7 ms·

I think a problem is the tighter cycle between academic discoveries and business people trying to monetize them. Large language models were developed, objective

I think a problem is the tighter cycle between academic discoveries and business people trying to monetize them. Large language models were developed, objectively a great achievement, and immediately someone nontechnical wants to apply their own interpretation and imagine that we can build a chatbot that you won't have to pay, and before you know it, people are selling and even deploying them. Anyone who questions or points out that the technology doesn't do what the business people think it does just gets dismissed as not understanding.

melony 5y ago
That's a good thing. The market is very good at empirically validating research. It helps filter out the chaff and ensure research is useful. Better than academia wasting years on concepts like the "semantic web" where nobody can even agree on what it means. Academia is under attack from many political directions right now, being able to show useful output will help it thrive in the long run.
- manquer 5y ago
  Research takes time, launching something prematurely which is clearly not ready for practical application will sooner or later fail and suck out any further funding out the field. The goal of academic research is to further knowledge, as long as knowledge is produced even if is only that an approach will not work then they are not wasting anything. It is not job of academic research to monetize or even do work that can be potentially monetized. That what corporate research is for. If academia focused on monetization they wouldn't need to teach or depend on public funding to keen afloat. That is simply not their goal. Most academic scholars have a teaching day job and are more than fullfilling a useful role in society with just that . anything further is gravy
- deleted 5y ago
  [deleted]
- KittenInABox 5y ago
  > The market is very good at empirically validating research. It helps filter out the chaff and ensure research is useful. I am very skeptical and would like to see studies that evidence this. Counterfactually, the market would never tolerate the decades of research behind MRNA vaccines and the researchers behind it were considered useless. The market has also put in mind-blowing amounts of money towards the ameloid hypothesis behind alzheimers to massive disappointment.
  - netizen-936824 5y ago
    I agree with you. I don't think the market is good at validating any ideas or research. Salespeople will talk up their product to no end and over promise. The only thing the market validates is the ability of people to sell crap Being able to sell something doesn't necessarily mean that thing is good or correct in any way
- nfgrep 5y ago
  I can understand your reason for saying this, (useful things often sell well) but a market only validates that people are willing to pay for something, not that it is ‘valid’ empirically.
  - sam0x17 5y ago
    Right. By that same token, directly selling fentanyl or oxy to consumers without any regulations would surely sell well, as does nicotine, etc., but this doesn't mean it's good for society.
- nobodyandproud 5y ago
  > The market is very good at empirically validating research. The market can do this, if it’s correctly incentivized to do so. More often than not, the incentives just aren’t there or are compelling enough. Often it’s other businesses that put up such disincentives.
- numpad0 5y ago
  The problem with the market is it wants consistent, short-term successive, quantifiable production, and that seems to instantly kill all progress in a field of research. They just go laid back watching investments burn and prints worse and worse nonsense.
- sam0x17 5y ago
  Capital is far too short-sighted to look beyond this year or this quarter. Many of the important groundbreaking ideas or projects take years, even decades to formulate. As I've said elsewhere, capital will just take the easiest road it is allowed to take, which currently is stifling innovation, buying competitors, maintaining monopolies, relying on economies of scale to shut out competitors when they can't be acquired, and using lobbyists to ensure regulations that affect the status quo never pass. In the past the big tech corporations maintained huge corporate labs and actually did groundbreaking research with 15+ year projects. Now everything is short term. We can't even compel capital to see the long term value of preventing climate change, when Exon was aware this was going to happen as far back as the 1970s in excruciating detail. No, capital will innovate only if there are sufficient regulations in place, incentives, and guardrails, that there is no other choice than for them other than to innovate (which they will do begrudgingly). Capital is by no means a vehicle for innovation. When was the last time you saw innovation from Google in the search space, their bread and butter?
