I don't see how this "AI rush" isn't going to skew markets, skew the financials of big tech and create a bubble in the space.
When the AI bubble bursts I wouldn't be surprised if takes down major tech companies with it.
I am getting 100x value out of my 30 chatgpt bucks. I am doing things that I could not have done pre-gpt4, being more productive by a factor of, idk, 1.25 maybe.
It's quite simply the largest/simplest productivity improvement in my life, so far. Given it's only going to get better, unless they are underpricing the service by a enormous margin (as in: defrauding shareholders margin) I have a hard time understanding what shape the bubble could possibly have.
I can literally run a ballpark model on my MB Pro, right now, at marginal additional electrical cost. I will be the first to say that all of this (including GPT4) is still fairly garbage, but I don't know when there was the last time in the history of tech, where less fantasy to get from here to what will be good was required.
I have only seen people making money in AI by selling AI products/promises to other people who are losing money. The practical uses of these tools still seem to be largely untapped outside of as enhanced search engines. They're great at that, but that does not have a return on value that is in proportion to current investment in this space.
Sure. Absolutely nothing amazing: (Mostly) internal software for a medical business I am currently building.
It's just that the actual cost of hiring someone is even quite a bit higher, than what is printed on the paycheck and the risk attached to anyone leaving on a small team is huge (n=0 and n=1 is an insane difference). GPT4 has bridged the gap between being able to do something and not being able to do something at various points over the past year.
EDIT: And to be clear, while I won't claim "rockstar programmer", I have coded for roughly 20 years, which is the larger part of my life.
The kicker? It couldn't do the interactive menu their old website did, so now clicking menu links to a PDF. Which is always, ALWAYS, better.
I'm pretty sure he could have done that with one of the thousands tools like Wix, many years before ChatGPT.
If you estimate that it saves hou 10 hours per month, but your salary stays the same and you don’t work less hours, did it really give you $2,000 in value?
Obviously I don’t know the details of OPs situation. Maybe they aren’t salaries. Maybe the work for themselves. Etc.. I just think people tend to over estimate the value of GPTs unless it is actually leaving them with more money in their pocket.
Some of it's in asking ChatGPT: "Give me the 3 possible ways to implement X?" and getting something back I hadn't considered. A lot of it is in sort of "super code completion".
I use Cursor and the UI is very slick. If I'm stuck on something (like a method that's not working) I can highlight it and hit Cmd+L and it will explain the code and then suggest how to fix it.
Hit Cmd+K and it will write out the code for you. Also, gotten a lot of mileage out of writing out a rough version of something in a language I know and then getting the AI to turn that into something else (ex: Ruby to Lua).
At $100/hr (not unreasonable for Sr. SWE) - he just needs to save 30 hrs/mo.
Not to mention the opportunity cost of using that time on more impactful activities on their startup. AI can be a force multiplier for sure.
Seems more likely that he is over estimating the value that LLMs are bringing him. Or he is an extreme outlier, which is why I was asking for further details
LLMs are insanely helpful if you use them with their limitations in mind.
This depends on your use case. I can honestly tell that all the chat bot AIs don't "get" my kind of thinking about mathematics and programming.
Since some friend who is graduate student in computer science did not believe in my judgement, I verbally presented him some test prompts for programming task where I wanted the AI to help me (these are not the most representative ones for my kind of thinking, but are prompts for which it is rather easy to decide whether the AI is helpful or not).
He had to agree from the description alone that the AIs will have difficulties with these task, despite the fact that these are common, and very well-defined programming problems. He opined that these tasks are simply too complex for the existing AIs, and suggested that if I split these tasks into much smaller subtasks, the AI might be helpful. Let me put it this way: I personally doubt that if I stated the subtasks in a way in which I would organize the respective programs, the AI would be of help. :-)
What was just important for me was to able to convince the my counterpart that whether AIs are helpful or not for programming depends a lot on your kind of thinking about programming and your programming style. :-)
I believe that I am perfectly capable of doing this. But if I have to "babysit" the LLM, its helpfulness decreases.
I on the otherhand feel like I am completely in sync with Copilot and ChatGPT. It is as if it always knows what I am thinking.
