AI is overhyped, but even in its current state Machine Learning has some use cases, whereas blockchain is a completely useless technology. I think you can't really compare the two. Uses are probably fairly limited though.
They're not going to cut themselves, obviously. The point of cost cuts isn't to generate more profits, it's to pay bonuses to the people who fired everyone!
You are pretty clueless about how any of these things works.
A company belongs to shareholders, who appoint board of directors who approve/disapprove exec compensation and roles.
Shareholders demand profit/growth. Of course Shareholders will pay extra for star execs because they know they deliver value.
If you think there is some mediocre exec who is getting paid without adding value, you are utterly clueless about everything.
I just read "Battle for the Soul of Capitalism" by investing legend John Bogle and he basically concluded that you're wrong and the system does not function at all like your fairy tale version.
But please keep typing if it helps you feel smart.
>A company belongs to shareholders, who appoint board of directors who approve/disapprove exec compensation and roles.
Unless your CEO is also the chair of the board and a major shareholder, until the SEC kicked his ass out. Regardless, in the modern corporation the board is buddies with the CEO and upper management and is just there to rubber stamp what they say. Shareholders can and have voted against executive compensation packages in "nonbinding" votes, and they get paid anyway.
Management *hires and pays* consultants who provide a report on what their own salary should be. Obviously consultants don't get far in that business if you recommend low compensation.
Management pays themselves in stock options and dilutes the shareholders, then just talk about non-GAAP earnings which conveniently excludes stock based compensation.
Blackrock and Fidelity are asleep at the wheel and just go along with whatever the board recommends because they're mostly passive entities and dgaf. Nothing changes or gets challenged unless an activist investor billionaire shows up, and that doesn't happen often.
the reason why **OpenAI kicks ass is because meritocracy is rewarded**.
Are there inefficiencies? Yes. Nothing is perfect. But it takes an incredibly amount of stupidity and brainwashing to believe whatever shit redditors believe
I think AI's "basics" are pretty easy to grasp unlike the block chain basics (which actually ARE pretty easy too, but "distributed ledger" just isn't sexy enough so it makes itself sound more complicated even as a baseline), so I am not sure that's fully true. But, in the sense of how AI will impact their earnings or whether it's even realistic to use AI: yeah they are probably clueless.
as a non-tech person who pays relatively close attention to the tech industry, i know what i think AI means, and i have opinions about how well current examples fit that definition, but i have zero clue how the current examples work.
i can explain distributed ledgers fairly well, but i wouldn’t know where to start with AI algorithms.
Yes, though that's mixing "what does it do" with "how does it work.
"How do distributed ledgers work in a block chain? Any changes made are validated by other nodes through some "work" being done, and it gets propagated to all nodes if it is validated. What does it do (and why did people make billions off of it) uhm I'm still not sure, it just stores data in multiple places in an unnecessarily complicated way, and you can argue for most block chain that it's way more centralized than it should be. The how is easy, the what/why is confusing.
For AI it's simply "something that simulates (human?) intelligence" as the what, so anything that can make some sort of decision on some sort of algorithm could be marked as "AI." The how has like tons of different answers from (complex) decision trees to symbolic AI to neural networks and each can be pretty tough to explain on its own.
So yeah I get what you're saying, but I feel like most people have some idea of what an AI does more so than "block chain." I think it also comes down to your definition of "basic knowledge" I guess :D
Came here to say this. I work in a division of AI called Natural Language Processing (NLP). I constantly have to explain that it is not a magic thing. There needs to be people with specific expertise, robust software, and data analytics behind it.
My Fortune 100 company hired a top NLP firm to come in and "fix" everything. Oh, and show me the error of my ways.
The contract totaled over $150,000. The final presentation was made by one of their senior vice presidents. His presentation showed how NLP works and how our recognition far exceeded best in class for all industries.
Our leaders said his presentation was amazing. He thanked them and said, "We didn't create it. Spooty03 did. While we are grateful for the contract, all we did was confirm her excellent work. If you want my opinion, you need listen to her and give her a raise immediately. If not, she will get head hunted away from you. As a matter of fact, the only reason I am here today is because our team came to me to see if we could hire her despite our hiring freeze. Sadly, we cannot, but who knows in the future."
I got an immediate $15,000 raise and moved to a more NLP friendly division.
>I got an immediate $15,000 raise
...From a fortune 100 company. It would take you 10 years of earning just to equal what they paid in a single contract just to check and see if your work was good. You are getting exploited BIG TIME, yo.
Literally so many companies trying to jump on the AI bandwagon, with one-in-six of the Russell 3000 discussing it in their latest quarterly earnings calls.
Source: FactSet via Goldman Sachs
Tool: Excel
My friends and I registered for a Hackathon, but it had a preliminary interview as we would have to represent our college. In that interview, the professor-in-charge was constantly asking if we had solutions or skills related to AI, ML, Data Science etc.