  - beepbooptheory 5y ago
    This is a really great way to frame it, because it really does seem to be about time/speed. I don't think we can even collectively comprehend great innovations that need many resources and time anymore, who has even the time to work on it? People need to have jobs after all.
  - simplestats 5y ago
    I cant think of the last time I saw the word "corporations" used in a post that wasn't part of an attack on them as inferior/evil/villanous etc. Speaking of NLP, your post would be very easy to classify sentiment of using a simple keyword approach. Anyway, I've worked both in academia and industry. Industry is simply more practical and better at technology. In tech areas, academia desperately needs industry to provide the feedback they provide. Especially in AI areas. You are thinking of CEO's or salespeople or something, but the people that matter here are the engineers. And I'd place their assessment over that of grad students any day. If the engineers can't make it work, then yes there's a problem here. Doesn't always mean it can't work, but for most ideas it probably does. By the way industry research labs certainly still exist. But long-term self-funded research has to compete with govt funding of research. Why throw your investor money at a high-risk idea when Stanford, MIT, and 100 other R1's are throwing taxpayer money at it? Otherwise industry labs end up just competing for govt gants ultimately. Meanwhile nowadays we see academia chasing short-term problems that industry leads in (and trying to patent them too).
- ClumsyPilot 5y ago
  "The market is very good at empirically validating research." That's why the market for homeopathy and fake medicine is worth $30,000,000,000, right?
dkarl 5y ago
There isn't really a new "problem" with AI. Businesses love hype, they love anything that can punch up a sales pitch, they love shitty cheap automation that replaces expensive human work, they love to identify ways to lower quality and save money without affecting revenue, and AI can be good for all of those things without being good at anything.
- semi-extrinsic 5y ago
  No, but most chatbots I've seen are no better than a well-structured FAQ page. We've had those since the mid 90s.
  - yawaworht1978 5y ago
    Some of them are literally a form linking to the faq part based on user input. I think it's ok as a first step to route customer care cases, like "payments issue","delete account" etc, but nothing more granular than that. That and link rot, when procedures have been updated, but the faq haven't. Infuriating.
  - emteycz 5y ago
    They are better in that someone actually reads the suggestions
  - version_five 5y ago
    I've often argued chatbots are much worse than an FAQ. With proper structure, like you say, it can be easy to see what is and isn't covered, and for things that are included, look up the answer. A chatbot is like an inefficient front end on an FAQ, you have to guess what they might be able to do, and guess what might trigger them to understand you. Best case scenario, you get the chatbot to provide you with a "help" response that's basically the FAQ. A simple list of options will always beat a "conversational interface" to a list of potential back-end actions. Incidentally, I think this gets obscured a but when dealing with businesses whose goal is to confuse or frustrate you into not taking action. If you look at Amazon or Uber's FAQ, they are designed to take you in circles and prevent you from getting any recourse or talking to a person. Chatbots could be helpful for this application
klabb3 5y ago
> Anyone who questions or points out that the technology doesn't do what the business people think it does[...] Uh oh, we've got a downer! Jokes aside, I'd like to consider an even simpler explanation, namely that "The purpose of a system is what it does"[1]. In this case, it would suggest decision makers are fully aware that they suck. Why would anyone want something that sucks? Because it's discouraging, and customer service today is all about discouragement. Unsubscribing, replacements, returns, special requests are all costs, and that's a fixable problem in the current business doctrine, especially in the faceless megacorp flavor of business. While chat bots (and other dark patterns) are frustrating, it creates a veil of plausible deniability for the business. It's hard to claim that it's deliberately hostile to customers, even though it's the simplest explanation. [1]: https://en.m.wikipedia.org/wiki/The_purpose_of_a_system_is_what_it_does https://en.m.wikipedia.org/wiki/The_purpose_of_a_system_is_w...
