Superhuman: What can AI do in 30 minutes?
oneusefulthing.substack.com
oneusefulthing.substack.com
The primary problem, which seems common to LLMs asked to do this stuff, is "very high level output" - a content smoothie, with few features that are particularly specific to the prompt. The marketing campaign in the OP is so generic, you can `s/Saturn Parable/Any other educational product` and it's still "fine". Similarly the emails - there are 1 to 2 sentences that are product specific, and a bunch of fluff. If I paid a marketing agency for this, I'd be very disappointed.
The LLM isn't demonstrating much more than "Generic templating ability over a large range of templates" in this instance. Whilst that's probably 50% of the jobs in the world, such jobs were already at risk of someone searching for "Basic X template" and expanding the placeholders themselves. I think I could do a similar job in 30 minutes by doing exactly that.
LLM's main wins seem to be providing a single unified entry point to all the templates in the universe. It's a "Universal UI", rather than a "Content creator". I guess I shouldn't discount the value of such a thing, once we get the "Sometimes it just lies" problem under control.
The most interesting immediate thing here is the image generation - that's pretty good, and a big saving over scraping through stock images. I suspect the demise of stock image providers to be the first palpable win for generative AIs, if the copyright question doesn't bog this whole field down.
I'm surprised the copyright issues aren't given more attention. It's technically not legal (in the US) to modify copyrighted images without the authors permission. I don't see how it's possible that systems like DALL-E haven't already done that. There's a near 0% chance that they aren't trained on at least one copyrighted image.
In short, the copyright issues appear to be given a lot of attention? Legal precedent takes time.
They look at countless numbers of them and learn what is the correct "professional style", etc. This is why you can instantly recognize most stock photos, because they all follow the "stock photo template".
In the context of AI, the issue is specifically with using a copyrighted image and creating something new based off of that. That is explicitly illegal for human artists.
But where do you draw the line? If AI imagines 3 people around a business table in front of a flip chart, is that copyright infringement on similar stock photos? Note that in the AI created image, the people are unique, they never existed, the business table is unique, the flip chart is unique, and in general you can't point to any existing photo it was trained over and say "it just copied this item here".
If so, why isn't it also copyright infringement when a human photographer stages another similar shot?
If I ask an AI for a picture, there is no artist 'bob' to be assigned ownership under copyright law and therefor it's not copyrightable under existing law.
Funny how originally all these pro-AI art people were anti-copyright law but I can see them sometime soon lobbying for MORE restrictive copyright law (granting it in a larger pool or circumstances hence making more things copyrighted) so that they can overcome this.
Well that's sort of the whole thing with copyright law. It's fairly arbitrary. Copyright specifically forbids derivative works: "A derivative work is a work based on or derived from one or more already exist- ing works."
It's vague on purpose because copyright infringements generally need to be handled on a case by case basis.
Now there are AI's trained on images that are copyrighted. If the image is copyrighted, should the AI have been allowed to train on it?
The reason human training/inspiration isn't specifically forbidden is because it can't be. We are impressioned by things whether we like it or not. Regardless, we can't prove where someone's inspiration came from.
But the act of training an AI on copyrighted images is deliberate. I feel that's a key difference.
And there's plenty of cases that say if you're too inspired, that's illegal and/or you own damagaes/royalties.
https://ethicsunwrapped.utexas.edu/case-study/blurred-lines-...
Taking copyrighted images and dumping them into a machine learning model is deliberate usage. The AI isn't a person, so it doesn't draw on past experience by happenstance.
Making the two processes equivalent is very reductive.
> For example: if they base their painting on an oft photographed or painted location, generic subject matter, or an image that has been taken by numerous photographers they would likely not be violating copyright law.
> However: if they create their painting, illustration or other work of art from a specific photograph or if your photography is known for a particular unique style, and their images are readily identifiable with you as the photographer, and an artist copies one of your photographic compositions or incorporates your photographic style into their painting or illustration they may be liable for copyright infringement.
https://www.thelawtog.com/blogs/news/what-do-i-do-if-someone...
Because AI rarely recreates images 1:1 it is unlikely the violate any copyrights.
Seems pretty cut and paste to me. If it has trained on my images and then uses that trained dataset to generate new images those images are in violation. Using training sets that include unlicensed copyrighted works requires attribution and licensing. TO be legal otherwise the end user/AI company would have to be able to prove in a court of law that without training on my copyrighted work it would have still generated that specific image which I can't see the users/company being able to do.
Is there a rulingn for this? This would be similar as using a school book requires attribution and licensing for your education.
Because of the “i”.
So all we have is a dumb bot that can appropriate styles and ideas. Revolutionary, but not quite to the extent needed to sue it for copyright.
