131–140 of 452 posts
The author's particular gripe is that the Watson advertisements showing someone sitting down and talking to "Watson." They bother me as well (and did so when I was working at IBM in the Watson group) because they portray a capability that nothing in IBM can provide. Nobody can provide it (again to the author's point) because dialog systems (those which interact with a user through conversational speech) don't exist o…
Everything IBM says about Watson should be taken with a few tons of salt. I don't know how much I'm allowed to say, but they couldn't even get it to work acceptably internally for some of the basic datamining and natural language processing that are among the things so highly touted in some of their TV advertising. This is with a gargantuan dataset compiled from years of relevant interactions to train on in the parti…
How is this different from nearly all other "AI" companies? IBM is not the only one guilty of hype. Neural nets can do specific things well, such as mirror a specific training set well, but still have major gaps in terms of what many call "common sense". It does smell like AI Bubble 2.0 brewing out there.
There are machine learning models which go far beyond counting words, for example see https://arxiv.org/abs/1502.01710
Ahh. So just from the article, his gripe is of the “begs the question” sort — he’s not pleased with the evolution of idiom. Since he was doing “real AI” back then, who are these frauds to claim they are doing AI?
His point may or may not be valid, but his specific argument is quite weak. He notes that even a person, an actual intelligence, wouldn’t know what Dylan was singing about without context. He goes on to presume that Watson doesn’t have context, but who’s to say? Watson could certainly read all the articles about Dylan that he so helpfully cites, and come to “understand” the songs. And maybe Watson has.
If you follow the links to his academy, you divine a bit more of the motivation.
His software development course provides “a unique automated mentor, employing natural-language processing technology derived from our decades of artificial intelligence research”. He is desperate to stay away from calling it actual AI, yet can’t resist implying that it is. This is probably most irksome to him.
My advice: sometimes you have to join ‘em.
Earlier quoted context omitted.
Kinda how Tesla advertises autopilot as a self driving car that's safer than human drivers? > Full Self-Driving Hardware on All Cars > All Tesla vehicles produced in our factory, including Model 3, have the hardware needed for full self-driving capability at a safety level substantially greater than that of a human driver. https://www.tesla.com/autopilot/
It's not just them. A lot of people think that because NNs can do object identification that self driving cars are almost here. It's similar to thinking that word recognition and pattern matching are going to give us conversational AI. Things like that are prerequisites for AI, but they are hardly the whole thing. Companies are spending billions on this stuff and I hope they're just hedging in case it pans out rather…
I admit I recently upped that number from "5-10 years minimum" after seeing the media reaction to recent driver-assist systems related accidents — it became clear to me that the old adage "the autonomous car does not need to be perfect, it only needs to be better than an {average, good, skilled} human driver" is simply wrong, because autonomous car brand X will be regarded - and judged - as if all X cars are one driver. Thus, these cars actually need to be much better than humans in essentially any traffic situation, because it simply won't be acceptable for "autonomous cars of brand X" to kill a few thousand people each year in every country. People would equate this to a single human driver mowing down thousands.
This effect is not necessarily bad, I don't have the inside information, but it's likely (or at least probable) that manufacturers invested in this technology observed the same and drew a similar conclusion.
The question now is whether the car makers make autonomous cars that good, or invest into massive PR campaigning to change public perception towards "each autonomous car is like an individual driver and it doesn't need to do much better than that".
We've seen the latter before. Jaywalking and avenues are just two examples.
> I started a company called Cognitive Systems in 1981. Ahh. So just from the article, his gripe is of the “begs the question” sort — he’s not pleased with the evolution of idiom. Since he was doing “real AI” back then, who are these frauds to claim they are doing AI? His point may or may not be valid, but his specific argument is quite weak. He notes that even a person , an actual intelligence, wouldn’t know what Dy…
I'm no expert in the field of AI or Machine Learning, so I have a question for the experts here? Has there been any theoretical breakthrough in the AI in the recent years? I knew we had neural networks and different types of classifiers, etc. for more than a few of decades now, so apart from better marketing, has there been a significant breakthrough that explains this sudden surge in the interest in AI?
EDIT: This paper refers to the algorithm as SuperVision which was the team name, but it is more commonly called AlexNet. Here is another article discussing it:
https://qz.com/1034972/the-data-that-changed-the-direction-o...
The author's particular gripe is that the Watson advertisements showing someone sitting down and talking to "Watson." They bother me as well (and did so when I was working at IBM in the Watson group) because they portray a capability that nothing in IBM can provide. Nobody can provide it (again to the author's point) because dialog systems (those which interact with a user through conversational speech) don't exist o…
Earlier quoted context omitted.
When I hear AI I usually imagine deep learning, but many companies using the term don't specify.
But that's more "machine learning" which always seemed less "sexy" than AI -- basically just regression but better, not magical like AI.
I think that's probably the most helpful definition because your ML output has to go into some larger intelligence system (human or otherwise) to produce some decision / activity. So your choices are:
* Human * Expert system with rules of interpretation that include ML output as input * AI system which relies solely on inference and reinforcement / goal-seeking to produce output
Earlier quoted context omitted.
I'm interested in the original idea. Can you expand on how your ideal system would function?
Well, the hope was that Watson, having explored and built a connected knowledge graph from various sources, could ask probing, adaptive questions to find out where a person landed. So, say I'm an undergrad at a good university and I tell the system "I'm interested in Computer Science. I am particularly interested in Scientific Computing and would like to get to a graduate level of knowledge." The system might ask "So…