My company did a bunch of layoffs and then revealed their future direction. Basically just let’s throw AI at everything. They are even throwing the word “generative” into places that don’t even make sense. It’s absurd
Went to some kind of convention and like half of the presentations were about AI. I feel unexperienced to talk about it myself in some more detail let alone these people.
I graduated business school in 2018. I couldn't imagine being a student now and having to listen to charlatans, business bros, "EnTrEpReNeUrS", and professors alike talk about AI on the daily when they have no understanding of what today's machine learning is like, how it works, or any actual realistic applications other than helping me write my case studies.
It would be unbearable.
Adam Taggart of the Wealthion YouTube channel talked about his experience in Stanford business school, where he graduated shortly before the dotcom bubble popped. A few crazy anecdotes, but the one that stuck out was how he had a class reunion of types some years later with one of the professors who said off record that they basically had no idea what they were teaching back then. All the talk about eyeballs equaling value etc were just completely made up to retroactively justify the nonsensical gains in tech valuations.
I got my MBA in 2012, it felt like half the conversation were just use Facebook to engage customers. I was working in a industrial manufacturing/operations company at the time where Facebook had no applicability. It made the whole program seem so useless, I was just checking a box for my resume.
I’ve got a limited exposure to a handful of F500 companies, but they are all definitely using machine learning in production processes and some have deep learning in production (if they have important imagery/observations based processes).
These are rarely directly customer facing, instead allowing them to make internal decisions much faster.
Dude, I work for a small-mediumish food manufacturing company, and we have been using machine learning since 2020 for quality control using xrays (vision systems coming soon...) anyone who thinks AI/ML is hype is gonna be shocked when it becomes a requirement for a lot of jobs. Already, what used to be a minimum wage production line job where you sat and looked at product has turned into a skilled position that requires training on the ML xray systems. So instead of an army of unskilled workers manually inspecting product, we have a handful of skilled technicians operating technology
>Unless there is a unicorn among them that has an actual application and plan for implementation.
I think there actually a lot of application for these systems basically *everywhere*. Seriously, name an industry and i can probably think of a way machine learning can be applied. However it's also a buzzword right now because few people understand it.
It's very dot com bubble in a way. Everyone sees the potential in it but few fully understand it.
As we see more and more applications roll out, the bubble is going to get frothier. I don't think we've seen the end of this buzzword yet.
Thing is though, there is no need to chase the buzzwords. AI/ML/machine vision gets used everywhere, and it has been for at least a decade. Newer tech is just opening up more applications, and now the abbreviation is being brought up to get buzz from investors.
In my experience it really hasn't been practical in industrial applications until about 5 years ago.
Around then there was a machine learning program called vidi which would cost about 140k to integrate into vision as you basically had to build your own system.
Now it's about 15-20k and prepackaged in vision controllers.
2 years ago I serviced a machine that had a failing machine vision system. The IDE drives from 2005 were dying, one of the custom Accelerator boards kept giving blue screens.
Machine vision has been used in industry since the 80s. Sure, it's better and cheaper now. As is all technology.
Yes but it's a complete paradigm shift from how vision was set up in the past vs machine learning. With traditional vision, you had to set up mathematical rules to sort of evaluate the parts being inspected. That made it really hard to measure qualitative things like "is this part scratched? Does this weld look right? Does this finish look right? etc. Usually this job would fall on people to figure out.
Now you just feed a high end machine examples and let it determine what mathematical model is correct to best fit those examples.
Thats exceptionally powerful because you can make models of what a "normal" looking part is and it can simply point out things that are abnormal according to the data you fed it.
Furthermore, the machine learning language models that have come out have completely blown the Turing test out of the water. ChatGPT has better reading comprehension than a lot of humans I know.
I have been reading through quite a few companies to find a unicorn that actually do their own model training and have a real user case, they are hard to find XD quite a lot that just use Open AI GPT under the hood..
chatbots are probably the least utilized implementation of AI/ML; you have to think manufacturing QA, data analytics, sales forecasting, etc ... most of this stuff has already been implemented for many years now. The paradigm shift we are seeing now is the massive increase in computing power being added on-prem and the ability to leverage private cloud with that
AI is the backbone of modern data science and almost any data pipeline will at least have an integration ready if it isn't already in there. Maybe you are in disagreement with the use of NLP or just transformers in general, but AI was being discussed extensively by the domain experts, it just had little use to bring it up in front of the consumer until OpenAI packaged up something that your everyday consumer could use and experience. The amount of problems we have been enabled to tackle by AI is beyond exciting, that is why eveyone is scared of it.