Arguably also, the copy is achieved at generation time, not training time, so the copyright violation is not in making the model or distributing it, but in using it to create copies of artworks. The human artist is the same: in their brain is encoded the knowledge to create forbidden works, but it is only the act of creating the work which is illegal, not the ability. The model creators might still be liable for contributory infringement though.
Anyway, I reject the notion that any use of unlicensed copyrighted works in training models is wrong. That to me seems like the homeopathic theory of copyright, it’s just silly. If copyright works that way we might as well put a cross over AGI ever being legal.
Now consider that these systems are already being used for profit, before this matter has even been settled.
This is huge and as a software developer I am now not worried that GPT or AI will write code instead of me.
Big change will be that big companies/small companies/average people won't need as many applications anymore. Software devs as I read various comments fixate on "AI writing code" too much, where real threat will be that lots of code will never be needed anymore.
That's a very good point.
Also, I am working in a very small team, developing a free app, for a nonprofit.
I will be suggesting to our CEO, that he consider ways to use AI to multiply the various things we need to do, in order to polish and launch the app.
We have a tiny, part-time team (except for Yours Truly), so there's a ton of "polishing the fenders" stuff that takes forever. I will suggest that he consider using ChatGPT (or some of the other engines) to do some of this work.
Time will tell, if this PoV is valid. I can tell you that a flashy, sexy demo, is not the same thing as shipping code.
A number of comments state that the quality of the output is fairly sparse, and amateurish, but this was also a very fast, thirty-minute demo of a marketing workflow, subjected to basic AI tools.
This article was the equivalent of those "Write an app in two hours" seminar/bootcamps.
Valid, but also constrained by the need to teach, and to get done within a certain amount of time. Very strict guardrails, and keep your hands inside the car at all times.
I have taken many, many of these courses, and have given a few. I'm quite aware of the difference between what we produce in a class, and what I'd hand to a customer.
What I think we'll be seeing, quite soon, is "one-person shops," acting as studios/agencies that will take on jobs normally done by large shops.
Like bootcamp babes that go out, thinking that they can now deliver a full-fat app to customers, many will fail.
But some will succeed. Lots of smart, hungry people, out there.
We'll look at what can be done with these tools (which, I should add, are still very much in their infancy. You ain't seen nuthin', yet). I don't think they'll be able to write the deliverables, yet, but that's OK. I think we may be able to leverage them to make those deliverables much more polished and robust.
I would not be surprised to see AI testing and diagnostics, integrated into IDEs.
For example, UI testing. Right now, it's next to worthless, as it's basically scripting and screengrab analysis.
An AI tester can do a much better job of simulating a user, and analyzing the behavior of the app. Of course, it will be a real skill to set up the boundaries and heuristics for the testing, but it could be very cool.
I suspect that AI will also find a place in security; both in hardening and red-team testing, and in blackhat probing.
Right now, it’s amazing for getting some boilerplate very quickly (so is create-react-app, etc).
It’s bad at context as the problem grows and very bad at subtle nuances.
Working with GPT today is like having a super fast and somewhat sloppy developer sitting next to you.
“Shipping” anything it creates means a LOT of review to make sure no false assumptions are present.
I have been “writing code” with it nonstop for weeks now.
Yes, it’s incredible, but it also has serious limitations (at least for now).
But these error checks still have similar errors and hallucinations to the basic output, from my personal experience
It’s not obvious that this recycling refines the output
Try this for yourself
So, you don’t mean “create a ‘system’”, you mean use the UI to talk with ChatGPT about creating a system, rather than using the API and connecting it to tools so it can build the system, verify its behavior, and get feedback that way rather than through conversation with a human user?
There aren’t any tools that I know of that can validate that GPT has correctly interpreted the prompt without any problems related to subtle (or overt) misunderstandings.
This being the case, there’s a lot of back and forth and careful validation necessary before anything ships.
Which is probably one of the easiest types of code to autogenerate.
In fact we already have tools to generate apis from a model. And a model could be produced by ai given human (language) inputs.
a) no-one's telling you to just throw the AI output up on to a website unedited, b) does it not give you at least a bit of pause how quickly this is advancing right now?
Of course, GPT5…
I'm not sure GPT5 will feel appreciably different on this type of task necessarily. GPT-4 feels a lot like GPT-3 for a pretty wide variety of things, but it's when you get higher complexity tasks that you start to see differences.
Is there a genuine problem that we're solving here?
"Quickly and cheaply create a large volume of mediocre content" will definitely appeal to certain entrepreneurial types, but were we actually short of mediocre content? What genuine problem are we solving?
Apart from a further lowering of the bar for certain entrepreneurial types to get rich(er) faster, that is.
If you can get 80% of what you want with a cheap or free tool vs 100% with a full-time salaried employee/expensive freelancers, well, most people are going to pick the former.