- lotsofpulp 5y ago
  I have to agree with this. I do not understand why I type all of my relevant information into a chatbot, and then a real person comes on the other end, and asks me all the same questions. Worse is when it is on the phone. I can only assume the intent is to discourage me, as that amount of ineptness is even more depressing to assume.
  - nmstoker 5y ago
    To be fair, people disregard the prior experience with other people too, so they're not necessarily treating bots that differently here. I had this in the supermarket the other day: went through an issue with the first person, they explained it to the more senior person who I heard listening, she then ignored what was said and repeated the exact same steps (whilst I was trying to talk her out of it because I could see it was a waste of even more time!) What I find odd about the online time wasting approach is that I just get the money back from the bank eventually, so they lose in the short-term (as the bank is sure to pass this cost back to the company) plus next time/long term I take my business elsewhere because I then know they aren't an honest participant.
thewarrior 5y ago
GPT-3 needs proper prompting to get the right output. Here's the same question as in the blogpost posed differently Student: Why is it unsafe to walk backwards down a staircase with my eyes closed ? Teacher: You can't see the step behind you! The "teacher" here is GPT-3 and answered the question easily. People are in denial of genuine progress. Student: Do you think I could predict changes in stock prices better if I used 10-year Treasury rates or the temperature in Curtin, Australia? Stock trader: I don't know. You might be able to, but I can't. The problem is that the temperature changes are so small that they won't be statistically significant. It's a question of sample size. An individual day's temperature in one location is far less likely to be an indicator of stock prices than the interest rate. Student: Why is that ? Stock trader: That's because interest rates are much more likely to affect the economy than a single day's temperature. Student: Why do interest rates affect the economy ? Stock trader: Interest rates are a measure of the cost of money, so the interest rate is a measure of the cost of capital. If the cost of capital is high, firms will borrow less money and they'll invest less. That means they won't be as profitable, and stock prices will fall. Quiz question: Who is the President of the United States? Answer: Donald Trump. I did get junk answers as well (it said that Jimi Hendrix is the president) but I have a better intuition of how to put GPT-3 in the right "frame of mind". GPT-3 is a text completion engine. It doesn't know whether you want it to produce a story, a reddit flamewar or a PhD thesis. You need to provide the hints. One prompt cannot answer any and all questions. If it were that good we would be jobless. It's far from perfect but it's beginning to get there.
- barthelomew 5y ago
  Once you start prompt-engineering, the answers, in seclusion look pretty great - and show some understanding of the domain. Yet, if you donot do this - they end up spitting out some randomly associated phrases/answers. This is a problem when you're asking a model, a question who's answer you donot completely know. How do you trust it to give the right answer? If you donot know the answer beforehand - you cannot prompt-engineer the model to give the "right answers". "Expert systems" from the 80s and the 90s, were pretty good at giving the "right answers" inside a closed domain. Those were truly wonderful systems.
  - 5y ago
kirso 5y ago
I love this answer because it resonates. As a former business person who learned the technical ins and outs, I believe the reason why this is happening is because majority of the population is uneducated how general tech works under the hood. I am not even speaking about coding syntax but the abstractions of what does AI actually mean, how it works with data and what are the limitations. The vast majority of business people think they get it, but they majorly overestimate the work required to actually produce output (whether it's ML or software in general). However that's hard to do when you haven't actually done it (talking about deliberate practice). Despite that gap, we still need to push commercially viable apps out there to seek progress, the question is rather what is the gap between the reality and expectations and what is really being marketed as a capability.

