Watson could be described as a natural language search engine. This is no small thing. It's linguistic abilities were showcased on jeopardy, though it's wins might have had more to do with speed of processing and "buzzing in" than it did with being really smart. Watson is quite possibly the most sophisticated specific use natural language program to ever exist (as opposed to general use nlp, which is star trek level problem).
That said, the approach and subsequent utility might not live up to the hype that IBM is pumping out. It's one thing to search very quickly. Being able to discover patterns that lead to new levels of understanding and predictable relationships is another thing entirely. IBM is more search vs predict in part because they only have so much data to work with. All of the medical books in the world are a drop in the bucket in terms of algorithmic understanding. Watson has mastered working with all available information. Collecting and processing massive data sets is another challenge that IBM hasn't been willing to tackle yet.
IBM is billing Watson as the all singing, all dancing solution to the world's data problems. They're tackling a lot of problems in diverse areas. I hope it works out, the world needs as much help as it can get. But IBM has shifted their core mission to be consulting and I wonder if Watson's purpose will be to support that more than becoming a Super Siri type software project that could do the most good.
> its wins might have had more to do with speed of processing and "buzzing in" than it did with being really smart.
It may only be better than humans at buzzing in, but being as good as humans at natural language search, but faster and more consistently (doesn't make mistakes when tired; works just as well in Kampala as New York; can be audited when it makes mistakes) is already better than humans.
> That said, the approach and subsequent utility might not live up to the hype that IBM is pumping out. It's one thing to search very quickly. Being able to discover patterns that lead to new levels of understanding and predictable relationships is another thing entirely.
I don't get this, Watson might not be able to provide new levels of understanding but it still does a much better job than current search engines, so why do you think it cannot live up to the hype? Why do you think that it is not a significant improvement? What makes you think the approach is wrong? I need some clarifications :)
Regarding Watson's speed on Jeopardy, that was certainly a big advantage for it. However, consider that no matter how fast it is, a machine that "only" gets 50% of the questions right after it buzzes in (which would be an amazing accomplishment already) would lose the game horribly. That it won so solidly shows that it goes well beyond mere speed.
Watson is is now only a search engine you need to train and define your own domain models and logics in side the App. The bloom depends on wether there can be enough Apps on the platform. Remember: those Apps are enterprise level and will always be developed by companies. Why don't these companies just deploy their app in other clouds and connect with a 'siri' like voice interface? I can't see any values inside this platform. Vertical search and IP is not hard for developers today. Small companies can do that without IBM's help.
“allows business users to send natural language questions and raw data sets into the cloud, for Watson to crunch, uncover, and visualize insights; without the need for advanced analytics training. After analyzing the data, Watson will deliver results to its users through graphic representations that are easy to understand, interact with, and share with colleagues; all in a matter of minutes.”
This sounds a lot like my present job description.
Remember, no one cares about data, they want a story and the evidence to back that up. Watson may just make it easier for you to focus on the story telling and evidence rather than the crunching.
I'm currently working on an my own open source version of Watson/Siri/Google Now. (It can answer "What is the capital of Brazil" Yay!).
As part of that I've been leaning as much as I can about how Watson actually works.
The most useful information can be found by Googling "Deep QA" which is what IBM has dubbed their question answering pipeline.
A slide deck like [2] is a good place to start if you are interested in this.
[1] Yeah, I know that is kind of a crazy thing to work on. It's actually even more stupid than you may think, because I want it make it self-hostable, with the ability to keep your own data separately to the rest of the application (ie, enforcing privacy).
Not crazy at all. I have been dreaming on working on something similar even before watson was announced (though i was just a Freshmen back then). And was hellishly jealous of that team. So I can totally understand your motivations for this.
Do hit me up if you'd welcome help with this. Email is in HN profile
I really don't appreciate the media's blood thirst - the slayer of this and the killer of that. Why can't we just have something that contributes in a non-zero-sum game?
You never had journalistic training. Journalists frame stories to satisfy criteria of "newsworthiness," a combined measure of the story's importance, urgency, and entertainment value. Just like a good novel has a dramatic conflict, journalists are taught to report on stories with conflict (which are often more interesting to read than dull, peaceful hum-drum). And if the story doesn't have conflict built-in, they make conflict by framing the story to include a conflict narrative. Journalists refer to the way they frame a story as their "angle." Anything can be news with the right angle.