I do this as a video editor all the time. If I have a fast turnaround often times I will just drop a LUT or use auto color correction in my in NLE. Of course I will sand down the edges afterwards, but it’s not like I’m going to give every single video that crosses my desk the full color grading treatment. Not everything requires that.
Look at the reddit UI, do you really think that it’s better than something GPT could toss out in 10 minutes?
Is this some kind of a joke? I'm pretty sure whole Reddit's UI team can't be replaced by GPT.
Considering the model doesn't "think" or understand abstract concepts, could we ever expect this?
We don’t necessarily need to teach it not to lie, but just to improve accuracy through better training and training data. It (probably) won’t ever be 100% reliable, but what is? Google searches can be inaccurate, same with Wikipedia and other encyclopedias.
This is less a weird quirk of the training data or a One Weird Trick That Makes Your Matricies Sentient, and more a limitation of the model architecture. Neural networks do not have the capability to implement 'for loops', the only looping construct is the process that runs the model repeatedly on each token. When you tell the model to "think out loud", you're telling it to use prior tokens as for loop state.
Another limitation is that the model can't backtrack. That is, if it says something wrong, that lie is now set in stone and it can't jump back and correct it, so you get confidently wrong behavior. I have to wonder if you could just tell the model to pretend it has a backspace button, so that it could still see the wrong data and avoid the pitfalls it dropped into before.
I agree, it's impressive how it can generate readable text that provides an overview of an idea. But the overview misses key points, or highlights things that aren't really central. For a lot of things, doing something simple like reading a Wikipedia page is likely more productive.
The leap from GPT-2 to 3 was enormous. 3 to 4 was enormous, and we’re not even using 32k context yet nor image input. 4 to 5 will likely be as disruptive if not more.
This isn’t about 4. We’re in the iPhone 1 era of LLMs. This is about what the world will look like in one or two decades. And there’s a good chance this comment might age poorly.
That’s a scary thought. I was skeptical of AI, and still am. But it seems undeniable that the world is in for a big awakening. This might be as big of a transformation to society as the introduction of microprocessors.
More like one or two years at this rate.
I don’t think that’s what they are actually worried about. I would also like to point out that the biggest scams, FTX for example, are simply traditional Ponzi schemes with a crypto front, they have all been executed entirely using regular banking systems and due to the incompetence of those regulators. Bitcoin itself is rock solid and constantly gaining users and influence.
I've spent the last couple of days creating python scripts to automate parts of my business. I'm not a developer (though technical enough to help point GPT in the right direction sometimes when it's getting stuck on problems) and have written <100 lines of python in my life.
I'm using image generation AI regularly to create images for my marketing emails, and when I've got writer's block it helps with the text too.
Right now the iPhone 1 is a great analogy - it was cool but it was really subpar for using a lot of the internet, because it wasn't mobile optimized. GPT takes some coaxing to get it where you want, like you had to do a lot of pinching to zoom in on websites on your phone. In a few generations, this is going to be as seamless to use as the iPhone 5 was compared to the first gen.
Every crypto person said the opposite. They said exactly what ChatGPT-hype people are saying now.
In fact, every drug buy I ever heard of (second hand, of course) involved fiat currencies.
I think progress is sigmoidal rather than exponential, and it’s very hard to tell the difference in the early stages. But even sigmoidal progress with smartphones was enough to completely upend online society. We adapted, of course, but it looks nothing like it did in 2003. We’re all still using the internet; that’s basically it.
Point is, it could slow down, assuming that AGI isn’t waiting like a cat in a corner. But it’ll still displace a tremendous amount of intellectual work.
Still, I think LLMs are different than phones in terms of scaling. Faster processor speeds don’t necessarily result in more user value for phones, but scaling up LLMs seem to predictability improve performance/accuracy.
what exactly is performance/accuracy in slogan generation?
currently using it like driving a junior programmer.
after gpt has written some functions to my specs in natural language. I can say for example: - "add unit tests". It writes for all functions tests. Not perfect but not bad for short instruction like this. - rewrite x to include y etc
When someone mentioned predictability/accuracy how does that apply to marketing slogans. I know how it applies to writing unit tests. The unit tests writing comes pretty close to the original posters definition of GPT as filling out templates. The sucky slogans I got were also very template like.
Would accuracy be if slogans did not suck?
At any rate there seems to be a lot of things people want to use it for where the terms accuracy / predictability don't make much sense. So making claims based on those qualities naturally causes me to ask how do they apply to all these cases - such as slogan generation where accuracy predictability are not normally metrics that apply.
Isn't this always the case before hitting diminishing returns?
Sure about that? GTP-4 doesn't seem 5 times better than 3, much less 10x. Despite having 5/10x the parameters.
it's just it's different in capabilities. chatgpt delivers different results and both have unique characteristics.
gpt4 being able to not only create images but also decipher what's in then is another huge advancement.
