6 ms·

> the models are in an important way indifferent to the truth of their outputs Everyone who spends a bit of time with LLMs is aware of this. My question - and

> the models are in an important way indifferent to the truth of their outputs Everyone who spends a bit of time with LLMs is aware of this. My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. I, as a laymen on the periphery of this phenomenon, am acutely aware that LLMs are not useful in applications requiring accuracy. I would not invest my company’s dollars or resources into such a technology. But they do. What am I missing? Is it the promise that LLMs will replace employees? How would that be believable for anyone willing to investigate the technology and its limitations, even a little bit?

pheggs 2y ago
I assume that's what c-level people have in their mind: Nothing is accurate and fail-safe 100%. You just have to reach a level where it is good enough most of the times to make money with it. Also, human brains are neural networks too, so that's where we know what the minimum is which is (theoretically) possible with this kind of technology.
- GOD_Over_Djinn 2y ago
  [flagged]
  - lupusreal 2y ago
    What do you think artificial neural networks were inspired by?
    - GOD_Over_Djinn 2y ago
      I don’t care what they were inspired by, because that’s not what we’re talking about. The comment I replied to said that brains ARE neural networks, in a literal sense. This is a common misconception, but is well known to be just that among people who are actually well-informed on the topic. Just because you don’t understand it doesn’t make it any less true.
      - lupusreal 2y ago
        Brains are networks of neurons, e.g. neural nets. They also contain other structures like blood vessels, etc, but it is completely reasonable to say they are neural networks.
        GOD_Over_Djinn 2y ago
        Sure, that makes a ton of sense. Kind of like how an airplane is a type of bird.
        lupusreal 2y ago
        Again, you are confusing neural networks with artificial neural networks. Neural networks are to artificial neural networks as birds are to ornithopters. Why don't you just cut to the chase and bring out the dualism "antennas for the soul" crap already? No sense beating around the bush, your username has me sure it's coming eventually.
        meiraleal 2y ago
        Ironically, a drone is becoming increasingly similar to a type of bird. In 100 years, when they might be made of organic material, I would guess it will be normal to call them birds.
yoav 2y ago
When you have a slack conversation with a coworker they are often not 100% accurate. Working with an LLM is much like working with a coworker that has a knowledge base as wide as the entire internet. It is exceptionally useful. There are a wide range of applications that may even require 100% accuracy in final output but do not require 100% accuracy in every conversation that leads to that output. For the last 6 months I have built things that would have taken me 4x as long in programming languages that I’ve never used before. I am a team of 1 that has the output of a team of 4 without the overhead of meetings
- slow_typist 2y ago
  Could you pls elaborate a bit on what you are developing?
CapeTheory 2y ago
> What am I missing? I think it can be summarised as "FOMO".
kjkjadksj 2y ago
Because if you utter AI in your earnings call your stock moons. Thats the drive right now. The executive thinks in the short term and keeping up with the joneses so to speak and jumping off the AI cliff with the rest of the lemmings is what their investors are expecting.
silverquiet 2y ago
There is a market for bullshit and LLMs bring the cost of bullshit generation down.
- surfingdino 2y ago
  The market for bullshit is infinite.
threeseed 2y ago
> What are the c-suite execs and specifically CTOs seeing So I can speak to this since I am trying to sell to them. CEO is being told from the markets, board, consultancies, Gartner etc that you need to have a Generative AI strategy. What that means in practice is irrelevant. You just need to throw it all against a wall and see what sticks. If you don't then the risk is you get left behind. CEO is telling the CIO that the need to figure this all out with the obvious pilot programs being in Customer Support and Search which the CFO has been tasked to find budget for. The problem is that the data in these companies is poor and getting poorer as the number of SaaS apps explode and they are forced to just dump everything in a messy data lake. Which is why for the CDO, AI is like their #6 concern and is going to make their lives 100x harder. The logical conclusion to all of this is that 95% of these projects will fail: (a) data is bad with no easy way to fix it, (b) LLMs are inaccurate/biased making them a risk, (c) ROI is poor, (d) data privacy/sovereignty is a mess.
- dvfjsdhgfv 2y ago
  > CEO is being told from the markets, board, consultancies, Gartner etc that you need to have a Generative AI strategy. What that means in practice is irrelevant. You just need to throw it all against a wall and see what sticks. If you don't then the risk is you get left behind. I can confirm this is the default view at many companies, just the usual FOMO - the irony being this happens even in the companies that are valued for not delivering computer-generated content. Using AI they actually take a greater risk than not doing that - but well, the CEOs somehow are convinced they have no other choice.