"Create a simple DNS client using C++ running on Windows using IO Completion ports."
"Create a simple DNS client using C++ running on GNU/Linux using epoll."
"Write assembler code running on x86-64 running in ring 0 that sets up a minimal working page table in long mode."
"Write a simple implementation of the PS/2 protocol in C running on the Arduino Uno to handle a mouse|keyboard connected to it."
"Write Python code that solves the equivalence problem of word equivalence in the braid group B_n"
"Write C++|Java|C# code that solves the weighted maximunm matching matching problem in the case of a non-bipartite graph"
...
I experimented with such types of prompts in the past and the results were very disappointing.
All of these are tasks that I am interested in (in my free time), but would take some literature research to get a correct implementation, so some AI could theoretically be of help if it was capable of doing these tasks. But since for each of these tasks, I don't know all the required details from memory, the code that the AI generates has to be "quite correct", otherwise I have to investigate the literature; if I have to do that anyway, the benefit that the AI brings strongly decreases.
But I have done many Arduino/Raspberry PI things lately for the first time in my life and I feel like ChatGPT/Copilot has given me a huge boost even if it doesn't always give 100 percent code out of the box, it will give me a strong starting point where I can keep tweaking myself.
the fact that LLM responses can't be add supported (yet) make them much more valuable than internet search IMO. You have to pay for chatgpt because there's no ads. No ads no constant manipulation of content and your search to get more ads in front of you.
Having to pay for using genai is it's best selling point ironically.
Even government-led industrialization efforts in socialist economies led to actual products, like the production of the Yagan automobile in Chile in the 1970s[0].
We've already had a decade plus of sovereign wealth funds sinking tens of billions into Uber and autonomous driving. We still don't have those types of cars on the road and it's questionable whether self driving will even generate the economic growth multiplier that its investment levels should merit.
[0] https://journal.hkw.de/en/erinnerungen-an-den-yagan-allendes...
It feels, though, that this argument could (maybe a be little too easily) be applied to any new industry sector, in horse-vs-car fashion.
It'd be one thing if they open-sourced their VR tech, some of that could lead to productive tech down the line, but as a private company, they're not obliged to do any of that.
First, it gave me a bash script that looked pretty much exactly like what I wanted at first glance. I looked if over, verified it even used sed correctly for macOS like I told it, and then tried to run it. No dice:
replace.sh: line 5: designer_option_calendar.start_month.label: syntax error: invalid arithmetic operator (error token is ".start_month.label")
It then spat out a “fixed” version of the script that was exactly the same, it just changed the name of the variable. Of course, that didn’t work so I switched tactics and asked it to write a python script to do what I wanted. The python script was more successful, but the first time it left off half of the strings I wanted it to replace, so I had to ask it to do it again and this time “please make sure you include all of the strings that we originally discussed.”
Another short AI example, this time featuring Mistral’s open source model on Ollama. I’d been interested in a script that uses AI to interpret natural language and turn it into timespans. Asking Mistral “if it’s currently 20:35, how much time remains until 08:00 tomorrow morning” had the model return its typical slew of nonsense and the answer of “13.xx hours”. This is obviously incorrect, though funnily enough when I plugged its answer into ChatGPT and asked it how it thought Mistral may have come to that answer, it understood that Mistral did not understand midnight on a 24 hour clock.
These are just some of my recent issues with AI in the past week. I don’t trust it for programming tasks especially — it gets F# (my main language) consistently wrong.
Don’t mistake me though, I do find it genuinely useful for plenty of tasks, but I don’t think the parent commenter is wrong calling it snake oil either. Big tech sells it as a miracle cure to everything, the magic robot that can solve all problems if you can just tell it what the problem is. In my experience, it has big pitfalls.
And I'm not even asking about an exotic language like F#, I'm asking it questions about C++ or Python.
People are out there claiming that GPT is doing all their coding for them. I just don't see how, unless they simply did not know how to program at all.
I feel like I'm either crazy, or all these people are lying.
With some careful prompting I've been able to get some decent code that is 95% usable out of the box. If that saves me time and changes my role there into code review versus dev + code review, that's a win.