melony 5y ago

That's a good thing. The market is very good at empirically validating research. It helps filter out the chaff and ensure research is useful. Better than academia wasting years on concepts like the "semantic web" where nobody can even agree on what it means. Academia is under attack from many political directions right now, being able to show useful output will help it thrive in the long run.

manquer 5y ago
Research takes time, launching something prematurely which is clearly not ready for practical application will sooner or later fail and suck out any further funding out the field. The goal of academic research is to further knowledge, as long as knowledge is produced even if is only that an approach will not work then they are not wasting anything. It is not job of academic research to monetize or even do work that can be potentially monetized. That what corporate research is for. If academia focused on monetization they wouldn't need to teach or depend on public funding to keen afloat. That is simply not their goal. Most academic scholars have a teaching day job and are more than fullfilling a useful role in society with just that . anything further is gravy
deleted 5y ago
[deleted]
KittenInABox 5y ago
> The market is very good at empirically validating research. It helps filter out the chaff and ensure research is useful. I am very skeptical and would like to see studies that evidence this. Counterfactually, the market would never tolerate the decades of research behind MRNA vaccines and the researchers behind it were considered useless. The market has also put in mind-blowing amounts of money towards the ameloid hypothesis behind alzheimers to massive disappointment.
- netizen-936824 5y ago
  I agree with you. I don't think the market is good at validating any ideas or research. Salespeople will talk up their product to no end and over promise. The only thing the market validates is the ability of people to sell crap Being able to sell something doesn't necessarily mean that thing is good or correct in any way
nfgrep 5y ago
I can understand your reason for saying this, (useful things often sell well) but a market only validates that people are willing to pay for something, not that it is ‘valid’ empirically.
- sam0x17 5y ago
  Right. By that same token, directly selling fentanyl or oxy to consumers without any regulations would surely sell well, as does nicotine, etc., but this doesn't mean it's good for society.
nobodyandproud 5y ago
> The market is very good at empirically validating research. The market can do this, if it’s correctly incentivized to do so. More often than not, the incentives just aren’t there or are compelling enough. Often it’s other businesses that put up such disincentives.
numpad0 5y ago
The problem with the market is it wants consistent, short-term successive, quantifiable production, and that seems to instantly kill all progress in a field of research. They just go laid back watching investments burn and prints worse and worse nonsense.
sam0x17 5y ago
Capital is far too short-sighted to look beyond this year or this quarter. Many of the important groundbreaking ideas or projects take years, even decades to formulate. As I've said elsewhere, capital will just take the easiest road it is allowed to take, which currently is stifling innovation, buying competitors, maintaining monopolies, relying on economies of scale to shut out competitors when they can't be acquired, and using lobbyists to ensure regulations that affect the status quo never pass. In the past the big tech corporations maintained huge corporate labs and actually did groundbreaking research with 15+ year projects. Now everything is short term. We can't even compel capital to see the long term value of preventing climate change, when Exon was aware this was going to happen as far back as the 1970s in excruciating detail. No, capital will innovate only if there are sufficient regulations in place, incentives, and guardrails, that there is no other choice than for them other than to innovate (which they will do begrudgingly). Capital is by no means a vehicle for innovation. When was the last time you saw innovation from Google in the search space, their bread and butter?
- beepbooptheory 5y ago
  This is a really great way to frame it, because it really does seem to be about time/speed. I don't think we can even collectively comprehend great innovations that need many resources and time anymore, who has even the time to work on it? People need to have jobs after all.
- simplestats 5y ago
  I cant think of the last time I saw the word "corporations" used in a post that wasn't part of an attack on them as inferior/evil/villanous etc. Speaking of NLP, your post would be very easy to classify sentiment of using a simple keyword approach. Anyway, I've worked both in academia and industry. Industry is simply more practical and better at technology. In tech areas, academia desperately needs industry to provide the feedback they provide. Especially in AI areas. You are thinking of CEO's or salespeople or something, but the people that matter here are the engineers. And I'd place their assessment over that of grad students any day. If the engineers can't make it work, then yes there's a problem here. Doesn't always mean it can't work, but for most ideas it probably does. By the way industry research labs certainly still exist. But long-term self-funded research has to compete with govt funding of research. Why throw your investor money at a high-risk idea when Stanford, MIT, and 100 other R1's are throwing taxpayer money at it? Otherwise industry labs end up just competing for govt gants ultimately. Meanwhile nowadays we see academia chasing short-term problems that industry leads in (and trying to patent them too).
ClumsyPilot 5y ago
"The market is very good at empirically validating research." That's why the market for homeopathy and fake medicine is worth $30,000,000,000, right?

dkarl 5y ago

There isn't really a new "problem" with AI. Businesses love hype, they love anything that can punch up a sales pitch, they love shitty cheap automation that replaces expensive human work, they love to identify ways to lower quality and save money without affecting revenue, and AI can be good for all of those things without being good at anything.

semi-extrinsic 5y ago
No, but most chatbots I've seen are no better than a well-structured FAQ page. We've had those since the mid 90s.
- yawaworht1978 5y ago
  Some of them are literally a form linking to the faq part based on user input. I think it's ok as a first step to route customer care cases, like "payments issue","delete account" etc, but nothing more granular than that. That and link rot, when procedures have been updated, but the faq haven't. Infuriating.
- emteycz 5y ago
  They are better in that someone actually reads the suggestions
- version_five 5y ago
  I've often argued chatbots are much worse than an FAQ. With proper structure, like you say, it can be easy to see what is and isn't covered, and for things that are included, look up the answer. A chatbot is like an inefficient front end on an FAQ, you have to guess what they might be able to do, and guess what might trigger them to understand you. Best case scenario, you get the chatbot to provide you with a "help" response that's basically the FAQ. A simple list of options will always beat a "conversational interface" to a list of potential back-end actions. Incidentally, I think this gets obscured a but when dealing with businesses whose goal is to confuse or frustrate you into not taking action. If you look at Amazon or Uber's FAQ, they are designed to take you in circles and prevent you from getting any recourse or talking to a person. Chatbots could be helpful for this application