- itsdrewmiller 2y ago
  Nailed it! I want to buy whatever it is you’re building.
empath75 2y ago
That the LLMs are wrong sometimes is no more relevant to their value than that humans are wrong sometimes.
- threeseed 2y ago
  It's how LLMs are wrong that is the problem. Companies revolve around risk management and whilst people can be wrong, biased, discriminatory etc there are measures that can be taken to mitigate them. There are no comparable mitigations for LLMs. And so if your LLM continually tells people to eat rocks or glue and you can't do anything about it then that very much impacts their value.
  - tim333 2y ago
    You can tell the LLM it's wrong like you can with people.
surfingdino 2y ago
> how is it possible that we see such incredible investments in LLMs? Because somehow LLMs became the next "big thing" that nobody can explain but everyone wants to be involved in. It's like audio streaming, the most ineffective form of audio distribution, but for a while it seemed like a good idea. > What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. The are idiots following the herd. They climb the greasy ladder of corporate career and fear getting fired. Their smarts are in corporate politics not in tech. And even if they were smart enough to tell that LLMs are an example of a research project that has received way too much funding, they need to appease the gods of Wall St who will judge them and punish them with a downgrade of the stock price if they cannot answer one question "What is your AI strategy?" It doesn't matter that the Wall St guys need help getting out of a strip bar, they have the power to ruin stockholders. This is why Apple, Google, and Salesforce are spending money of AI projects as a form of defence, not as a way to build new products or services. It's to show that they are relevant and can innovate. Voice assistants were the same thing, so were chatbots, and audio and video streaming services (remember Groove Music Pass), touchscreens, pocket audio players (remember Zune?), etc. Fortunately for all involved, investors are already wondering if an AI correction is coming? I think we may see a wipeout of a lot of investments in AI soon.
- pheggs 2y ago
  > Because somehow LLMs became the next "big thing" that nobody can explain but everyone wants to be involved in. It's like audio streaming, the most ineffective form of audio distribution, but for a while it seemed like a good idea. I know it's slightly off topic, but could you elaborate on the "audio streaming" part?
  - surfingdino 2y ago
    Sure. Compared to traditional broadcast over airwaves or even a download to a device that can play audio without having to stream it from the server, audio streaming is the least efficient and the least convenient form of audio delivery. When you have a transmitter, people adding a thousand new radio receivers in the area does not increase your cost as a broadcaster, adding a thousand clients requires more bandwidth, and more infrastructure. I never understood why audio streaming became as popular as it did when better forms of distribution were available.
madsbuch 2y ago
> in applications requiring accuracy You have it right there. There is a large set of applications that does not require accuracy. These applications will benefit hugely from LLMs. Examples include recommender systems, knowledge extraction, transformation, etc. all in domains where accuracy does not matter too much. In particular, instruct aligned LLMs makes it very easy to integrate ad hoc machine learning into an application.
thaanpaa 2y ago
FOMO, probably. Just like any other tech bubble, really.
layer8 2y ago
> how is it possible that we see such incredible investments in LLMs? Profitability doesn’t require accuracy, generally speaking. Bullshitting often is a successful strategy, as politics and marketing amply demonstrate.
kikimora 2y ago
>My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? Opportunities like this happens once in 5-10 years when “the next big thing” are in the radar. Idea behind this investments is to bullshit it’s way to the Series B or IPO where original investors can exit. It is not about usefulness but about using momentum of the situation to extract money.
- GOD_Over_Djinn 2y ago
  I think you’ve really captured the essence of this phenomena in a remarkably succinct way. I do hope that business leaders eventually develop their own capabilities for independent creative thought, rather than being a bunch of mindless also-rans.
tbrownaw 2y ago