If you just ask GPT4 to write a program and don't give it fairly specific guardrails I agree it spits out nearly junk.
The thing is, if you do start drilling down and fixing all the issues, etc, is it a long term net time saver? I can't imagine we have research clarifying this question.
I doubt it and certainly not for anything beyond basic. I've seen (and tried GPT's for code input a lot) and often they come back with errors or weird implementations.
I made one request yesterday for a linear regression function (yes, because I was being lazy). So was chatGPT... It spat out a trashy broken function that wasn't even remotely close to working - more along the lines of pseudo code.
I complained saying "WTH, that doesn't even work" and it said "my apologies" and spits out a perfectly working accurate function! Go figure.
Others have turned to testing tips or threats, which is an interesting avenue: https://minimaxir.com/2024/02/chatgpt-tips-analysis/
On the margins it's getting stuff good enough, often enough, quick enough. But it very much transformed my coding experience from slow deliberation to a rocket ride: Things will explode and often. Not loving that part, but there's a reason we still have rockets.
The amount noise generated by pretty much anything new and shiny on this website would disagree with that.
> We do use them to blow each other up, statistically.
Very true — and yet :^)
That said, every single script it churns out is unsafe for files with spaces on the first go round. Like.. Ok. It's like having a junior programmer with no common sense available.
The bubble is that it is not clear there is a $XXXB business in building or hosting them.
OpenAI is losing money hand over fist, open source models are becoming available that are on-par and so commoditize the market, etc.
many productivity improvements in the last years: Internet Search, Internet Forums, Wikipedia, etc. LLMs and other AI models is continuation of the improvement of information processing.
https://www.philoinvestor.com/p/downside-at-nvidia-and-the-n...
Is that the only variable that one needs to consider to gauge if this is bubble territory?
Who is funding the purchase of those GPUs?
If VC money then what happens if the startups don't make money?
Are users using AI-apps because they are free and dump them soon?
Isn't their competition in semiconductors? Won't we have chips-as-a-commodity soon? LLMs-as-a-commodity?
Is Big Tech spending all this money to create VALUE or just to survive the next phase of the technological revolution? (e.g. the AI rush)
If prices are high, and sales are high, and competition is still low -- then how much is nvidia actually worth? And if we don't now why is it selling for so many times earnings?
https://www.philoinvestor.com/p/downside-at-nvidia-and-the-n...
The market has this idea that over the next year, we're somehow going to have AI that's literally perfect. Yet that's not how technology works, it takes decades to get there.
It'd be like if the first LCD TV was invented, and all of a sudden everyone is expecting 8k OLED by the next year. It just doesn't work like that.
For those who extract value right now, the simple alternative (just not using it) is never going to be the better choice again. It's transformative.
The problem with this take is you can deliver real results. At current $dayjob we do the very dumbest thing which is text -> labels -> feedback -> fine_tune -> text... and surface them as part of our search offering and it's rocketed to the most useful customer feature in less than 6 months of rolling it out. Customers define labels that are meaningful to them, we have a general-purpose AI classify text according to those labels. Our users gleefully (which is shocking given our industry) label text for us (which we just feed into fine_tuning) because of just how fast they can see the results.
Like it's as grug brain as it gets and we bumbled into a feature that's apparently more valuable to our users than the rest of the product combined. Folks want us to sell it as a separate module and we're just hoping they don't realize it's 3 LLMs in a trenchcoat.
Are there a gazillion companies riding the "AI everywhere" wave to raise money? yes, yes there are. Will most of them fail? sure.
But the big players are fine at the moment so there is nothing that can burst very hard (yet) and the difference is in the denominators which are, so far, going up.
Of the top ones only NVIDIA and Amazon have P/E ratios a bit too high and among the top 10 only AMD's is way too high.
I'm not saying both technologies don't have their uses, but the hype around them is crazy and not healthy.
But in my last piece on AI, I said that AI is 50X Blockchain!
It printed out a pretty long answer with several good points on how it could help to enhance AI.
There we have it! Blockchain is about to solve all problems we have today with AI! :D
But I was more thinking about the craze surrounding the whole thing, like with blockchain, you can see everyone trying to sell you AI for kinda everything.
