421–430 of 452 posts
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> it's still slower than typing In alphabetic languages. What about Chinese, or Japanese?
Typing in Japanese is about half as fast as English if you're good. Still better than handwriting.
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In addition to what novia said about your first sentence, your comment is so weirdly off-base. You have very strong opinions about pen computing, but where in reality are they coming from? No, we are not talking about the 1940s, why would anyone be talking about the 1940s? How does that make any sense at all? We aren't talking about a Microsoft demo that worked well for you once, either. We are talking about the fact…
I don't have strong opinions about pen computing, but the comment I replied to was just giving a bad impression of the tech in the early 2000s. It worked quite well actually. Since he didn't specify the timeframe, I gave him the benefit of the doubt and thought it he was talking about before my time.
Apart from the problems mentioned in the comment you replied to. You don't seem to have a point other than being contrarian (as a state).
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> The other was companies who had tricked people into learning a new kind of handwriting [...] It's interesting parallels with spoken word interfaces. I don't know what the answer is. Well, here's a possibility: we'll meet in the middle. Companies will train humans into learning a new kind of speech which is more easily machine-recognisable. These dialects will be very similar to English but more constrained in synta…
Of course, voice assistants are already doing this to us a bit. Once I learn the phrasing that works reliably, I stick with it, even though repeating "Add ___ to shopping list" for every item feels like the equivalent of GOTO statements. The challenge with learning anything new from our voicebots is the same as it already is: discoverability. I don't have the patience to listen to Siri's canned response when it's don…
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What are the big successes? Speech recognition? Which still seems rather bad to me. Language translation (which for the languages I’m interested in (Japanese) is still almost totally unusable? Self driving cars? Which are not yet in production (and where the social issues are probably far harder than the technical ones, and likely have been since the 90s). Is there some big application if ML that I’m missing that is…
I work on Amelia at IPSoft, things seem to be going well. Customer Service is a huge, overlooked industry mostly based around classifying requests and then performing a rote action, which is a great use case for AI.
In my opinion, sales at IPsoft faced some of the same challenges initially (selling the idea of AI vs selling a well working solution for a specific problem), but has become more focused now that they have proven use cases in the field.
As you say, service desks are a great opportunity for ML. They're seen as cost centers, typically plagued by high attrition of employees, provide inconsistent service levels, and spend the majority of their time on requests that are relatively standard. Still, it is not an automatic effort: integrating with back-end systems, creating a dataset to start classifying incoming requests, and defining the processes to handle them are (mostly) still manual work.
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…
> Unfortunately many, many people think that talking to your computer in actually already possible, they just haven't experienced it yet. Given how often another person can't correctly infer meaning when people talk, I doubt it will ever be how people imagine it. Initially, I imagine it will be a lot of people trying to talk normally and a lot of AI responses asking how your poorly worded worded request should be car…
That's what Roger Schank is advocating against in his article: artificial intelligence that makes humans think like computers, rather than computers that think like humans.
Personally, I think it's a terrible idea and the path to becoming like the Borg: a species of people who "enhanced" themselves until they lost everything that made them people.
Also: people may get stuff wrong a lot of the time (way more than 10%). But, you can always make a human understand what you mean with enough effort. Not so with a "computer" (i.e. an NLP system). Currently, if a computer can't process an utterance, trying to explain it will confuse it even further.
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In a previous job I looked into the viability of pen computing, specifically which companies had succeeded commercially with a pen-based interface. A lot of folks are too young to know this, but there was a time when it was accepted wisdom that much of personal computing would eventually converge to a pen-based interface, with the primary enabling technology being handwriting recognition. What I found is that compute…
I'd just like to see a voice interface that has any attempt at natural error correction. We do this in a hundred ways in English, emphasis, meta-words, too many to fold into a system. But with a little user prodding, I think you could cover enough of this ground to still sound almost natural. Asst.: Would you like me to read that back to you? User: Yes A: The click brown ox... U: The _quick_ brown _fox_... A: Ok. The…
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> Like, using a word for "(economic/technological) development" to describe "advanced cancer" That sounds like a mistake caused by the translator having a (relatively) poor knowledge of English. A bilingual English/Korean speaker wouldn't make that mistake. I mean, I don't know your linguistic background, but you clearly know enough English and Korean to know that that's a bad translation, and you presumably wouldn't…
> A bilingual English/Korean speaker wouldn't make that mistake. Well, "bilingual" is not black and white. I think you have a point here, but considering that people who are paid to translate can't get these stuff right, the argument veers into the territory of "no true bilingual person". Anyway, my pet theory is that it is surprisingly hard to translate from language A to B, even when you are reasonably good at both…
Not entirely, but it is definitely possible for someone to be a native speaker of two languages, and they wouldn't make those kinds of mistakes if they were.
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>Unfortunately people compare these to a collection of the best translators in the world. I don't think that's really true. They're comparing them to the performance of a person who is a native speaker of both of the languages in question. That seems like a pretty reasonable comparison point, since it's basically the ceiling for performance on a translation task (leaving aside literary aspects of translation). If you…
>They're comparing them to the performance of a person who is a native speaker of both of the languages in question. Which is synonymous with the best translators in the world. Those people are relatively few and far between honestly - I've traveled a lot and I'd argue that native bi-lingual people are quite rare.
https://www.researchgate.net/post/What_is_the_percentage_of_...
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…
We’d all see the problem with such a situation. People with a 6th grade knowledge on space travel understand that the commercials were BS marketing and we should fire the executives for not knowing the same or doing their due diligence. We’d be mad at SpaceX for taking advantage of companies and failing to reach Mars as promised.