I’ve tried several types of artificial intelligence including Gemini, Microsoft co-pilot, chat GPT. A lot of the times I ask them questions and they get everything wrong. If artificial intelligence doesn’t work why are they trying to make us all use it?
Cause it’s cool
Not to me. If you like it, that’s fine.
Perhaps your personal bias is clouding your judgement a bit here. You don’t seem very open minded about it. You’ve already made up your mind.
Probably but I’m far from the only one.
Investors are dumb. It’s a hot new tech that looks convincing (since LLMs are designed specifically to appear correct, not be correct), so anything with that buzzword gets a ton of money thrown at it. The same phenomenon has occurred with blockchain, big data, even the World Wide Web. After each bubble bursts, some residue remains that actually might have some value.
I can see that. That guy over there has the new shiny toy. I want a new shiny toy. Give me a new shiny toy.
Generative AI has allowed us to do some things that we could not do before. A lot of people very foolishly took that to mean it would let us do everything we couldn’t do before.
That’s because the PR department keeps telling us that it’s the best things since sliced bread.
I second this, very consice and accurate
The last big fall in the price of bitcoin, in December '22 was caused by a shift in the dynamics of mining where it became more expensive to mine new btc than what the coin was actually worth. Not only did this plunge the price of crypto it also demolished demand for expensive graphics chips which are repurposed to run the process-heavy complex math used in mining. Cheaper chips, cascading demand and server space that was dedicated to mining related activities threatened to wipe out profit margins in multiple tech sectors.
6 months later, Chat GPT is tolled out by Open AI. The previous limitations on processing capabilities were gone, server space was cheap and the tech was abundant. So all these tech sectors at risk of losing their ass in an overproduction driven recession, now had a way to pump the price of their services and this was to pump AI.
Additionally around this time the world was recovering from covid lockdowns. Increased demand for online services was dwindling (exacerbating the other crisis outlined above) as people were returning to work and spending more time being social IRL rather than using services. Companies had hired lots of new workers: programmers, tech infrastructure workers, etc., yo meet the exploding demand during covid. Now they had too many workers and their profits were being threatened.
The Federal reserve had raised interest rates to stifle continued hiring of new employees. The solution that the fed had come up with in order to stifle inflation was to encourage laying off workers end masse – what Marxists might call restoring the reserve army of labor, or relative surplus population – which was substantially depleted during the pandemic. But business owners were reluctant to do this, the tight labor market of the last few years had made business owners and managers skittish about letting people go.
A basic principle at play here, is that new technology is introduced for two reasons only: to sell as a new commodity and (what we are principally concerned with) replacing workers with machines. Another basic principle is that the capitalist system has to have a certain percentage of its population unemployed and hyper exploited in order to keep wages low.
So there was a confluence of incentives here. 1. Inexpensive server space and chips which producers were eager to restore to profitability (or else face drastic consequences) 2. A need to lay off workers in order to stop inflation 3. Incentives for businesses to do so.
Laying off relatively highly paid technical/intellectual labor is a low hanging fruit in this whole equation, and the roll out of AI did just that. Hundreds of thousands of highly paid workers were laid off across a variety of sectors, assured that AI would create so much more efficiency and cut out the need for so many of these workers. So they rolled out this garbage tech that doesn’t work, but everyone in the industry, the media, the government needs it to work, or else they face a massive economic crisis, which had already started with inflation.
At the end of the day its just a massive grift, pushed out to compensate for excessive overproduction driven by another massive grift (cryptocurrency) combined with economic troubles that arose from an insufficient government response to a pandemic that killed millions of people; and rather than take other measures to stifle inflation our leaders in global finance decided to shunt the consequences onto workers, as always. The excuse given was AI, which is nothing more than a predictive text algorithm attached to a massive database created by exploited workers overseas and stolen IPs, and a fuck load of processing power.
I hope someday we can come up with an economic system that is not based purely on profit and the exploitation of human beings. But I don’t know that I’ll live long enough to see it.
Well remember that the shifts that can happen in material conditions and consciousness can happen very quickly. We can’t decide when that is, but we can prepare and build trust until it does occur. Hard to imagine what it would take in the west to see an overthrow of capitalism, all we can do is throw our weight behind where it will have the most effect, hopefully where our talents reside also! Stay optimistic, despite even evidence to the contrary. For the capitalists, its better to believe that the end of the world is coming than to believe a new world is possible. So if nothing else lets give em hell
I can’t tell you how many times I’ve had this exact thought. 😕
Are you an economist or business professor IRL? Because that was an amazing answer!