Real life example: in the 90s, journalists reported on the "Great Hacker War," a "virtual gang war" between two competing hacker groups, LOD & MOD. In reality, the event was a scuffle between some hackers in a chat room, which resulted in some minor hacking, name calling, and prank phone calls. But that didn't make for a great headline.
So far Watson for developers/business is 100% PR and 0% real. In November they announced the Watson API. Where is the API? Where is the documentation? Where are the examples? Google it and you'll get a torrent of PDF press release and incentives to call their sales team.
I'm afraid Watson is just a PR stunt. Was it oversold by IBM engineers to their executives? Or by the executives to the PR team? Or by the PR team to the press? I don't know. But they lost control of it.
My field of research is in machine learning, and upon chatting with medical folks about recent machine learning breakthroughs that outperform panels of experts at making diagnoses, they are all extremely resistant and think that using AI in medicine is somehow immoral.
I'd personally want to be diagnosed by a panel of experts with access to said AI.
In 2012, Memorial Sloan-Kettering Cancer Center in New York began work on an adviser to recommend cancer treatments. Dr. Mark Kris, a Sloan-Kettering oncologist, said an early version of the Watson tool could be used on patients later this year if it passes tests.
At his office, he pulled out an iPad and showed a screen from Watson that listed three potential treatments. Watson was less than 32% confident that any of them were correct. "Just like cancer, it is much more complex than we thought," Dr. Kris said.
Is there even a product to sell to medical? I thought Watson was just a proof-of-concept system. An actual product based on Watson would need to have some defined scope (i.e. only used for cancer treatments), would need some sort of FDA clearance which would probably require clinical trials. Is it there yet? Does IBM even want to take on the liability and expense of bringing it to medical? And is the market even big enough to interest IBM? Today, the "decision-support system" market is tiny.
Slow to adapt comes from many factors. We've been studying the history of medical innovation. The biggest hurdle is the training time required. We're talking a decade to get credentials. Then another decade to get experience. Those 20 years are hard work (schooling, residency, long hours, loans, meager pay). By the time they're ready to contribute, risks are not a good thing esp adding to the chance of doing harm to patients. So the status quo persists until the next generation comes along.
We're meeting mental health professionals who were trained in the 60s, 70s, and 80s who proudly claim they know little about the brain. I don't blame them entirely - when they were trained we only knew about the human brain from stokes and open head trauma. To get them up to speed requires a whole new training. That's very hard when you spend all week seeing patients - that's your livelihood.
For specialized tasks expert systems have been better than doctors since the 1970s (Mycin, infection/antibiotic assignment). So I would guess there is some resistance.
Watson in its original incarnation could be already quite useful. It could provide workers with valuable input on what their manager has in mind when he babbles incomprehensibly throwing his favorite buzzwords at random.
At least 20% of full-stack programmers job is to figure out how people want the computer to behave and all we have to work with is chaos of words that flow from their mouths and fingers.
So Siri is for consumer devices and Watson is going to be for businesses. I dont think they are going to be killing each other since they are targeting different markets.
It would be more convincing if Watson accomplished some real knowledge archievment such as finding a cure for a specific disease, or publish some papers enhance our understanding of some research topics ...
Unix starts small, it works. Google starts small, it helps us tremendously. Haven't seen something starts as a big business plan can success greatly? even Microsoft started small ...
[+] [-] hooande|12 years ago|reply
That said, the approach and subsequent utility might not live up to the hype that IBM is pumping out. It's one thing to search very quickly. Being able to discover patterns that lead to new levels of understanding and predictable relationships is another thing entirely. IBM is more search vs predict in part because they only have so much data to work with. All of the medical books in the world are a drop in the bucket in terms of algorithmic understanding. Watson has mastered working with all available information. Collecting and processing massive data sets is another challenge that IBM hasn't been willing to tackle yet.
IBM is billing Watson as the all singing, all dancing solution to the world's data problems. They're tackling a lot of problems in diverse areas. I hope it works out, the world needs as much help as it can get. But IBM has shifted their core mission to be consulting and I wonder if Watson's purpose will be to support that more than becoming a Super Siri type software project that could do the most good.
[+] [-] taejo|12 years ago|reply
It may only be better than humans at buzzing in, but being as good as humans at natural language search, but faster and more consistently (doesn't make mistakes when tired; works just as well in Kampala as New York; can be audited when it makes mistakes) is already better than humans.