klabb3 5y ago

> Anyone who questions or points out that the technology doesn't do what the business people think it does[...] Uh oh, we've got a downer! Jokes aside, I'd like to consider an even simpler explanation, namely that "The purpose of a system is what it does"[1]. In this case, it would suggest decision makers are fully aware that they suck. Why would anyone want something that sucks? Because it's discouraging, and customer service today is all about discouragement. Unsubscribing, replacements, returns, special requests are all costs, and that's a fixable problem in the current business doctrine, especially in the faceless megacorp flavor of business. While chat bots (and other dark patterns) are frustrating, it creates a veil of plausible deniability for the business. It's hard to claim that it's deliberately hostile to customers, even though it's the simplest explanation. [1]: https://en.m.wikipedia.org/wiki/The_purpose_of_a_system_is_what_it_does https://en.m.wikipedia.org/wiki/The_purpose_of_a_system_is_w...

lotsofpulp 5y ago
I have to agree with this. I do not understand why I type all of my relevant information into a chatbot, and then a real person comes on the other end, and asks me all the same questions. Worse is when it is on the phone. I can only assume the intent is to discourage me, as that amount of ineptness is even more depressing to assume.
- nmstoker 5y ago
  To be fair, people disregard the prior experience with other people too, so they're not necessarily treating bots that differently here. I had this in the supermarket the other day: went through an issue with the first person, they explained it to the more senior person who I heard listening, she then ignored what was said and repeated the exact same steps (whilst I was trying to talk her out of it because I could see it was a waste of even more time!) What I find odd about the online time wasting approach is that I just get the money back from the bank eventually, so they lose in the short-term (as the bank is sure to pass this cost back to the company) plus next time/long term I take my business elsewhere because I then know they aren't an honest participant.

thewarrior 5y ago

GPT-3 needs proper prompting to get the right output. Here's the same question as in the blogpost posed differently Student: Why is it unsafe to walk backwards down a staircase with my eyes closed ? Teacher: You can't see the step behind you! The "teacher" here is GPT-3 and answered the question easily. People are in denial of genuine progress. Student: Do you think I could predict changes in stock prices better if I used 10-year Treasury rates or the temperature in Curtin, Australia? Stock trader: I don't know. You might be able to, but I can't. The problem is that the temperature changes are so small that they won't be statistically significant. It's a question of sample size. An individual day's temperature in one location is far less likely to be an indicator of stock prices than the interest rate. Student: Why is that ? Stock trader: That's because interest rates are much more likely to affect the economy than a single day's temperature. Student: Why do interest rates affect the economy ? Stock trader: Interest rates are a measure of the cost of money, so the interest rate is a measure of the cost of capital. If the cost of capital is high, firms will borrow less money and they'll invest less. That means they won't be as profitable, and stock prices will fall. Quiz question: Who is the President of the United States? Answer: Donald Trump. I did get junk answers as well (it said that Jimi Hendrix is the president) but I have a better intuition of how to put GPT-3 in the right "frame of mind". GPT-3 is a text completion engine. It doesn't know whether you want it to produce a story, a reddit flamewar or a PhD thesis. You need to provide the hints. One prompt cannot answer any and all questions. If it were that good we would be jobless. It's far from perfect but it's beginning to get there.

barthelomew 5y ago
Once you start prompt-engineering, the answers, in seclusion look pretty great - and show some understanding of the domain. Yet, if you donot do this - they end up spitting out some randomly associated phrases/answers. This is a problem when you're asking a model, a question who's answer you donot completely know. How do you trust it to give the right answer? If you donot know the answer beforehand - you cannot prompt-engineer the model to give the "right answers". "Expert systems" from the 80s and the 90s, were pretty good at giving the "right answers" inside a closed domain. Those were truly wonderful systems.
- 5y ago

kirso 5y ago

I love this answer because it resonates. As a former business person who learned the technical ins and outs, I believe the reason why this is happening is because majority of the population is uneducated how general tech works under the hood. I am not even speaking about coding syntax but the abstractions of what does AI actually mean, how it works with data and what are the limitations. The vast majority of business people think they get it, but they majorly overestimate the work required to actually produce output (whether it's ML or software in general). However that's hard to do when you haven't actually done it (talking about deliberate practice). Despite that gap, we still need to push commercially viable apps out there to seek progress, the question is rather what is the gap between the reality and expectations and what is really being marketed as a capability.