No actually I’m mostly self educated. I’m just a tech worker who studies history, social theory and economics, but also does some political organizing. So take it with a grain of salt if you must.
Glad you got something from it, I appreciate the compliment!
That is a very pessimistic and causal explanation, but you’ve got the push right. It’s marketing that pushes I though, not necessarily tech. AI, as we currently see it in use, is a very neat technological development. Even more so it is a scientific development, because it isn’t just some software, it is a intricate mathematical model. It is such a complex model, that we actually have study it how it even works,because we don’t now the finer details.
It is not a replacement for office workers, it is not the robot revolution and it is not godlike. It is just a mathematical model on a previously unimaginable scale.
“Pessimistic and casual”? You’re gonna make me self conscious.
I’m an AI skeptic. Its too energy hungry and its not doing anything except scraping massive amounts of consumer data. No its not going to replace workers (because it doesn’t work), but then again countless workers were already laid off so it already served its purpose there. Doesn’t have to replace them, just has to purge them but in a systematic way, such that the Fed called for when they started raising interest rates.
Are you an AI Scientist/engineer? If so I’d love to hear more about your work. I’m in tech myself but def not on the bleeding edge of AI.
Machine learning has many valid applications, and there are some fields genuinely utilizing ML tools to make leaps and bounds in advancements.
LLMs, aka bullshit generators, which is where a huge majority of corporate AI investment has gone in this latest craze, is one of the poorest. Not to mention the steaming pile of ethical issues with training data.
Very nice writeup. My only critique is the need to “lay off workers to stop inflation.” I have no doubt that some (many?) managers etc… believed that to be the case, but there’s rampant evidence that the spike of inflation we’ve seen over this period was largely due to corporate greed hiking prices, not due to increased costs from hiring too many workers.
Exactly! the two things are the same phenomenon expressing in two different ways! This is exactly why this is such a mindfuck.
Follow my logic: in the usa by 2022, covid19 had killed over a million people. When you compare this to the total unemployed in the US, that’s not just the governments padded numbers but adding together all the people in prisons, people who stopped looking for work, etc., those covid deaths were about 12% of that unemployed “surplus” population. Again, the system needs a certain number of people to be unemployed, over a million people died, which means over a million “jobs” (this includes employed and unemployed positions within the entire workforce.) At the time the media was calling it “the great resignation,” where employees were just going out and getting better jobs. But where did these jobs come from? Can you really just go out and get a better job any time you want? Of course not. Try searching for a job now, good fucking luck.
Seriously, google “reserve army of labor” if you haven’t already, it explains everything. So as the labor market tightens, consumption increases. People got a better job and can fix their credit up in a few months and get a loan on a car maybe for the first time. People are walking out of the grocery store with more food, or going out to eat more. Retailers notice this and raise prices in response to increased spending. this is a phenomena that Marx wrote about in value price and profit, which I might mention again.
So why were prices going up? Larry Summers gets in front of Jon Stewart and says that increase in spending equals increase in demand, when demand challenges supply then prices go up! Which is what we are generally taught. Except Marx proved that this was not the case, that inflation really was just retailers raising prices due to increase in consumer spending. Its a bit of economic slight of hand that I could explain if you want but for now I’m already long.
The federal reserve says that inflation (which is like you said, mostly driven by companies raising prices to squeeze consumers, and this is proven by the way the fed responds) is out of control, so therefore they are raising interest rates. The way this will control inflation is by making it harder and more expensive for companies to get money for large capital investments. This is all to squeeze the companies to stop hiring (since their p&l is negatively affected) and eliminate excess staff. But the companies are reluctant to let people go/stop hiring because of what they just experienced with a “tight” labor market. They have the incentives or pressures, but they need an excuse, they need a justification. Enter automation with ai. Finally the automation revolution that the media has been threatening workers with for decades is here and sorry can’t halt progress you see (Ned Ludd did nothing wrong.)
Except it isnt all that. In the mean time the economy has adjusted to the depleted reserve population, the corpos were given everything they wanted or needed in order to continue to profit after the death of millions, and a new grift industry has grown up and attracted all this funding and following and clout. Didn’t even have to lose that many jobs, just a bunch of high paid ones. Except interest rates are still elevated so the fed is continuing to keep that pressure on the labor market. Anyway, there’s all of these cascading effects, from systems interacting with each other; therefore its more useful to understand the relation between phenomenon than it often is to try and understand that phenomena on its own.