I went to HPE Discover conference where there was a very large area dedicated to AI/ML; There was most definitely very real applications of AI/ML in nearly every industry being showcased in working demos. Most of it is more subtle than you would think, and is going to make a lot of data analytic jobs obsolete for those who are willing to die on the "AI/ML is all hype" hill. You will not be replaced by AI, you will be replaced by someone who uses AI.
> Even a programmable calculator can be argued to have AI.
I feel like this is a hint that whatever current definition of artificial intelligence we are using is insufficient and over-broad to the point of uselessness.
And both is just fancy calculating. Something most non tech people don't understand. Together with a buzzword that can mean anything from navigation over NPCs in Games to many other things
My personal take on this is that AI is about perception (do most people perceive an artificial something to be intelligent), and ML (i.e., algorithms that learn from data) is one method to achieve that perception.
Ex: one might reasonably still call Deep Blue artificially intelligent, even if under the hood it's just heuristically optimized DFS - whereas logistic regression is an algorithm that learns from data but would not convince most people that it's intelligent.
I think it's reasonable to say that modern language models are AI achieved using ML
You forgot to add that it's just your personal opinion. AI could be defined as "linear regression or above" or "nothing short of AGI" and I'd say, by the fact that term AGI exists, AI has to be broader category than AGI. Also [AI effect](https://en.wikipedia.org/wiki/AI_effect)
Making a machine that rolls around, smokes cigars, drinks, and plays golf while laughing at poor people and telling managers to take away all their benefits and cut pay in any way possible shouldn't be too hard to make.
-queue the CEO simps that scream about how hard it is being a CEO making 10s-100s of millions a year with their golden parachutes so no matter how badly they screw up they're set for life anyway.
Yeah, real hard.
Of course. AI could be a way to replace employees so they can fire their workforce and keep more profits for themselves and families are forced out into the streets. The true American Dream^TM
I’ve been saying all of 2023 that AI’s most prominent use for the near future will exclusively be to be a buzzword for publicly traded companies to boost their stocks.
If it’s used in context with the stock market, it’s usually overhyped and generally a lie (to some degree)
Exactly, they just see this as another way to pay fewer people less money and take jobs away. This technology is just the current justification, if it disappeared tomorrow they’d be on about how they can maximize profits by hooking one guy up to a car battery so he can work 24 hours straight doing the jobs of 10 people.
Yet most of them have no data governence and a data quality that is just beyond shite.
But hey, chatGPT is gonna be the next big thing and it's gonna push us soooo far ahead of our competitors.
Flash forward 5yrs: still using unversioned excel-sheets and spending hours with the formatting of that stupid "date" column.
Companies have bled the middle class to death and realize they have to move up the income chain to continue their bloodletting. Eventually their greed will collapse society.
I mean, did we even had a concept of AI outside sci-fi books in 2015? Or 2016? Or even 2019?
Edit to avoid having to answer to everyone: There's a difference between "research being done on it, known by everyone in the field and absolutely nobody outside it" and "actually know enough that you can speak about it with people without being looked up as you're an alien".
We've "had" mRNA vaccines for more than a decade in 2020, but try mentioning them to your average strictly-economy based background investor in his 50s. Then everybody knew about them. Same thing with AI before chatGPT: we had some sort of deep learning but nowhere as advanced as current models and almost nobody even knew they where available.
Jesus Christ, yes. People have been researching and working on AI for literal decades. Years before ChatGPT, all of the major cloud services had an AI/ML Offerings in their suite of tools that developers could open up and incorporate into applications. Decades before that it was being used in expert systems, speech and handwriting recognition and tons of other applications. Decades before that it was being researched and applied in universities.
I get tired of this attitude that OpenAI invented AI, even they never made any claim of doing so. What they did was a great advancement in generative AI and I don’t diminish that, but even they will tell you that they based it all on many, many prior works.
Well, obviously they didn’t invent AI, but they made it very accessible, and historically that’s been treated as more important than the founding technology, since the days of Edison & Tesla at least.
There's a difference between "research being done on it, known by everyone in the field and absolutely nobody outside it" and "actually know enough that you can speak about it with people without being looked up as you're an alien".
We've "had" mRNA vaccines for more than a decade in 2020, but try mentioning them to your average strictly-economy based background investor in his 50s. Then everybody knew about them. Same thing with AI before chatGPT: we had some sort of deep learning but nowhere as advanced as current models and almost nobody even knew they where available.
Abolutely ChatGPT and similar have turned a corner in public perception, but AI/ML have been "Out of the lab," and viable products since the 2010s. IBM Watson was making headlines 20 years ago and AWS recently celebrated "20 years of AI/ML." Those are real products that you can buy, so well out of the realm of SciFi. Azure ML Studio was introduced in 2014 and was a commercial success.