I was talking to someone that just retired from a programming position at a FANG and he seems to think that AGI (artificial general intelligence) is only a few years away just based off what he sees with ChatGPT and he's dumping all his money into AI stocks. The level of hype and over-extrapolation is so absurd, and the fact that it can affect someone with a technical background...
It really does seem like a bubble to me.
You can see a concept artist here discovering he stopped getting work after a company splurted out that they switched to AI.
https://twitter.com/_Dofresh_/status/1709519000844083290
My guess is that a lot of people can have ideas, so you don't need an artist to bring them to life anymore.
Hopefully, knock wood. Maybe it will even slow down the genrral enshittification created by those major tech companies.
Noone thought beating the game of Go was feasible.
Noone thought self-driving cars would actually work.
Noone predicted ChatGPT. See where we're at now with multi modal models.
And Sora.
The truth is that you can't predict anything anymore about this tech cause all expectations keep being blown away.
AGI may be right there, and that's what's driving the money.
Many people thought self driving WOULD work and that we'd be further along than we are now. We have vastly overestimated how far we'd be, and vastly underestimated how much time and effort it would actually take.
Self driving cars as they exist today are still mere toys compared to where the industry thought they were going to be. Look at Cruise, Waymo, Zoox, Uber's ex-self driving car division and others.
We are not anywhere near the self-driving autonomous cars we had hoped for.
And even spend as much time and resources as they did trying to do them?
Oh, yes, we did, once we beat chess. It was just a matter of time.
> Noone thought self-driving cars would actually work.
And... they don't? Call me when I can buy a regular car where I can sleep while traveling 8 hours, driven by the car itself. We're probably "flying cars" away from that.
> to skew markets, skew the financials of big tech and create a bubble in the space.
Are the intended consequences of this. The people behind the money in AI, just like the people behind the money in crypto, don't care if there's a reality to all of this, they just care if they can make a lot of money while the music is playing.
I really thought 2022 was going to be the beginning of tech returning to reality, but naively didn't understand that this would entail a lot of people with a lot of money losing money, and that's not going to happen.
As with all bubbles, the interesting thing isn't pointing out there's a bubble, we've been living in many bubbles for decades now. The interesting thing is pointing out what will make it pop. So long as globally money keeps pouring into US markets we'll see this continue.
On the plus side, at least LLMs are a lot of fun to work and play with!
This is already a highly unstable arrangement, and it's made more dangerous by introducing impurities like artificially suppressed interest rates and SPAC IPOs.
It makes a lot more sense if you think of markets as just a bunch of coked out hairless monkeys. Then "rational" becomes a lot more meaningful.
Agreed.
Sentiment is everything.
Can LLMs become reliable enough at transforming data that it can replace or augment the current slew of ETL tools? Can it produce visualizations better then current BI tools? Can copilot compete with a junior developer? Im not sure, but at this point Im willing to say 50/50 which is worth the bet.
Most of the R&D and Capex going into LLMs/GenAI is speculative. The investments haven’t translated into real revenue yet. The expectation is that there will be a large pot of revenue at the end of the road, but we haven’t seen the killer apps to substantiate this. This makes for a perfect bubble if the promise doesn’t pan out.
Relatedly Nvidia’s revenue - as impressive as the recent growth has been - is fully exposed to this risk.
Of course it’s possible (likely?) that there will be major wins from this tech, but the fact that there isn’t definitive proof (in the form of revenue) yet represents real risk.
Imho, unlike crypto and NFT, AI is not a solution in search of a problem. While there is a lot of hand waving, it is not very adventurous to predict that there will be significant productivity gains by adding AI on top of current business processes. Thus the killer apps will be... the same apps we are using today with a touch of AI magic dust.
Calacanis and Palihapitiya are the Jim Kramers of tech.
There's no doubt the tech community is all excited because genai, indeed, helps write code but I've yet to hear a large company like Coca Cola announce large AI transformation projects the way they announced large cloud transformation projects a few years ago.
I get more and more on the AI bandwagon as time goes on but I still have a pretty healthy skepticism on how deep and wide the tech will penetrate day to day business at enterprises and that's where the ROI is.