Gen2 another ai can create amazing videos from a text prompt. Any director or film maker wannabe with more prowess on creating the story than filming it, can now just use ai to create the film from their vision.
even more exciting is the speed that things are progressing. it was supposed to take 8 years to get chatGPT quality training down to 400k price instead of millions. Stanford did it in 6 weeks with llama and alpaca. it can run for under 600 or slower on home PCs.
I don't know about the future, but by analogy with the past I would say that GPT-3 was the original iPhone (neat tech demo but I didn't really care), ChatGPT is the iPhone 3G, and GPT-4 is the 3GS.
Looking at the sales graphs on Wikipedia (Q1 2012) I think it took until the 4S to transition from "the next big thing" to "the big thing".
Analogies only rhyme rather than replicate, so don't assume GPT needs exactly two more versions to do the same; might be more, might be less, and Uncanny Valley might trigger a Butlerian Jihad at the last possible moment before fully-general AGI.
Similarly, the original iPod was a not obviously remarkable pocket music player in a fairly crowded field.
Like self driving cars, the leap were enormous until they hit a wall and we still don't have full self driving
A little better but a lot “safer” to cut down on the articles on how it’s trying to steal someone’s man.
We were a bit blown away with 'Siri' - I mean, it could understand what you said, and 'get the weather'.
I think we're going to start feeling the limits of this soon.
It will be pervasive though.
GPT3 is great, but I can't reasonably say that 4 is such a huge advance over 3 in my experience so far. Apparently it's better at some things according to the marketing, but for actual usage I can't qualitatively say 4 is an "enormous" advance over 3. It seems to face the same major shortcomings, and it produces qualitatively the same results.
That brings me to the iPhone bit. Yes, the iPhone was a huge advance, but today looking at an iPhone 14, it largely has the same form/function/features as early iPhones. If you looked at the trajectory of iPhones in 2005, you'd conclude that in 2023 they would be 1mm think and transparent with a holodisplay or something. But instead, in the year 2023, my iPhone 14 looks and functions largely like my old iPhone 4. I mean, it does more stuff better, but I'm still using it to browse the net, text, take pictures, and use the maps app -- the same stuff that made the original iPhone revolutionary.
Well, on the other hand, iPhone 14 isn't that different. Same how a 60s car and a modern Tesla aren't that different. Evolutionary marginally better yes. More convenient, yes. But nothing life changing or necessary. Which is why some folks can even get by reverting to a dumb phone (whereas they wouldn't dream of going pre-electricity or pre-antibiotics).
Also, we were hearing the same about VR in the early 90s, and again in the mid 2010s. Still crickets.
Nothing "toy" about it, it was the most advanced phone on the market. The people who laughed were just the handful of idiots that would laugh because "Apple, har har har" and then go buy the same thing from another vendor. The same kind of Zune buying crowd.
>Today a modern phone is a requirement to be a member of society.
You'd be surprised.
>It is how I pay for things. It is needed for most of my interactions with friends/family. It is the diary of my life, and the repository of my good memories with its near unlimited video/image storage at a quality only dreamed of when the iPhone 1 came out.
None of those are essential, even for a 21st century level lifestyle, some of those are indulgent, others are detrimental. In any case, nothing revolutionary, except if one thinks "I can pay by taking out my phone and pointing it at the gizmo at the cashier" is something far great than "I can pay by getting out my credit card and pointint it at the gizmo at the cashier" (or, god forbid, giving cash and not being tracked).
In no way was the original iphone the most advanced phone on the market. Many other smartphones before it and at the time were way more advanced in features and what they could do. What the first iPhone did was make it easy and accessible to everybody, not just nerds. That was the killer feature which made it take over the world.
There was no iPod level music players on a phone before the iPhone. There were crappy music players you can revisit and compare.
Mail apps on phones were crap.
Messaging was crap, in tiny little screens.
Just a few things.
People reviewing and getting the iPhone the time was wowed and think of it like magic. It's people not having it, and dismissing it outhand because it had a touch screen or because their unusable Windows ME phone had some crappy third party software that didn't get it. Of course all of those got either the iPhone or an Android clone of it very soon and never looked back.
iPhone couldn't take videos as people have already mentioned, couldn't install any 3rd party apps to start with (because Mr. Jobs didn't believe in it), no selfie camera, no torch.
All the iPhone did was streamline people's interaction with the phone, with a large multi-touch display and a simple, intuitive (not anymore though) operating system. They definitely improved things, but in the way that Apple usually does; wait for other companies to do the things, then take the cream of the crop, iterate/improve on them, wrap them up/lock into ecosystem (which some people like) and ship.
Most people in 2006, just before the iPhone came out, didn't have copy and paste either. They still typed T9 style like it was 1996.
It showed the way forward, but it was a frustratingly limited device and everyone around at the time recognized that immediately.