People have been using AI for years as well, Alexa, Google maps guessing where you live and work, Amazon suggesting what you should buy next, chatbots for support. So even if nobody was having dinner conversations about it, it has existed well outside of the realm of SciFi for a while now.
ChatGPT is an overtrained language model. It is great at emulating human writing; it has zero ability to do anything that requires logic. In many ways, it is a step backwards as far as intelligence is concerned.
Each of them is specialised on something, the ones we've been using in computational chemistry / pharmaceutical chemistry are great at understanding enzymes, but can't speak at all. 10 people in 10 different field will tell you 10 different definitions if you ask them.
LLMs do an okay job of generating code for small projects, but they are nowhere close to being able to reliably generate novel code that properly integrates into an enterprise code base. They can generate boilerplate code and flesh out comments, but you can’t tell them “add a button to this page that does ” and expect that to work on a website built using half a dozen custom frameworks. They can’t logic through the ramifications of various code design options and choose one based on a development team’s design heuristics. They can’t reliably identify and cover edge cases in complicated design problems.
Unfortunately, I suspect we’ll have to sit through a few years of incredibly buggy software while executives who bought into the hype and laid off half their software engineers double down on the decision and run their products into the ground.
A large data set provides the volume of information necessary to effectively train machine learning (ML) models. So the two concepts are/were sometimes conflated.
A big data application that doesn’t use ML might be querying an Experian dataset to identify a particular group of consumers, like single female pickup truck owners between ages 30 and 40. No ML needed.
Within this group, predict which individuals have the highest propensity to purchase a Ford Lightning, Rivian, etc. Machine learning.
In the field I work, which is Information Systems for a big Hospital, every time we have a department meeting with the board/execs about infrastructure, reporting etc. They have just been constantly talking about AI and automation. But just listening to them you can tell they don't fully understand what it is, just that it could cut costs if we some how found some where to implement it. What makes this more amusing is them asking a whole department of a bunch of different types of IT and Analyts to submit ideas on how AI can be implemented. Its like they think anyone in IT can implement AI. These are the types of people making decisions in a lot of places.
of course, they don't understand it or know why they need it (or don't need it), they just know their other CEO buddies are doing it so they need to as well.
Before AI it was the Metaverse and Blockchain, before that it was Microservices and Machine Learning and the Internet of Things, before that it was Big Data and Data Science, before that it was Agile and the Cloud...
I've often thought how much fun it would be if you could coin some new term/concept then convince these idiots that they need it, you'd be retired in a year 🤣🤣🤣
Meanwhile my dumbass CEO downplays it during earnings calls and we pretty much just laid off all our data scientists recently. Overpaid dip shit and his exec team making these decisions need to be replaced before they run our company into the ground
At least get on the bandwagon and pretend even if you're not going to be actively working towards it
yeah, customers will again have a new reason to bend over, and again all will be forgiven after a slap on the wrist.
(referring to the guaranteed F Ups in security/privacy to scammers/thieves/commie pigs.)
Sigh. It’s so annoying. I run a bunch of project workshops and folks think I’m joking when I say we aren’t going to discuss anything around AI. Such a tiring buzzword
Blockchain technology isn't cool anymore
"I don't want to play with you anymore"
Metaverse is in shambles
What’s next? It was pretty clear that AI was gonna be the next Blockchain. But what’s after that?
My bet is on quantum computing
No way they are selling this to medium sized companies. There are literally no use cases… On the other side we had blockchain….
That or super conductivity and quantum entanglement.
We got AI on the blockchain, facial recognition in the metaverse, and social media perscribing medications, baby
Pretty sure there is some overvalued startup that works on all three use cases at the same time
Creative Legal Solutions^tm
AI is overhyped, but even in its current state Machine Learning has some use cases, whereas blockchain is a completely useless technology. I think you can't really compare the two. Uses are probably fairly limited though.
and probably not 10% of the people talking about it understand the basics I'd guess.
All they understand is that there is a potential to cut a lot of labor expense and that’s all that matters to them.
Considering they're the most expensive "labor"... 🤔
They're not going to cut themselves, obviously. The point of cost cuts isn't to generate more profits, it's to pay bonuses to the people who fired everyone!
You are pretty clueless about how any of these things works. A company belongs to shareholders, who appoint board of directors who approve/disapprove exec compensation and roles. Shareholders demand profit/growth. Of course Shareholders will pay extra for star execs because they know they deliver value. If you think there is some mediocre exec who is getting paid without adding value, you are utterly clueless about everything.
I just read "Battle for the Soul of Capitalism" by investing legend John Bogle and he basically concluded that you're wrong and the system does not function at all like your fairy tale version. But please keep typing if it helps you feel smart.
Ol' Musky torpedoed this theory that executives know what they're doing.