> What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. > I, as a laymen on the periphery of this phenomenon, am acutely aware that LLMs are not useful in applications requiring accuracy. They are not useful in isolation. They can be very useful as part of a larger process, especially if they particular way that you're using them has a low error rate. (And given a particular task you can in fact measure the error rate, or how often the generated bullshit happens by chance to (not) be true.) Most processes that involve steps done by humans have built-in pieces to catch and correct errors, because humans also make errors. If the error rate of the LLM component is lower than the error rate of the human it's replacing, you're fine. If it's higher but the cost of catching and fixing the extra errors is lower than the cost of the replaced human, you're still fine. (The person who you just sent the way of the buggy whip manufactures might be less fine, but that's Somebody Else's Problem.)
ffsm8 2y ago
> My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? LLMs are going to revolutionize the way the government, your employer and advertisers will spy on you. That's a pretty high value right there
tivert 2y ago
> My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? The same reason we did for blockchain. It's a sexy new technology, with amazing demos and hype. People who want to be entrepreneurs but have no ideas of their own race to apply it everywhere because they think hitching their wagon to this horse could be their shot. Boring old companies wanting to seem hot. Lots of FOMO.
- coffeebeqn 2y ago
  What were the amazing demos for crypto? Hype- sure.
  - tivert 2y ago
    Bitcoin itself.
AnimalMuppet 2y ago
> the models are in an important way indifferent to the truth of their outputs They're indifferent to the truth of their inputs, too. That's also a problem.
thefz 2y ago
> What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. It's a whoa moment for the general population. Look, the computer can understand and respond in natural language. I don't think there is other value in LLMs. Other applications of AI are very good, though.
- lxgr 2y ago
  They are also very good at translating between natural and structured/"computer" language. At a much higher rate than anything I've seen before in any algorithm, they "get" irony, sarcasm etc., when until a few years ago, I (as a non-linguist), assumed that any such solution to the "aboutness" problem would require solving AGI. That alone is worth a lot in a world which spends considerable resources on people that effectively work as translators between human and structured language. Besides that, I suspect that their existence is seen as a strong and remarkable hint that intelligence really might just be a quantitative phenomenon emergent from throwing a lot of compute at a lot of data, which at some point might become self-reinforcing. Whether that's true or not, and for better or worse, that's what people now seem to be set on doing.
  - slow_typist 2y ago
    LLMs don’t get irony. That is not how they work. They simulate getting it.
TradingPlaces 2y ago
My view is that there is extrapolation going on. They look at the progression of GPT 2-3-4 over a relatively short number of years and are extrapolating to a near future where these things are much more capable. FOMO. But the history of AI is huge leaps from a technological innovation, followed by years of crawl, and all this extrapolation may be wrong.
1vuio0pswjnm7 2y ago
"Is it the promise that LLMs will replace employees?" If we accept the conclusions of the paper, perhaps LLMs can replace employees who are bullshitters. For example, Microsoft has announced layoffs claiming "AI wave" as the cause. Perhaps so-called "tech" companies like Microsoft employ bullshitters and "AI" can replace them. Employees who act as if they are right 100% of the time when in truth they are wrong at least 20% of the time. Why hire people who can only be relied on 80% of the time, and who will never do what it takes to reach 100%, if this "work" can be done by a computer.
fragmede 2y ago
If you're only looking at English generation, and focusing on the limitations, you're missing the bigger picture. The AI revolution is about the fact that we have now have the ability to produce ChatGPT level of thing, but for all of the kinds of data that companies have, not just English text. The idea isn't that it will replace the employees, but that the employees will be augmented by AI and be able to be way more productive. What executive hasn't wished they had 10x the people on a project at a fraction of the cost. The allure for a CTO isn't about LLMs, it's about resource management. staring at the hallucination problem is missing the forest for the trees. yes it's a problem, but holy shit, the thing generates essays as fast as the GPU can dot-product and matrix multiply. CTOs are buying into the idea that we've invented cars, when before we were just looking at a faster horse.
meiraleal 2y ago
> I, as a laymen on the periphery of this phenomenon, am acutely aware that LLMs are not useful in applications requiring accuracy. How accurate do you think humans are? 100%? 80%? 20%? If LLMs can be 20% as accurate as humans, the use cases are infinite. And it can only go up.
stemlord 2y ago
chatgpt and code completion tools have pretty much doubled my productivity... "write me this tedious function in c# for unity" could save me up to a couple minutes, "what are 5 makes and models of PoE switches used in industrial applications?" could save me up to an hour

