As I mentioned in another post, about the same topic:
Slapping the words “artificial intelligence” onto your product makes you look like those shady used cars salesmen: in the best hypothesis it’s misleading, in the worst it’s actually true but poorly done.
I think AI has mostly been about luring investors into pumping up share prices rather than offering something of genuine value to consumers.
Some people are gonna lose a lot of other people’s money over it.
Yeah, can make some products better but most of the products these days that use AI, it doesn’t actually need them. It’s annoying to use products that actively shovel AI when it doesn’t even need it.
Ya know what pfoduct MIGHT be better with AI?
Toasters. They have ONE JOB, and everybody agrees their toaster is crap. But you’re not going to buy another toaster, because that too will be crap.
How about a toaster, that accurately, and evenly toasts your bread, and then DOESN’T give you a heart attack at 5am when you’re still half asleep???
IS THAT TOO MUCH TO ASK???
This is the visionary we need. Take my venture capital millions on a magic carpet ride, time traveler!
Nah. We already have AI toasters, and they’re ambitious, but rubbish.
Adding AI is just serious overkill for a toaster, especially when it wouldn’t add anything meaningful, not compared to just designing the toaster better.
It only needs one string of conditions that it can understand: don’t catch on fire. Turn yourself off IF smoke.
Sweet, I’m the one who gets to link the obligatory Technology Connections toaster video!
Aw man, now I want this toaster.
I said the exact same thing months ago when I saw that video. I don’t even use a toaster.
Yes, I’m getting some serious dot-com bubble vibes from the whole AI thing. But the dot-com boom produced Amazon, and every company is basically going all-in in the hope they are the new Amazon while in the end most will end up like pets.com but it’s a risk they’re willing to take.
“You might lose all your money, but that is a risk I’m willing to take”
- visionairy AI techbro talking to investors
Investors pump money in a bunch of companies so the chances of at least one of them making it big and paying them back for all the failed investments is almost guaranteed. That’s what taking risks is all about.
Sure, but it SEEMS, that some investors are relying on buzzword and hype, without research and ignoring the fundamentals of investing, i.e. besides the ever evolving claims of the CEO, is the company well managed? What is their cash flow and where is it going a year from now? Do the upper level managers have coke habits?
You’re right, but these fundamentals don’t really matter anymore, investors are buying hype and hoping to sell a bigger hype for more money later.
OpenAI will fail. StabilityAI will fail. CivitAI will prevail, mark my words.
My doorbell camera manufacturer now advertises their products as using, “Local AI” meaning, they’re not relying on a cloud service to look at your video in order to detect humans/faces/etc. Honestly, it seems like a good (marketing) move.
A lot of it is follow the leader type bullshit. For companies in areas where AI is actually beneficial they have already been implementing it for years, quietly because it isn’t something new or exceptional. It is just the tool you use for solving certain problems.
Investors going to bubble though.
I tried to find the advert but I see this on YouTube a lot - an Adobe AI ad which depicts, without shame, AI writing out a newsletter/promo for a business owner’s new product (cookies or ice cream or something), showing the owner putting no effort into their personal product and a customer happily consuming because they were attracted by the thoughtless promo.
How are producers/consumers okay with everything being so mediocre??
How are producers/consumers okay with everything being so mediocre??
“You’re always trying to make everything just a little bit worse so that you can feel good about having a lot more of it. I love it. It’s so human!” - The Good Place
Definitely. Many companies have implemented AI without thinking with 3 brain cells.
Great and useful implementation of AI exists, but it’s like 1/100 right now in products.
If my employer is anything to go by, much of it is just unimaginative businesspeople who are afraid of missing out on what everyone else is selling.
At work we were instructed to shove ChatGPT into our systems about a month after it became a thing. It makes no sense in our system and many of us advised management it was irresponsible since it’s giving people advice of very sensitive matters without any guarantee that advice is any good. But no matter, we had to shove it in there, with small print to cover our asses. I bet no one even uses it, but sales can tell customers the product is “AI-driven”.
My old company before they laid me off laid off our entire HR and Comms teams in exchange for ChatGPT Enterprise.
“We can just have an AI chatbot for HR and pay inquiries and ask Dall-e to create icons and other content”.
A friend who still works there told me they’re hiring a bunch of “prompt engineers” to improve the quality of the AI outputs haha
God that sounds like hell.
That’s an even worse ‘use case’ than I could imagine.
HR should be one of the most protected fields against AI, because you actually need a human resource.
And “prompt engineer” is so stupid. The “job” is only necessary because the AI doesn’t understand what you want to do well enough. The only productive guy you could hire would be a programmer or something, that could actually tinker with the AI.
I’m sorry. Hope you find a better job, on the inevitable downswing of the hype, when someone realizes that a prompt can’t replace a person in customer service. Customers will invest more time, i.e., even wait in a purposely engineered holding music hell, to have a real person listen to them.
LLMs: using statistics to generate reasonable-sounding wrong answers from bad data.
Often the answers are pretty good. But you never know if you got a good answer or a bad answer.
And the system doesn’t know either.