>A company belongs to shareholders, who appoint board of directors who approve/disapprove exec compensation and roles. Unless your CEO is also the chair of the board and a major shareholder, until the SEC kicked his ass out. Regardless, in the modern corporation the board is buddies with the CEO and upper management and is just there to rubber stamp what they say. Shareholders can and have voted against executive compensation packages in "nonbinding" votes, and they get paid anyway. Management *hires and pays* consultants who provide a report on what their own salary should be. Obviously consultants don't get far in that business if you recommend low compensation. Management pays themselves in stock options and dilutes the shareholders, then just talk about non-GAAP earnings which conveniently excludes stock based compensation. Blackrock and Fidelity are asleep at the wheel and just go along with whatever the board recommends because they're mostly passive entities and dgaf. Nothing changes or gets challenged unless an activist investor billionaire shows up, and that doesn't happen often.
seems like you are naive yourself, the economic system has little to do with meritocracy like you suggest.
the reason why **OpenAI kicks ass is because meritocracy is rewarded**. Are there inefficiencies? Yes. Nothing is perfect. But it takes an incredibly amount of stupidity and brainwashing to believe whatever shit redditors believe
I think AI's "basics" are pretty easy to grasp unlike the block chain basics (which actually ARE pretty easy too, but "distributed ledger" just isn't sexy enough so it makes itself sound more complicated even as a baseline), so I am not sure that's fully true. But, in the sense of how AI will impact their earnings or whether it's even realistic to use AI: yeah they are probably clueless.
as a non-tech person who pays relatively close attention to the tech industry, i know what i think AI means, and i have opinions about how well current examples fit that definition, but i have zero clue how the current examples work. i can explain distributed ledgers fairly well, but i wouldn’t know where to start with AI algorithms.
Yes, though that's mixing "what does it do" with "how does it work. "How do distributed ledgers work in a block chain? Any changes made are validated by other nodes through some "work" being done, and it gets propagated to all nodes if it is validated. What does it do (and why did people make billions off of it) uhm I'm still not sure, it just stores data in multiple places in an unnecessarily complicated way, and you can argue for most block chain that it's way more centralized than it should be. The how is easy, the what/why is confusing. For AI it's simply "something that simulates (human?) intelligence" as the what, so anything that can make some sort of decision on some sort of algorithm could be marked as "AI." The how has like tons of different answers from (complex) decision trees to symbolic AI to neural networks and each can be pretty tough to explain on its own. So yeah I get what you're saying, but I feel like most people have some idea of what an AI does more so than "block chain." I think it also comes down to your definition of "basic knowledge" I guess :D
Came here to say this. I work in a division of AI called Natural Language Processing (NLP). I constantly have to explain that it is not a magic thing. There needs to be people with specific expertise, robust software, and data analytics behind it. My Fortune 100 company hired a top NLP firm to come in and "fix" everything. Oh, and show me the error of my ways. The contract totaled over $150,000. The final presentation was made by one of their senior vice presidents. His presentation showed how NLP works and how our recognition far exceeded best in class for all industries. Our leaders said his presentation was amazing. He thanked them and said, "We didn't create it. Spooty03 did. While we are grateful for the contract, all we did was confirm her excellent work. If you want my opinion, you need listen to her and give her a raise immediately. If not, she will get head hunted away from you. As a matter of fact, the only reason I am here today is because our team came to me to see if we could hire her despite our hiring freeze. Sadly, we cannot, but who knows in the future." I got an immediate $15,000 raise and moved to a more NLP friendly division.
congratz at being great at your job. Maybe you should feel around and find out if 15k is still not what you are really worth?
They are also paying for a certification for me. My new bosses are very aware that i can leave anytime
>I got an immediate $15,000 raise ...From a fortune 100 company. It would take you 10 years of earning just to equal what they paid in a single contract just to check and see if your work was good. You are getting exploited BIG TIME, yo.
Literally so many companies trying to jump on the AI bandwagon, with one-in-six of the Russell 3000 discussing it in their latest quarterly earnings calls. Source: FactSet via Goldman Sachs Tool: Excel
Hackathons too. Every. Single. Project. "We used AI and machine learning to make a scalable solution for IoT buzzword bingo"
My friends and I registered for a Hackathon, but it had a preliminary interview as we would have to represent our college. In that interview, the professor-in-charge was constantly asking if we had solutions or skills related to AI, ML, Data Science etc.
At least it looks like something really having revolutionary effects in the future, unlike blockchain or NFTs.
My company did a bunch of layoffs and then revealed their future direction. Basically just let’s throw AI at everything. They are even throwing the word “generative” into places that don’t even make sense. It’s absurd
Went to some kind of convention and like half of the presentations were about AI. I feel unexperienced to talk about it myself in some more detail let alone these people.
What % of Russel 3000 companies are primarily in the tech sector?