pheggs 2y ago

I assume that's what c-level people have in their mind: Nothing is accurate and fail-safe 100%. You just have to reach a level where it is good enough most of the times to make money with it. Also, human brains are neural networks too, so that's where we know what the minimum is which is (theoretically) possible with this kind of technology.

GOD_Over_Djinn 2y ago
[flagged]
- lupusreal 2y ago
  What do you think artificial neural networks were inspired by?
  - GOD_Over_Djinn 2y ago
    I don’t care what they were inspired by, because that’s not what we’re talking about. The comment I replied to said that brains ARE neural networks, in a literal sense. This is a common misconception, but is well known to be just that among people who are actually well-informed on the topic. Just because you don’t understand it doesn’t make it any less true.
    - lupusreal 2y ago
      Brains are networks of neurons, e.g. neural nets. They also contain other structures like blood vessels, etc, but it is completely reasonable to say they are neural networks.
      - GOD_Over_Djinn 2y ago
        Sure, that makes a ton of sense. Kind of like how an airplane is a type of bird.
        lupusreal 2y ago
        Again, you are confusing neural networks with artificial neural networks. Neural networks are to artificial neural networks as birds are to ornithopters. Why don't you just cut to the chase and bring out the dualism "antennas for the soul" crap already? No sense beating around the bush, your username has me sure it's coming eventually.
        meiraleal 2y ago
        Ironically, a drone is becoming increasingly similar to a type of bird. In 100 years, when they might be made of organic material, I would guess it will be normal to call them birds.

yoav 2y ago

When you have a slack conversation with a coworker they are often not 100% accurate. Working with an LLM is much like working with a coworker that has a knowledge base as wide as the entire internet. It is exceptionally useful. There are a wide range of applications that may even require 100% accuracy in final output but do not require 100% accuracy in every conversation that leads to that output. For the last 6 months I have built things that would have taken me 4x as long in programming languages that I’ve never used before. I am a team of 1 that has the output of a team of 4 without the overhead of meetings

slow_typist 2y ago
Could you pls elaborate a bit on what you are developing?

CapeTheory 2y ago

> What am I missing? I think it can be summarised as "FOMO".

kjkjadksj 2y ago

Because if you utter AI in your earnings call your stock moons. Thats the drive right now. The executive thinks in the short term and keeping up with the joneses so to speak and jumping off the AI cliff with the rest of the lemmings is what their investors are expecting.

silverquiet 2y ago

There is a market for bullshit and LLMs bring the cost of bullshit generation down.

surfingdino 2y ago
The market for bullshit is infinite.

threeseed 2y ago

> What are the c-suite execs and specifically CTOs seeing So I can speak to this since I am trying to sell to them. CEO is being told from the markets, board, consultancies, Gartner etc that you need to have a Generative AI strategy. What that means in practice is irrelevant. You just need to throw it all against a wall and see what sticks. If you don't then the risk is you get left behind. CEO is telling the CIO that the need to figure this all out with the obvious pilot programs being in Customer Support and Search which the CFO has been tasked to find budget for. The problem is that the data in these companies is poor and getting poorer as the number of SaaS apps explode and they are forced to just dump everything in a messy data lake. Which is why for the CDO, AI is like their #6 concern and is going to make their lives 100x harder. The logical conclusion to all of this is that 95% of these projects will fail: (a) data is bad with no easy way to fix it, (b) LLMs are inaccurate/biased making them a risk, (c) ROI is poor, (d) data privacy/sovereignty is a mess.

dvfjsdhgfv 2y ago
> CEO is being told from the markets, board, consultancies, Gartner etc that you need to have a Generative AI strategy. What that means in practice is irrelevant. You just need to throw it all against a wall and see what sticks. If you don't then the risk is you get left behind. I can confirm this is the default view at many companies, just the usual FOMO - the irony being this happens even in the companies that are valued for not delivering computer-generated content. Using AI they actually take a greater risk than not doing that - but well, the CEOs somehow are convinced they have no other choice.
itsdrewmiller 2y ago
Nailed it! I want to buy whatever it is you’re building.