Can we just accept that these are opinions? I also waited in line for the first iPhone, and it was by far better than any other phone I owned at the time. True, I was not a "CrackBerry" addict as was common for a certain class of worker in the 00s, but the ability to browse the "real" web in a way that was not completely hobbled was just night and day better than other phones at the time.
At that point around 2007, that vast majority of time I was in range of WiFi: at home, at work, or at a place with public wifi like a coffee shop/library. Totally agree that the 2.5 G made everything super slow, but honestly, in retrospect, that almost seems like a feature vs a bug. I would only pull out my phone on a cell connection for very targeted actions, e.g. pulling up maps, looking for phone numbers or business hours of operation, sending/reading email (as email was a batch operation the slow connection didn't have too much on an impact), etc. Point being that since it was a "costly" endeavor, I would only use it for things I was really intentional about. Versus now, when I'll pull out my phone at the slightest twinge of boredom and scroll, scroll, scroll through HN, Facebook, etc.
"toy" doesn't have to mean cheap or low-tech.
The point is that at the time, a lot of people didn't really believe that phones could be that revolutionary - and laugh at the iphone because compared to the blackberry, it has next to no functionality.
I’m actually getting rid of the cell-phone plan on my iPhone, keeping it as WiFi only, and getting a dumb phone for calls. It may suck but I’m trying it as a 6 month experiment, so we’ll see!
On the other hand nuclear fusion, self-driving cars, and bitcoin were the things to change the world as we know it in the next decade or so.
Things that change the world tend to be hard to recognize as such when we first see them.
Yes there were other “smart” phones at the time but it truly felt like social media blew up in size with the introduction of the iPhone. And that was revolutionary.
Ask ChatGPT: “Assume the perspective of an expert in CS and Deep Learning. What are the scaling characteristic (use LLMs and Transformer models if you need to be specific) of deep learning ? Expect answer in terms of Big O notation. Tabulate results in two rows, respectively “training” and “inference”. For columns, provide scaling characteristic for CPU, IO, Network, Disk Space, and time. ”
This should get you big Os for n being the size of input (i.e. context size). You can then ask for follow up with n being the model size.
Spoiler, the best scaling number in that entire estimate set is quadratic. Be “scared” when a breakthrough in model architecture and pipeline gets near linear.
ie even more foundational for everything that's coming in the future. ai will be as essential as electricity.
On the other hand, perhaps AI could help with due diligence types of inquiries from an independent standpoint? A real-time online AI research assistant with web scraping capabilities would be interesting.
Marketplace reviews are well guardable in terms of that you need to have an account there that purchased the same sku.*
Expert person reviews are based on trust. There is a destructive correlations between spaming Ai reviews and creating a valuable brand as an expert person. So you cannot really do a hard play on ai here, maybe a soft one but that would arguably be just "going with the times".
* Some might ask "why does amazon still have issues with review spam?" Answer is that amazon actually has a pretty firm grip on it, nonetheless the marketplace's incentives seem to be such that some slippage is acceptable/helpful for them.
A marketing agency would have spent at least a few weeks gathering specific information about your company, the article allotted two minutes.
How many more minutes would you need to devote to giving ChatGPT more specific information before it could match the marketing agency's output? Not weeks surely. What's the cost difference in both time and money? Multiple orders of magnitude.
I can literally tell it “write me basic code to do ‘x,’ now explain how to add it to my squarespace site.” In many cases it will just spit out exactly what to do. As we all know, part of knowing how to do your job well is knowing how to find answers. In some ways chat GPT makes that step even easier. At least in the use cases I have found so far.
You'd be. Most people wouldn't even notice or care, whether it's the ones paying the marketing agency, or the ones being shown the content as potential customers.
GPT generated "ideas" strike as wanting to use a swipe file. Only instead of it being full of persuasive, high-performing marketing materials.. it's just fast and prolific
But you didn't. You paid only a few cents. You're probably not using it for a million dollars ad campaign but many people could use it to make their communications look better in less time. Same thing as using a stock PowerPoint template instead of paying an agency to create one. Good enough for most of us.
I'm not sure what a better metaphor is; each thing I consider ends up defaulting back to what a ML model actually is, without really "metaphoring" at all. But not templates.
Yet… we are are talking about a tool that came out literally FOUR MONTHS AGO. And the huge advancement on that came out TWO WEEKS AGO.
Yet everyone here continues to proclaim, “it’s not even that good , honestly.” As though no progress will ever be made from this current moment in time.
I feel like I’m taking crazy pills.
Sure, here is a short story about a computer hacker:
Once upon a time, there was a young hacker named Kevin who loved to explore the world of computers. He was always curious about how things worked, and he loved to find new ways to break into systems. One day, Kevin was exploring a new website when he came across a hidden file. The file contained a list of passwords, and Kevin was curious to see what they were for. He tried a few of the passwords, and to his surprise, they all worked! Kevin had just hacked into a major company's computer system.