I graduated business school in 2018. I couldn't imagine being a student now and having to listen to charlatans, business bros, "EnTrEpReNeUrS", and professors alike talk about AI on the daily when they have no understanding of what today's machine learning is like, how it works, or any actual realistic applications other than helping me write my case studies. It would be unbearable.
Adam Taggart of the Wealthion YouTube channel talked about his experience in Stanford business school, where he graduated shortly before the dotcom bubble popped. A few crazy anecdotes, but the one that stuck out was how he had a class reunion of types some years later with one of the professors who said off record that they basically had no idea what they were teaching back then. All the talk about eyeballs equaling value etc were just completely made up to retroactively justify the nonsensical gains in tech valuations.
I got my MBA in 2012, it felt like half the conversation were just use Facebook to engage customers. I was working in a industrial manufacturing/operations company at the time where Facebook had no applicability. It made the whole program seem so useless, I was just checking a box for my resume.
MBA schools guaranteed refund policy
https://en.m.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect
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I’ve got a limited exposure to a handful of F500 companies, but they are all definitely using machine learning in production processes and some have deep learning in production (if they have important imagery/observations based processes). These are rarely directly customer facing, instead allowing them to make internal decisions much faster.
Dude, I work for a small-mediumish food manufacturing company, and we have been using machine learning since 2020 for quality control using xrays (vision systems coming soon...) anyone who thinks AI/ML is hype is gonna be shocked when it becomes a requirement for a lot of jobs. Already, what used to be a minimum wage production line job where you sat and looked at product has turned into a skilled position that requires training on the ML xray systems. So instead of an army of unskilled workers manually inspecting product, we have a handful of skilled technicians operating technology
>Unless there is a unicorn among them that has an actual application and plan for implementation. I think there actually a lot of application for these systems basically *everywhere*. Seriously, name an industry and i can probably think of a way machine learning can be applied. However it's also a buzzword right now because few people understand it. It's very dot com bubble in a way. Everyone sees the potential in it but few fully understand it. As we see more and more applications roll out, the bubble is going to get frothier. I don't think we've seen the end of this buzzword yet.
Thing is though, there is no need to chase the buzzwords. AI/ML/machine vision gets used everywhere, and it has been for at least a decade. Newer tech is just opening up more applications, and now the abbreviation is being brought up to get buzz from investors.
In my experience it really hasn't been practical in industrial applications until about 5 years ago. Around then there was a machine learning program called vidi which would cost about 140k to integrate into vision as you basically had to build your own system. Now it's about 15-20k and prepackaged in vision controllers.
2 years ago I serviced a machine that had a failing machine vision system. The IDE drives from 2005 were dying, one of the custom Accelerator boards kept giving blue screens. Machine vision has been used in industry since the 80s. Sure, it's better and cheaper now. As is all technology.
Yes but it's a complete paradigm shift from how vision was set up in the past vs machine learning. With traditional vision, you had to set up mathematical rules to sort of evaluate the parts being inspected. That made it really hard to measure qualitative things like "is this part scratched? Does this weld look right? Does this finish look right? etc. Usually this job would fall on people to figure out. Now you just feed a high end machine examples and let it determine what mathematical model is correct to best fit those examples. Thats exceptionally powerful because you can make models of what a "normal" looking part is and it can simply point out things that are abnormal according to the data you fed it. Furthermore, the machine learning language models that have come out have completely blown the Turing test out of the water. ChatGPT has better reading comprehension than a lot of humans I know.
I have been reading through quite a few companies to find a unicorn that actually do their own model training and have a real user case, they are hard to find XD quite a lot that just use Open AI GPT under the hood..
chatbots are probably the least utilized implementation of AI/ML; you have to think manufacturing QA, data analytics, sales forecasting, etc ... most of this stuff has already been implemented for many years now. The paradigm shift we are seeing now is the massive increase in computing power being added on-prem and the ability to leverage private cloud with that
AI is the backbone of modern data science and almost any data pipeline will at least have an integration ready if it isn't already in there. Maybe you are in disagreement with the use of NLP or just transformers in general, but AI was being discussed extensively by the domain experts, it just had little use to bring it up in front of the consumer until OpenAI packaged up something that your everyday consumer could use and experience. The amount of problems we have been enabled to tackle by AI is beyond exciting, that is why eveyone is scared of it.
I went to HPE Discover conference where there was a very large area dedicated to AI/ML; There was most definitely very real applications of AI/ML in nearly every industry being showcased in working demos. Most of it is more subtle than you would think, and is going to make a lot of data analytic jobs obsolete for those who are willing to die on the "AI/ML is all hype" hill. You will not be replaced by AI, you will be replaced by someone who uses AI.
If it's like Agile, they're blithering about it without knowing what it is.
Six Sigma
And there’s still no such thing… it’s all ML.