For me this is the major issue. A human is capable of saying “I don’t know”. LLMs don’t seem able to.
Accurate.
No matter what question you ask them, they have an answer. Even when you point out their answer was wrong, they just have a different answer. There’s no concept of not knowing the answer, because they don’t know anything in the first place.
The worst for me was a fairly simple programming question. The class it used didn’t exist.
“You are correct, that class was removed in OLD version. Try this updated code instead.”
Gave another made up class name.
Repeated with a newer version number.
It knows what answers smell like, and the same with excuses. Unfortunately there’s no way of knowing whether it’s actually bullshit until you take a whiff of it yourself.
So instead of Prompt Engineer, the more accurate term should be AI Taste Tester?
From what I’ve seen you’ll need an iron stomach.
They really aren’t. Go ask about something in your area of expertise. At first glance, everything will look correct and in order, but the more you read the more it turns out to be complete bullshit. It’s good at getting broad strokes but the details are very often wrong.
Now imagine someone that doesn’t have your expertise reading that answer. They won’t recognize those details are wrong until it’s too late.
That is about the experience I have. I asked it for factual information in the field I work at. It didn’t gave correct answers. Or, it gave working protocols which were strange and would not be successful.
With proper framework, decent assertions are possible.
- It must cite the source and provide the quote, not just a summary.
- An adversarial review must be conducted
If that is done, the work on the human is very low.
That said, it’s STILL imperfect, but this is leagues better than one shot question and answer
Except LLMs don’t store sources.
They don’t even store sentences.
It’s all a stack of massive N-dimensional probability spaces roughly encoding the probabilities of certain tokens (which are mostly but not always words) appearing after groups of tokens in a certain order.
And all of that to just figure out “what’s the most likely next token”, an output which is then added to the input and fed into it again to get the next word and so on, producing sentences one word at a time.
Now, if you feed it as input a long, very precise sentence taken from a unique piece, maybe you’re luck and it will output the correct next word, but if you already have all that you don’t really need an LLM to give you the rest.
Maybe the “framework” you seek - which is quite akin to a indexer with a natural language interface - can be made with AI, but it’s not something you can do with LLMs because their structure is entirely unsuited for it.
The proper framework does, with data store, indexing and access functions.
The cutting edge work is absolutely using LLMs in post-rag pipelines.
Consumer grade chat interfaces def do not do this.
Edit if you worry about topics like context window, sentence splitting or source extraction, you aren’t using a best in class framework any more.
Market shows that investors are actively turned on by products that use AI
Market shows that the market buys into hype, not value.
Market shows that hype is a cycle and the AI hype is nearing its end.
How can you tell when the cycle is ending?
When one of two things happens:
- A new hype starts to replace it (can happen fast though!)
- The hype starts to specialize into subcategories of the hype (e.g. AI images, AI videos, AI text generation)
When “AI” hype dies down we are likely to see “AI” removed from various topics because enough people know and understand the hyped parent topic. It’ll just be “image generation”, “video generation”, “generated text”, etc.
Customers worry about what they can do with it, while investors and spectators and vendors worry about buzzwords. Customers determine demand.
Sadly what some of those customers want to do is to somehow improve their own business without thinking, and then they too care about buzzwords, that’s how the hype comes.
It’s the new block chain or NFT hype, they think it’s magic.
But what if it actually is magic this time? Just this once!? And we miss the hype train?! (This is a sarcastic impression of real conversations I have had.)
There are different types of people in the market. The informed ones hate AI, and the uninformed love it. The informed ones tend to be the cornerstones of businesses, and the uninformed ones tend to be in charge.
So we have… All this. All this nonsense. All because of stupid managers.
No shit, because we all see that AI is just technospeak for “harvest all your info”.
Not to mention it’s usually dog shit out put
I refuse to use Facebook anymore, but my wife and others do. Apparently the search box is now a Meta AI box, and it pisses them every time. They want the original search back.
That’s another thing companies don’t seem to understand. A lot of them aren’t creating new products and services that use ai, but are removing the existing ones, that people use daily and enjoy, and forcing some ai alternative. Of course people are going to be pissed off!
For the love of god, defund MBAs.
LLM based AI was a fun toy when it first broke. Everyone was curious and wanted to play with it, which made it seem super popular. Now that the novelty has worn off, most people are bored and unimpressed with it. The problem is that the tech bros invested so much money in it and they are unwilling to take the loss. They are trying to force it so that they can say they didn’t waste their money.
Honestly they’re still impressive and useful it’s just the hype train overload and trying to implement them in areas they either don’t fit or don’t work well enough yet.
They’ve overhyped the hell out of it and slapped those letters on everything including a lot of half baked ideas. Of course people are tired of it and beginning to associate ai with bad marketing.
This whole situation really does feel dotcommish. I suspect we will soon see an ai crash, then a decade or so later it will be ubiquitous but far less hyped.
Thing is, it already was ubiquitous before the AI “boom”. That’s why everything got an AI label added so quickly, because everything was already using machine learning! LLMs are new, but they’re just one form of AI and tbh they don’t do 90% of the stuff they’re marketed as and most things would be better off without them.