Kevin was excited about his discovery, but he also knew that he had done something wrong. He had hacked into a system without permission, and he could get in a lot of trouble. But Kevin couldn't help himself. He was too curious about what he could find in the system. He started exploring the files, and he quickly found out that the company was up to some shady business. They were involved in illegal activities, and Kevin knew that he had to do something to stop them.
Kevin decided to hack into the company's website and post a warning to their customers. He wanted to let them know that the company was not trustworthy, and that they should avoid doing business with them. Kevin knew that his actions would get him in trouble, but he didn't care. He was doing what he thought was right, and he was willing to face the consequences.
The company was furious when they found out what Kevin had done. They threatened to sue him, and they even tried to have him arrested. But Kevin was not afraid. He knew that he had done the right thing, and he was willing to fight for what he believed in.
In the end, Kevin was able to expose the company's illegal activities, and he helped to protect the company's customers. He also learned a valuable lesson about the importance of doing what is right, even when it is difficult.
What this means to me is that if you see the parts of your job that are basically drudgery as being what you're good at then you should worry. If instead you see them as a necessary evil that you have to do in order to accomplish the bigger goals you're aiming for then you should be happy.
I've seen a lot of comments on here like "well LLMs are good at writing snippets, but could never write or maintain large codebases to accomplish a larger goal" - but are you SURE about that 'never' given the current generation is already doing things people suspected they could never do? "But they'll never be able to manage / interpret stakeholders", Are you SURE that LLMs will have to adapt to fit stakeholders, and not the other way round? I don't know for sure, and even if this is coming, I've no idea on the timelines. But I'm not completely writing it off as a possibility anymore either.
That sounds a lot like the self driving cheerleaders five or ten years ago. That work so far has resulted in some awesome features like adaptive cruise control and parking assist but it fell far short of what the hype was promising to deliver by now.
Five or ten years later Mercedes is the only company getting ready to ship level three self driving. Level four and five are still a pipe dream, practically restricted to a few companies like Waymo in a few controlled environments like Phoenix and San Francisco.
GPT4 is great and I can't wait to see what 32K or even 100K/1M token models can do, but I fear we're about to hit the point where progress grinds to a halt because going further requires something closer to AGI than what we have now.
I also don't think the comparison quite works, because no one is saying that we need to get down to zero humans for this to to be profoundly disruptive, just enough humans to code review and make relatively small changes, I wouldn't be amazed if that's what software engineering becomes in the coming decades.
Other objections, such as “if your job can be replaced by an algorithm, you weren’t particularly valuable in the first place” or “software development is much broader than writing code” are irrelevant to the question of whether a large portion of developers will be replaced.
I don’t think they will, given the world’s appetite for software, but it might become a less prestigious and lucrative profession on average.
Longer-term, what we now consider tech skills will be replaced with communication skills and business domain knowledge. This will cause an influx of workers from different professions and walks of life. As the field starts encompassing a broader spectrum of work, the barrier for entry will be lowered, and there’ll be more work and more practitioners.
There will still be high-paid jobs, but on average, software development will become a more traditional middle-class profession.
This is all speculation on my part, of course.
We've been through a number of iterations of the same pipe dream since then, but it always turns out that the actually hard problem in programming is figuring out the requirements in full detail without handwaving and glossing over anything, and translating them into unambiguous instructions. And "workers from different professions and walks of life" just inevitably suck at that.
Whether this time it really is different will hinge on whether LLMs can really figure out the handwavey parts, or whether those will be exactly where they will always make up shit and be confidently wrong.
Even before the recent ML advances, there’s been a shift towards involving a broader, less skilled workforce as the amount of work expands. Hence the people switching careers and getting gainful employment after a few months of even weeks in a coding bootcamp. Don’t think that was as common in the assembly coding days.
So while none of those advances suddenly destroyed the profession, there’s been a gradual change to include a broader spectrum of practicioners. I don’t expect the LLMs to revolutionize the field in two months, but I feel like it’s safe to extrapolate that this is where it’s headed eventually.
I can imagine LLMs becoming a UI in front of just about everything. Instead of googling the ffmpeg flags you need, you’ll just ask your terminal to walk you through it.
maybe not true.
There are many threads where new products got comments of "useless" and then launched. HN users are smart, picky, and not representative for crowds.
https://jalopnik.com/elon-musk-promises-full-self-driving-ne...
ChatGPT is a giant step forward in the journey towards AGI. Tesla’s cars, for all their flaws, are big steps forward in EVs and even self-driving.
I personally find that exciting enough.
Honestly, I feel the opposite. I'm sick of the endless fawning over ChatGPT because it can print code that exists in a stackoverflow answer somewhere.