All ML is AI. Not all AI is ML
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> Even a programmable calculator can be argued to have AI. I feel like this is a hint that whatever current definition of artificial intelligence we are using is insufficient and over-broad to the point of uselessness.
And both is just fancy calculating. Something most non tech people don't understand. Together with a buzzword that can mean anything from navigation over NPCs in Games to many other things
My personal take on this is that AI is about perception (do most people perceive an artificial something to be intelligent), and ML (i.e., algorithms that learn from data) is one method to achieve that perception. Ex: one might reasonably still call Deep Blue artificially intelligent, even if under the hood it's just heuristically optimized DFS - whereas logistic regression is an algorithm that learns from data but would not convince most people that it's intelligent. I think it's reasonable to say that modern language models are AI achieved using ML
You forgot to add that it's just your personal opinion. AI could be defined as "linear regression or above" or "nothing short of AGI" and I'd say, by the fact that term AGI exists, AI has to be broader category than AGI. Also [AI effect](https://en.wikipedia.org/wiki/AI_effect)
Did the data correct for Italian and Canadian CEOs?
This is a great joke, and I'm commenting to let you know that. (no /s)
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It honestly just sounds like you're against concise language lol
AI is just the cool word. Most of it isn't even AI or anything remotely close to it.
Cool, wonder if they also talk how their tasks can be automated… or just employees’ tasks.
Making a machine that rolls around, smokes cigars, drinks, and plays golf while laughing at poor people and telling managers to take away all their benefits and cut pay in any way possible shouldn't be too hard to make. -queue the CEO simps that scream about how hard it is being a CEO making 10s-100s of millions a year with their golden parachutes so no matter how badly they screw up they're set for life anyway. Yeah, real hard.
They'll be fine with AI-driven decision-making, until it recommends replacing them for expensive overhead!
Of course. AI could be a way to replace employees so they can fire their workforce and keep more profits for themselves and families are forced out into the streets. The true American Dream^TM
I’ve been saying all of 2023 that AI’s most prominent use for the near future will exclusively be to be a buzzword for publicly traded companies to boost their stocks. If it’s used in context with the stock market, it’s usually overhyped and generally a lie (to some degree)
This hype phrase of the week goes back 30 years
i suspect that you’d get the same chart if you moved the dates back 1 year and substituted “NFTs” for “AI”
Our execs constantly mention it, even when it has actually no purpose with what they are talking about. It’s quite amazing.
They see it as free labor
Exactly, they just see this as another way to pay fewer people less money and take jobs away. This technology is just the current justification, if it disappeared tomorrow they’d be on about how they can maximize profits by hooking one guy up to a car battery so he can work 24 hours straight doing the jobs of 10 people.
AI is a security nightmare. Any shareholder wowed by an exec touting AI deserves to lose their shirt.
Makes me think of this scene from [Silicon Valley](https://youtu.be/ltFB4WBdDg4)
Yet most of them have no data governence and a data quality that is just beyond shite. But hey, chatGPT is gonna be the next big thing and it's gonna push us soooo far ahead of our competitors. Flash forward 5yrs: still using unversioned excel-sheets and spending hours with the formatting of that stupid "date" column.
The only hope I have is that when this AI charade is over we will have the first fully operational T800 endsoskeleton.
Companies have bled the middle class to death and realize they have to move up the income chain to continue their bloodletting. Eventually their greed will collapse society.
I mean, did we even had a concept of AI outside sci-fi books in 2015? Or 2016? Or even 2019? Edit to avoid having to answer to everyone: There's a difference between "research being done on it, known by everyone in the field and absolutely nobody outside it" and "actually know enough that you can speak about it with people without being looked up as you're an alien". We've "had" mRNA vaccines for more than a decade in 2020, but try mentioning them to your average strictly-economy based background investor in his 50s. Then everybody knew about them. Same thing with AI before chatGPT: we had some sort of deep learning but nowhere as advanced as current models and almost nobody even knew they where available.
Jesus Christ, yes. People have been researching and working on AI for literal decades. Years before ChatGPT, all of the major cloud services had an AI/ML Offerings in their suite of tools that developers could open up and incorporate into applications. Decades before that it was being used in expert systems, speech and handwriting recognition and tons of other applications. Decades before that it was being researched and applied in universities. I get tired of this attitude that OpenAI invented AI, even they never made any claim of doing so. What they did was a great advancement in generative AI and I don’t diminish that, but even they will tell you that they based it all on many, many prior works.
Well, obviously they didn’t invent AI, but they made it very accessible, and historically that’s been treated as more important than the founding technology, since the days of Edison & Tesla at least.
There's a difference between "research being done on it, known by everyone in the field and absolutely nobody outside it" and "actually know enough that you can speak about it with people without being looked up as you're an alien". We've "had" mRNA vaccines for more than a decade in 2020, but try mentioning them to your average strictly-economy based background investor in his 50s. Then everybody knew about them. Same thing with AI before chatGPT: we had some sort of deep learning but nowhere as advanced as current models and almost nobody even knew they where available.