So you’re right, it was corporate policy, but it isn’t greed necessarily. Definitely greed adjacent though, its like systematic greed. There are incentives and disincentives present within the system. Karl Marx was able to write about the causes of inflation 150 years ago, and they were using the same faulty excuses then. That’s also why the fed decided to raise interest rates, they understood what the problem was, and the fix is and always has been to throw people into unemployment. The system is predictable, but it isn’t rational.
We’ve already established that language models just make shit up. There is no need to demonstrate. Bad bot!
Excuse me? Are you calling me a bot?
I remember learning about Turing tests to determine whether speech was coming from a machine. Its ironic that in practice its much more common for people to not be able to recognize even a real person.
It’s just that I rarely see a real person be so confidently wrong.
Care to elaborate?
A dumb person thinks AI is really smart, because they just listen to anyone that answers confidentially
And no matter what, AI is going to give its answer like it’s is 100% definitely the truth.
That’s why there’s such a large crossover with AI and crypto, the same people fall for everything.
There’s new supporting evidence for Penrose’s theory that natural intelligence involves just an absolute shit ton of quantum interactions, because we just found out how the body can create an environment where quantom super position can not only be achieved, but incredibly simply.
AI got a boost because we didn’t really (still dont) understand consciousness. Tech bro’s convinced investors that neurons were what mattered, and made predictions for when that amount of neurons can be simulated.
But if it include billions of molecules in quantum superposition, we’re not getting there in our lifetimes. But there’s a lot of money sunk in to it already, so there’s a lot of money to lose if people suddenly get realistic about what it takes to make a real artificial intelligence.
So they’re using the sunk cost logical fallacy? Gee that’s intelligent.
The microtubules creating an environment that can sustain quantum super position just came out like a month ago.
In all honesty the tech bros probably don’t even know yet, or understands it means human level AI speculation has essentially been disproven as happening anytime remotely soon.
But I’m assuming when they do, they’ll just ignore it and double down to maintain share prices.
It’s also possible it all crashes and billions of dollars disappear.
Microtubules have been pushed for decades without any proof. The latest paper wasn’t evidence but unsupported speculation.
But more importantly the physics of computation that creates intelligence has absolutely nothing to do with understanding intelligence. Even if quantum effects are relevant ( which is extremely unlikely given the warm and moving environment inside the brain), it doesn’t answer anything about how humans are intelligent.
Penrose used Quantum Mechanics as a “God in the Gaps” explanation. That worked 40 years ago but today we have working quantum computers but no human intelligence.
So the senator from Alaska was right? The internet is all a bunch of tubes?
Rich assholes have spent a ton of money on it and they need to manufacture reasons why that wasn’t a waste.
IIRC When ChatGPT was first announced I believe the hype was because it was the first real usable interface a layman could interact with using normal language and have an intelligible response from the software. Normally to talk with computers we use their language (programming) but this allowed plain language speakers to interact and get it to do things with simple language in a more pervasive way than something like Siri for instance.
This then got over hyped and over promised to people with dollars in their eyes at the thought of large savings from labor reduction and capabilities far greater than it had. They were sold a product that has no real “product” as it’s something most people would prefer to interact with on their own terms when needed, like any tool. That’s really hard to sell and make people believe they need it. So they doubled down with the promise it would be so much better down the road. And, having spent an ungodly amount into it already, they have that sunken cost fallacy and keep doubling down.
This is my personal take and understanding of what’s happening. Though there’s probably more nuances, like staying ahead of the competition that also fell for the same promises.
If artificial intelligence doesn’t work why are they trying to make us all use it?
But it does work. It’s not obviously flawless but it’s orders of magnitude better than it was 10 years ago and it’ll only improve from here. Artificial intelligence is a spectrum. It’s not like we succesfully created it and it ended up sucking. No, it’s like the first cars; they suck compared to what we have now but it’s a huge leap from what we had before.
I think the main issue here is that the common folk has unrealistic expectations about what AI should be. They’re imagining what the “final product” would be like and then comparing our current systems to that. Ofcourse from that perspective it seems like it’s not working or is no good.
We’ll have to wait and see. I’m still not eating rocks or putting glue on my pizza.
There is no artificial intelligence, just very large statistical models.
It’s easier for the marketing department. According to an article, it’s neither artificial nor intelligent.
In what way is it not artificial
Artificial intelligence (AI) is not artificial in the sense that it is not fake or counterfeit, but rather a human-created form of intelligence. AI is a real and tangible technology that uses algorithms and data to simulate human-like cognitive processes.