I'm also cautious about extrapolating. Constant improvement, let alone exponential, is far from a guarantee, but from what the LLM acolytes would have you believe it's pretty much a given that GPT6 will be an AGI before 2030.
I think the sentiment is warranted in some contexts, but in others it just seems dismissive.
For instance, I am not impressed by ChatGPT's code output. It seems to be incapable of understanding the nuance that is required to modify known or similar solutions to fit a novel problem. In that sense, I don't think it's doing much more than a search engine. It could be it just hasn't had enough training examples. It could also be that there is something uniquely more difficult in regards to solving novel problems via code (I doubt this).
But to get a marketing campaign and a website (albeit in mediocre quality) from text prompts is truly amazing imo. A lot of people are missing the point that these models are in the toddler stage of their life.
If you gave an idiot something very intelligent to say and he read it out loud perfectly, people might be very impressed too. That’s GPT.
And when something gives the increasingly-accurate illusion of knowing, I fail to see how it matters (with regard to impact on society and overall utility).
I’m not saying GPT-4 is this amazingly accurate, near perfect model. But if you extend the timeline a bit, it’ll be able to become more and more accurate across a broader range of domains.
Furthermore, how can we prove a human “knows” something?
When I write code, I don’t just focus on solving the problem at hand, I think about things like, like: how will another human interpret this, how maintainable will this be, what are the pitfalls down the line, what are the consequences of this, any side effects, performance implications, costs, etc… things GPT does not know.
And your point about humans lying about knowledge only to be found inexperienced is quite the opposite of an LLM (albeit there is the hallucination problem, but GPT-4 is a massive improvement there):
These models do have “experience” aka their training data. And I would argue with most every one of your examples of things that GPT doesn’t know.
You can ask it about performance implications, side effects, costs. It’s quite good at all that right now even! Imagine the future just a few years out.
There is no “getting better” from this. If you gave a monkey a type writer and it occasionally typed words randomly you wouldn’t say “Wow this is just what it can do now, imagine several years out!”
Comparing GPT-4 to a monkey with a typewriter , and claiming the absolute of “there’s no getting better from this” when we’ve literally seen dramatic progress in just months?
I think you’re missing out on some of the utility this stuff can actually provide .
And it will never do those things, because it’s an LLM and there are limits to what LLMs can do. There is no “getting better”, it will only sound better.
If it’s going to replace programming, the prompts simply cannot be more laborious than writing the damn code yourself in the first place.
LLMs are just the part of a much larger looping system that can do these things you speak of. Be active and seek out stuff. Of course, it’s all illusory, but I’m sorry I think it’s no different with myself.
By the way, it actually gives ok reviews on novel code, so I’m not sure what you mean. At some point nothing is truly novel, even innovation is composing existing “patterns” (at whatever abstraction level).
So thinking that chatGTP could gain understanding is as crazy as the idea that primates could learn to use tools or type words?
Could GPT be given some screenshots of a game you want to play and then code it up?
Could you run through a demo of some competitor’s app and have it make something similar but better?
Everyone repeats the retort you gave, yet I’ve yet to see a clear definition of “knowing”.
If an AI reliably produces good code in response to prompts, it is a better program than most humans. If an AI reliably produces prose that's free of errors, well organized, and summarizes the issues asked for, it is a good writer. Irrespective of what we can say it "knows" or doesn't know.
The issue is that the folks promoting chatGPT are for the most part incredibly dishonest. E.g. this entire blog post is about the AI having written a sales email, with zero written about how well it actually converted. The author is claiming that the AI can do a superhuman amount of work in 30 minutes, but we don't actually know if it did any work at all.
How can we even know whether OpenAI is making progress if we don't know how good it is in its current state? Back when Go AI was far less good than even the average club player, we at least knew what rank the AI was playing at. Whereas right now the ChatGPT equivalent is basically that it's putting stones on the board in a way that looks somewhat like a real game, but you're not allowed to know what level it's playing at.
“All I had to do is search for a sample product launch email and POOF it appeared! Just had to fill in the company name.”
It’s the same thing with the minor code snippets being “written” by Chat GPT. Any real programmer knows that Google could give you pretty much the same thing. And they also know how complicated their actual job is that goes well beyond the simple prompts people are using that everyone has been googling for over a decade now.
It’s all hyperbole. This technology is just an evolutionary improvement on Google.
If y'all have been focusing on GPT-4 coding abilities, I ask you to try it with literature-based prompts. GPT-4 is an exceptional writer, summarizer, and style corrector.
Sorry but it's just frustrating seeing "how can we know it's better?" when it's right f-ing there in front of you. Maybe you don't want to spend $20USD to try it out, fine whatever, wait until it's free to use but don't make lazy negative remarks from a place of ignorance.