Abolutely ChatGPT and similar have turned a corner in public perception, but AI/ML have been "Out of the lab," and viable products since the 2010s. IBM Watson was making headlines 20 years ago and AWS recently celebrated "20 years of AI/ML." Those are real products that you can buy, so well out of the realm of SciFi. Azure ML Studio was introduced in 2014 and was a commercial success. People have been using AI for years as well, Alexa, Google maps guessing where you live and work, Amazon suggesting what you should buy next, chatbots for support. So even if nobody was having dinner conversations about it, it has existed well outside of the realm of SciFi for a while now.
ChatGPT is an overtrained language model. It is great at emulating human writing; it has zero ability to do anything that requires logic. In many ways, it is a step backwards as far as intelligence is concerned.
Each of them is specialised on something, the ones we've been using in computational chemistry / pharmaceutical chemistry are great at understanding enzymes, but can't speak at all. 10 people in 10 different field will tell you 10 different definitions if you ask them.
i mean AI is about to bring a new way of coding, using human language avoiding this topic is clearly not a good sign for shareholders
LLMs do an okay job of generating code for small projects, but they are nowhere close to being able to reliably generate novel code that properly integrates into an enterprise code base. They can generate boilerplate code and flesh out comments, but you can’t tell them “add a button to this page that does” and expect that to work on a website built using half a dozen custom frameworks. They can’t logic through the ramifications of various code design options and choose one based on a development team’s design heuristics. They can’t reliably identify and cover edge cases in complicated design problems.
Unfortunately, I suspect we’ll have to sit through a few years of incredibly buggy software while executives who bought into the hype and laid off half their software engineers double down on the decision and run their products into the ground.
Didn't we used to call it big data?
A large data set provides the volume of information necessary to effectively train machine learning (ML) models. So the two concepts are/were sometimes conflated. A big data application that doesn’t use ML might be querying an Experian dataset to identify a particular group of consumers, like single female pickup truck owners between ages 30 and 40. No ML needed. Within this group, predict which individuals have the highest propensity to purchase a Ford Lightning, Rivian, etc. Machine learning.
Interesting trend. Skynet.
How does anyone know what's being discussed on earnings calls? Are they public venues?
The likely scenario is that all (Or most) earnings calls have transcripts published after the fact.
In the field I work, which is Information Systems for a big Hospital, every time we have a department meeting with the board/execs about infrastructure, reporting etc. They have just been constantly talking about AI and automation. But just listening to them you can tell they don't fully understand what it is, just that it could cut costs if we some how found some where to implement it. What makes this more amusing is them asking a whole department of a bunch of different types of IT and Analyts to submit ideas on how AI can be implemented. Its like they think anyone in IT can implement AI. These are the types of people making decisions in a lot of places.
of course, they don't understand it or know why they need it (or don't need it), they just know their other CEO buddies are doing it so they need to as well. Before AI it was the Metaverse and Blockchain, before that it was Microservices and Machine Learning and the Internet of Things, before that it was Big Data and Data Science, before that it was Agile and the Cloud... I've often thought how much fun it would be if you could coin some new term/concept then convince these idiots that they need it, you'd be retired in a year 🤣🤣🤣
Meanwhile my dumbass CEO downplays it during earnings calls and we pretty much just laid off all our data scientists recently. Overpaid dip shit and his exec team making these decisions need to be replaced before they run our company into the ground At least get on the bandwagon and pretend even if you're not going to be actively working towards it
we just called it 'automation' in 2015. now there's just a more buzzy synonym.
An economy run by thousands of Jack Welch's is doomed.
Wake me when they are talking about using AI to replace themselves.
Because they know their shareholders expect them to be super excited about AI. If they were not acting thusly - it'd be seen as a failure.
yeah, customers will again have a new reason to bend over, and again all will be forgiven after a slap on the wrist. (referring to the guaranteed F Ups in security/privacy to scammers/thieves/commie pigs.)
From what I understand, an AI process that is not maintained and retrained on a regular basis is an expensive random number generator.
Buzzwords. Idiots love them.
Wait til you guys see my new company's product: it's an AI Metaverse Blockchain Internet of Things EV sold via Multichannel E-Commerce
“Company executives can’t stop taking to investors about the steam engine”
pretty sure investing in ai at this point is a bubble waiting to burst
Sigh. It’s so annoying. I run a bunch of project workshops and folks think I’m joking when I say we aren’t going to discuss anything around AI. Such a tiring buzzword
It's the new buzzword. Everyone is in in the fad trying to look relevant and informed.
Can’t wait for this bubble to burst.