I’m generally familiar with “artificial” to mean “human-created”
Humans created cars and cars are real. I tried to get some info from the Wired article but they pawalled me.
“Artificial” doesn’t mean “fake”, it usually means “human made”
That’s what Gemini said.
Found a link to Kate Crawford’s research. The quote is near the bottom of the article. It’s interesting, anyway.
When will people finally stop parroting this sentence? It completely misses the point and answers nothing.
Where’s the intelligence in suggesting glue in pizza? Or is it just copying random stuff and guessing what comes next like a huge phone keyboard app?
This is like saying that automobiles are overhyped because they can’t drive themselves. When I code up a new algorithm at work, I’m spending an hour or two whiteboarding my ideas, then the rest of the day coding it up. AI can’t design the algorithm for me, but if I can describe it in English, it can do the tedious work of writing the code. If you’re just using AI as a Google replacement, you’re missing the bigger picture.
I’m retired. I don’t do all that stuff.
Maybe look into the creativity side more and less ‘Google replacement’?
I’ll see if I can think of something creative to do. I was just reading an article from MIT that pointed out that one reason AI is bad at search is that it can’t determine whether a source is accurate. It can’t tell the difference between Reddit and Harvard.
Neither can most of reddit…
The hype machine said we could use it in place of search engines for intelligent search. Pure BS.
Yes. Far more useful to embrace its hallucinogenic qualities…
A lot of people are doing work that can be automated in part by AI, and there’s a good chance that they’ll lose their jobs in the next few years if they can’t figure out how to incorporate it into their workflow. Some people are indeed out of the workforce or in industries that are safe from AI, but that doesn’t invalidate the hype for the rest of us.
The natural general hype is not new… I even see it in 1970’s scifi. It’s like once something pierced the long-thought-impossible turing test, decades of hype pressure suddenly and freely flowed.
There is also an unnatural hype (that with one breakthrough will come another) and that the next one might yield a technocratic singularity to the first-mover: money, market dominance, and control.
Which brings the tertiary effect (closer to your question)… companies are so quickly and blindly eating so many billions of dollars of first-mover costs that the corporate copium wants to believe there will be a return (or at least cost defrayal)… so you get a bunch of shitty AI products, and pressure towards them.
Sounds about right
Interestingly, the turing test has been passed by much dumber things than LLMs
I’m not talking about one-offs and the assessment noise floor, more like: “ChatGPT broke the Turing test” (as is claimed). It used to be something we tried to attain, and now we don’t even bother trying to make GPT seem human… we actually train them to say otherwise lest people forget. We figuratively pole-vaulted over the turing test and are now on the other side of it, as if it was a point on a timeline instead of an academic procedure.
True!
Disclaimer: I’m going to ignore all moral questions here
Because it represents a potentially large leap in the types of problems we can solve with computers. Previously the only comparable tool we had to solve problems were algorithms, which are fast, well-defined, and repeatable, but cannot deal with arbitrary or fuzzy inputs in a meaningful way. AI excels at dealing with fuzzy inputs (including natural language, which was a huge barrier previously), at the expense of speed and reliability. It’s basically an entire missing half to our toolkit.
Be careful not to conflate AI in general with LLMs. AI is usually implemented as Machine Learning, which is a method of fitting an output to training data. LLMs are a specific instance of this that are trained on language (hence, large language models). I suspect that if AI becomes more widely adopted, most users will be interacting with LLMs like you are now, but most of the business benefit would come from classifiers that have a more restricted input/output space. As an example, you could use ML to train an AI that can be used to detect potentially suspicious bank transactions. The more data you have to sort through, the better AI can learn from it*, so I suspect the companies that have been collecting terabytes of data will start using AI to try to analyze it. I’m curious if that will be effective.
*technically it depends a lot on the training parameters
I suppose it depends on the data you’re using it for. I can see a computer looking through stacks data in no time.
-
automation by companies so they can "streamline"their workforces.
-
innovation by “teaching” it enough to solve bigger problems (cancer, climate, etc).
-
creating a sentient species that is the next evolution of life and watching it systematically eradicate every last human to save the planet.
Terminator was also a documentary
Skynet for the win!
Come with me if you want to live!
-
Holy BALLS are you getting a lot of garbage answers here.
Have you seen all the other things that generative AI can do? From bone-rigging 3D models, to animations recreated from a simple video, recreations of voices, art created from people without the talent for it. Many times these generative AIs are very quick at creating boilerplate that only needs some basic tweaks to make it correct. This speeds up production work 100 fold in a lot of cases.
