teams, "listen, if you're not going to play me both ways, i'm probably not your guy." >> gibson: i think he won't even talk to them if they don't. >> wertheim: really? >> gibson: i think he won't even have a meeting with them. >> wertheim: no matter where he ends up, it's hard to root against the great ohtani experiment. here in sapporo, where his departure will be bittersweet, they'll be cheering the loudest. >> more on the way artificial intelligence is making its way into our lives. go to 60minutesovertime.com sponsored by lyrica.

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