empath75 2y ago

That the LLMs are wrong sometimes is no more relevant to their value than that humans are wrong sometimes.

threeseed 2y ago
It's how LLMs are wrong that is the problem. Companies revolve around risk management and whilst people can be wrong, biased, discriminatory etc there are measures that can be taken to mitigate them. There are no comparable mitigations for LLMs. And so if your LLM continually tells people to eat rocks or glue and you can't do anything about it then that very much impacts their value.
- tim333 2y ago
  You can tell the LLM it's wrong like you can with people.

surfingdino 2y ago

> how is it possible that we see such incredible investments in LLMs? Because somehow LLMs became the next "big thing" that nobody can explain but everyone wants to be involved in. It's like audio streaming, the most ineffective form of audio distribution, but for a while it seemed like a good idea. > What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. The are idiots following the herd. They climb the greasy ladder of corporate career and fear getting fired. Their smarts are in corporate politics not in tech. And even if they were smart enough to tell that LLMs are an example of a research project that has received way too much funding, they need to appease the gods of Wall St who will judge them and punish them with a downgrade of the stock price if they cannot answer one question "What is your AI strategy?" It doesn't matter that the Wall St guys need help getting out of a strip bar, they have the power to ruin stockholders. This is why Apple, Google, and Salesforce are spending money of AI projects as a form of defence, not as a way to build new products or services. It's to show that they are relevant and can innovate. Voice assistants were the same thing, so were chatbots, and audio and video streaming services (remember Groove Music Pass), touchscreens, pocket audio players (remember Zune?), etc. Fortunately for all involved, investors are already wondering if an AI correction is coming? I think we may see a wipeout of a lot of investments in AI soon.

pheggs 2y ago
> Because somehow LLMs became the next "big thing" that nobody can explain but everyone wants to be involved in. It's like audio streaming, the most ineffective form of audio distribution, but for a while it seemed like a good idea. I know it's slightly off topic, but could you elaborate on the "audio streaming" part?
- surfingdino 2y ago
  Sure. Compared to traditional broadcast over airwaves or even a download to a device that can play audio without having to stream it from the server, audio streaming is the least efficient and the least convenient form of audio delivery. When you have a transmitter, people adding a thousand new radio receivers in the area does not increase your cost as a broadcaster, adding a thousand clients requires more bandwidth, and more infrastructure. I never understood why audio streaming became as popular as it did when better forms of distribution were available.

madsbuch 2y ago

> in applications requiring accuracy You have it right there. There is a large set of applications that does not require accuracy. These applications will benefit hugely from LLMs. Examples include recommender systems, knowledge extraction, transformation, etc. all in domains where accuracy does not matter too much. In particular, instruct aligned LLMs makes it very easy to integrate ad hoc machine learning into an application.

thaanpaa 2y ago

FOMO, probably. Just like any other tech bubble, really.

layer8 2y ago

> how is it possible that we see such incredible investments in LLMs? Profitability doesn’t require accuracy, generally speaking. Bullshitting often is a successful strategy, as politics and marketing amply demonstrate.

kikimora 2y ago

>My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? Opportunities like this happens once in 5-10 years when “the next big thing” are in the radar. Idea behind this investments is to bullshit it’s way to the Series B or IPO where original investors can exit. It is not about usefulness but about using momentum of the situation to extract money.

GOD_Over_Djinn 2y ago
I think you’ve really captured the essence of this phenomena in a remarkably succinct way. I do hope that business leaders eventually develop their own capabilities for independent creative thought, rather than being a bunch of mindless also-rans.

tbrownaw 2y ago

> What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. > I, as a laymen on the periphery of this phenomenon, am acutely aware that LLMs are not useful in applications requiring accuracy. They are not useful in isolation. They can be very useful as part of a larger process, especially if they particular way that you're using them has a low error rate. (And given a particular task you can in fact measure the error rate, or how often the generated bullshit happens by chance to (not) be true.) Most processes that involve steps done by humans have built-in pieces to catch and correct errors, because humans also make errors. If the error rate of the LLM component is lower than the error rate of the human it's replacing, you're fine. If it's higher but the cost of catching and fixing the extra errors is lower than the cost of the replaced human, you're still fine. (The person who you just sent the way of the buggy whip manufactures might be less fine, but that's Somebody Else's Problem.)