Plenty of simple answers are correct, breaking entrenched monopolies like Google from search, I’ve even had these GPTs take input text and summarize it quickly - at different granularity for quick skimming. There’s a lot of things that can be worthwhile out of these AIs. They can speed up workflows significantly.
I’m a simple man. I just want to look up a quick bit of information. I ask the AI where I can find a setting in an app. It gives me the wrong information and the wrong links. That’s great that you can do all that, but for the average person, it’s kind of useless. At least it’s useless to me.
You aren’t really using it for its intended purpose. It’s supposed to be used to synthesize general information. It only knows what people talk about; if the subject is particularly specific, like the settings in one app, it will not give you useful answers.
I mentioned somewhere in here that I created a document with it and it turned out really good.
Yeah, it’s pretty good at generating common documents like that
So you got the wrong information about an app once. When a GPT is scoring higher than 97% of human test takers on the SAT and other standardized testing - what does that tell you about average human intelligence?
The thing about GPTs is that they are just word predictors. Lots of time when asked super specific questions about small subjects that people aren’t talking about - yeah - they’ll hallucinate. But they’re really good at condensing, categorizing, and regurgitating a wide range of topics quickly; which is amazing for most people.
It’s not once. It has become such an annoyance that I quit using and asked what the big deal is. I’m sure for creative and computer nerd stuff it’s great, but for regular people sitting at home listening to how awesome AI is and being underwhelmed it’s not great. They keep shoving it down our throats and plain old people are bailing.
tl;dr: It’s useful, but not necessarily for what businesses are trying to convince you it’s useful for
Yeah, see that’s the kicker. Calling this “computer nerd stuff” just gives away your real thinking on the matter. My high school daughters use this to finish their essay work quickly, and they don’t really know jack about computers.
You’re right that old people are bailing - they tend to. They’re ignorant, they don’t like to learn new and better ways of doing things, they’ve raped our economy and expect everything to be done for them. People who embrace this stuff will simply run circles around those who don’t. That’s fine. Luddites exist in every society.
Yeah, I feel like people who have very strong opinions about what AI should be used for also tend to ignore the facts of what it can actually do. It’s possible for something to be both potentially destructive and used to excess for profit, and also an incredible technical achievement that could transform many aspects of our life. Don’t ignore facts about something just because you dislike it.
It’s understandable to feel frustrated when AI systems give incorrect or unsatisfactory responses. Despite these setbacks, there are several reasons why AI continues to be heavily promoted and integrated into various technologies:
-
Potential and Progress: AI is constantly evolving and improving. While current models are not perfect, they have shown incredible potential across a wide range of fields, from healthcare to finance, education, and beyond. Developers are working to refine these systems, and over time, they are expected to become more accurate, reliable, and useful.
-
Efficiency and Automation: AI can automate repetitive tasks and increase productivity. In areas like customer service, data analysis, and workflow automation, AI has proven valuable by saving time and resources, allowing humans to focus on more complex and creative tasks.
-
Enhancing Decision-Making: AI systems can process vast amounts of data faster than humans, helping in decision-making processes that require analyzing patterns, trends, or large datasets. This is particularly beneficial in industries like finance, healthcare (e.g., medical diagnostics), and research.
-
Customization and Personalization: AI can provide tailored experiences for users, such as personalized recommendations in streaming services, shopping, and social media. These applications can make services more user-friendly and customized to individual preferences.
-
Ubiquity of Data: With the explosion of data in the digital age, AI is seen as a powerful tool for making sense of it. From predictive analytics to understanding consumer behavior, AI helps manage and interpret the immense data we generate.
-
Learning and Adaptation: Even though current AI systems like Gemini, ChatGPT, and Microsoft Co-pilot make mistakes, they also learn from user interactions. Continuous feedback and training improve their performance over time, helping them better respond to queries and challenges.
-
Broader Vision: The development of AI is driven by the belief that, in the long term, AI can radically improve how we live and work, advancing fields like medicine (e.g., drug discovery), engineering (e.g., smarter infrastructure), and more. Developers see its potential as an assistive technology, complementing human skills rather than replacing them.
Despite their current limitations, the goal is to refine AI to a point where it consistently enhances efficiency, creativity, and decision-making while reducing errors. In short, while AI doesn’t always work perfectly now, the vision for its future applications drives continued investment and development.
We shall see. The above feels like an AI reponse.
lmao I see what you did there
Only ChatGPT is obsessed with bullet points like this. I’m pretty damn sure this is an LLM response
-