[+] [-] bnegreve|12 years ago|reply
I don't get this, Watson might not be able to provide new levels of understanding but it still does a much better job than current search engines, so why do you think it cannot live up to the hype? Why do you think that it is not a significant improvement? What makes you think the approach is wrong? I need some clarifications :)
[+] [-] mikeash|12 years ago|reply
[+] [-] jijiwaiwai|12 years ago|reply
[+] [-] eggoa|12 years ago|reply
This sounds a lot like my present job description.
[+] [-] tsunamifury|12 years ago|reply
[+] [-] rapht|12 years ago|reply
[+] [-] nl|12 years ago|reply
As part of that I've been leaning as much as I can about how Watson actually works.
The most useful information can be found by Googling "Deep QA" which is what IBM has dubbed their question answering pipeline.
A slide deck like [2] is a good place to start if you are interested in this.
[1] Yeah, I know that is kind of a crazy thing to work on. It's actually even more stupid than you may think, because I want it make it self-hostable, with the ability to keep your own data separately to the rest of the application (ie, enforcing privacy).
[2] http://www.cs.hku.hk/news/2011/WatsonHongKong_talk_ppt.pdf
[+] [-] xerophtye|12 years ago|reply
Do hit me up if you'd welcome help with this. Email is in HN profile
[+] [-] fortepianissimo|12 years ago|reply
[+] [-] normloman|12 years ago|reply
Real life example: in the 90s, journalists reported on the "Great Hacker War," a "virtual gang war" between two competing hacker groups, LOD & MOD. In reality, the event was a scuffle between some hackers in a chat room, which resulted in some minor hacking, name calling, and prank phone calls. But that didn't make for a great headline.
[+] [-] sheetjs|12 years ago|reply
[+] [-] ar7hur|12 years ago|reply
I'm afraid Watson is just a PR stunt. Was it oversold by IBM engineers to their executives? Or by the executives to the PR team? Or by the PR team to the press? I don't know. But they lost control of it.
[+] [-] Spooky23|12 years ago|reply
http://watson.rpi.edu/
[+] [-] kitd|12 years ago|reply
[+] [-] pervycreeper|12 years ago|reply
[+] [-] gamegoblin|12 years ago|reply
I'd personally want to be diagnosed by a panel of experts with access to said AI.
[+] [-] adolph|12 years ago|reply
http://online.wsj.com/news/articles/SB1000142405270230488710...
In 2012, Memorial Sloan-Kettering Cancer Center in New York began work on an adviser to recommend cancer treatments. Dr. Mark Kris, a Sloan-Kettering oncologist, said an early version of the Watson tool could be used on patients later this year if it passes tests.
At his office, he pulled out an iPad and showed a screen from Watson that listed three potential treatments. Watson was less than 32% confident that any of them were correct. "Just like cancer, it is much more complex than we thought," Dr. Kris said.
[+] [-] macspoofing|12 years ago|reply
[+] [-] robg|12 years ago|reply
We're meeting mental health professionals who were trained in the 60s, 70s, and 80s who proudly claim they know little about the brain. I don't blame them entirely - when they were trained we only knew about the human brain from stokes and open head trauma. To get them up to speed requires a whole new training. That's very hard when you spend all week seeing patients - that's your livelihood.
[+] [-] carbocation|12 years ago|reply
I don't think this is true, but if so, please contact me (details in my HN profile).
[+] [-] jmount|12 years ago|reply
[+] [-] bhouston|12 years ago|reply
[+] [-] kylemclaren|12 years ago|reply
http://youtu.be/8lGJ0h_jAp8
[+] [-] scotty79|12 years ago|reply
At least 20% of full-stack programmers job is to figure out how people want the computer to behave and all we have to work with is chaos of words that flow from their mouths and fingers.
[+] [-] wil421|12 years ago|reply
[+] [-] taopao|12 years ago|reply
[+] [-] robg|12 years ago|reply
[+] [-] jonathansizz|12 years ago|reply
[+] [-] balozi|12 years ago|reply
[+] [-] robg|12 years ago|reply
[+] [-] lingben|12 years ago|reply
[+] [-] unknown|12 years ago|reply
[deleted]
[+] [-] hipaulshi|12 years ago|reply
[+] [-] isaacpei|12 years ago|reply
It would be more convincing if Watson accomplished some real knowledge archievment such as finding a cure for a specific disease, or publish some papers enhance our understanding of some research topics ...
Unix starts small, it works. Google starts small, it helps us tremendously. Haven't seen something starts as a big business plan can success greatly? even Microsoft started small ...
[+] [-] nathan_f77|12 years ago|reply