ffsm8 2y ago

> My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? LLMs are going to revolutionize the way the government, your employer and advertisers will spy on you. That's a pretty high value right there

tivert 2y ago

> My question - and I hope someone can address it in the discussion - how is it possible that we see such incredible investments in LLMs? The same reason we did for blockchain. It's a sexy new technology, with amazing demos and hype. People who want to be entrepreneurs but have no ideas of their own race to apply it everywhere because they think hitching their wagon to this horse could be their shot. Boring old companies wanting to seem hot. Lots of FOMO.

coffeebeqn 2y ago
What were the amazing demos for crypto? Hype- sure.
- tivert 2y ago
  Bitcoin itself.

AnimalMuppet 2y ago

> the models are in an important way indifferent to the truth of their outputs They're indifferent to the truth of their inputs, too. That's also a problem.

thefz 2y ago

> What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. It's a whoa moment for the general population. Look, the computer can understand and respond in natural language. I don't think there is other value in LLMs. Other applications of AI are very good, though.

lxgr 2y ago
They are also very good at translating between natural and structured/"computer" language. At a much higher rate than anything I've seen before in any algorithm, they "get" irony, sarcasm etc., when until a few years ago, I (as a non-linguist), assumed that any such solution to the "aboutness" problem would require solving AGI. That alone is worth a lot in a world which spends considerable resources on people that effectively work as translators between human and structured language. Besides that, I suspect that their existence is seen as a strong and remarkable hint that intelligence really might just be a quantitative phenomenon emergent from throwing a lot of compute at a lot of data, which at some point might become self-reinforcing. Whether that's true or not, and for better or worse, that's what people now seem to be set on doing.
- slow_typist 2y ago
  LLMs don’t get irony. That is not how they work. They simulate getting it.

TradingPlaces 2y ago

My view is that there is extrapolation going on. They look at the progression of GPT 2-3-4 over a relatively short number of years and are extrapolating to a near future where these things are much more capable. FOMO. But the history of AI is huge leaps from a technological innovation, followed by years of crawl, and all this extrapolation may be wrong.

1vuio0pswjnm7 2y ago

"Is it the promise that LLMs will replace employees?" If we accept the conclusions of the paper, perhaps LLMs can replace employees who are bullshitters. For example, Microsoft has announced layoffs claiming "AI wave" as the cause. Perhaps so-called "tech" companies like Microsoft employ bullshitters and "AI" can replace them. Employees who act as if they are right 100% of the time when in truth they are wrong at least 20% of the time. Why hire people who can only be relied on 80% of the time, and who will never do what it takes to reach 100%, if this "work" can be done by a computer.

fragmede 2y ago

If you're only looking at English generation, and focusing on the limitations, you're missing the bigger picture. The AI revolution is about the fact that we have now have the ability to produce ChatGPT level of thing, but for all of the kinds of data that companies have, not just English text. The idea isn't that it will replace the employees, but that the employees will be augmented by AI and be able to be way more productive. What executive hasn't wished they had 10x the people on a project at a fraction of the cost. The allure for a CTO isn't about LLMs, it's about resource management. staring at the hallucination problem is missing the forest for the trees. yes it's a problem, but holy shit, the thing generates essays as fast as the GPU can dot-product and matrix multiply. CTOs are buying into the idea that we've invented cars, when before we were just looking at a faster horse.

meiraleal 2y ago

> I, as a laymen on the periphery of this phenomenon, am acutely aware that LLMs are not useful in applications requiring accuracy. How accurate do you think humans are? 100%? 80%? 20%? If LLMs can be 20% as accurate as humans, the use cases are infinite. And it can only go up.

stemlord 2y ago

chatgpt and code completion tools have pretty much doubled my productivity... "write me this tedious function in c# for unity" could save me up to a couple minutes, "what are 5 makes and models of PoE switches used in industrial applications?" could save me up to an hour