I feel the same way but on the other side. All I see are non-technical or quasi-technical people using AI tools to perform work that is x% better than Google could do.
The only entity at risk of being displaced from this technology for the foreseeable future is Google.
The only thing left to discern is what % better this technology is than Google’s antiquated algorithms.
Think about it for a second. Putting the right query into Google could give similar templated results. This technology is just an evolutionary improvement on that.
Yes. A lot.
Last I checked I can't ask Google to invent a new programming language specification for me
I have literally never done this in my job. Ever. I've been a professional software developer for multiple decades.
I then asked it to write a short tutorial for that language in the style of Learn X in Y minutes
So you can't Google, "Tutorial How to Learn X in Y minutes", get a result that has a completely viable format and details and then do the remaining 15% of the work to fill in your specific items?
I then asked it to write bubble sort in the new language and got a result
Do you know how many times I've written a bubble sort in my actual software profession?
The use cases you're bringing up is very typical of what people bring up with GPT-4. Contrived stuff without real-world application or something that is an evolutionary improvement on Google.
Overinflated claims of what GPT-4 can do causes real harm to our industry. There are business owners making decisions now based on the smoke and mirror demos that people are showing that has convinced them that they won't need developers in a few years. I literally met with a computer science major who was considering switching majors because of GPT-4.
Over the next decade, GPT-4 will be an amazing productivity enhancer for actual software engineers. Just like Google has been but with significant improvements.
If they aren't doing their due diligence on this then that's their problem. If my example isn't good enough then provide one of your own that you couldn't get to work.
Regardless, I’d argue that GPT-4 is actually far better at programming assistance, understanding concepts (it’s phenomenal at explaining things when prompted within a context), writing in general, and kick-starting creative pursuits than it is being a Google-replacement (for now, at least).
Have you seen or used GPT-4? What has your experience been? What has it failed at, or rather, what would you wish to see in such a system that might make you to, “huh, ok — that is pretty cool.”
But the fact that you feel the exact opposite shows that maybe this is just an artifact of cognitive bias.
What has your experience with GPT been? For me, GPT-3 was not really useful as a software dev.
But GPT-4 is miles ahead of that. It’s helped me write code maybe 4-8x faster than usual, and has even allowed me to debug existing issues far, far quicker and more accurately than I’d ever be able to on my own.
Part of the gap very well might be my own mediocrity with development . I wouldn’t argue that folks with far superior skills and novel challenges day-to-day might be unimpressed.
But as an average dev writing pretty boring code (REST APIs and system integration mostly), I’ve been blown away by GPT-4. I am pretty well compensated and have been in the field for 10 years, too; but I am aware of my own shortcomings.
Or social media/advertising engagement algorithms doing their work. After all, you get more engagement with negative emotions than positive ones.
It seems plausible that you and the OP are at least slightly on different sides of the LLM issue, and so you and the OP could literally be seeing two different realities crafted by engagement algorithms, because it detects that each of you pay more attention to the other side that you disagree with, and that snowballs into seeing only the other side and thinking you're taking crazy pills.
Like, I might ask "using this library, implement that feature" in the hopes that there it has learned of some way to do a thing I haven't been able to figure out. In those cases I see it hallucinate, which I assume means it's just combining information from multiple distinct environments.
If I'm not too specific, it does a pretty good job.
IMO its biggest fault is that it is not good at admitting it doesn't know something. If they can crank up the minimum confidence values (or whatever, the values used to guess the next token), maybe we'll see better results.
We must be reading different HN. This is not at all what I'm seeing. As of now, the first comment I'm seeing which is dismissive is the sixth from the top, while your comment is second from the top.
Ask an HN person if the website is pro-spaceman and anti-spaceman. A lot of people feel very strongly about one way or the other.
Remember how 3D printing was supposed to be ubiquitous by now? Or how self-driving cars would lead to an economic apocalypse because of how reliant the economy is on truckers? Remember all the predictions of bitcoin going to $100k? Remember how an AI startup called “The Grid” was making news for their AI website builder back in 2016 (edit: 2014)?
Don’t even get me started on VR and mixed reality. Remember Magic Leap?
My takeaway from all this, other than that futurists are hucksters, is that progress is actually quite slow, and relies on sudden, unpredictable breakthroughs. I mean, without the iPhone, we arguably wouldn’t have smartphone apps, the death of Flash, or responsive websites. Arguably, without this single pivotal product, tech as we know it would be a very different place. I know it’s a stretch to some to call the iPhone a breakthrough, but it’s impact has been pretty huge.
The catch is knowing when something is a real breakthrough, and when it isn’t. I genuinely thought that the Oculus was at the time, and yet here we are, years later, and it seems like nothing has changed, aside from incremental improvements in VR display technology and a very niche VR gaming community.
GPT-4 is clearly impressive from a technical standpoint, useful even, but where does it really go from here? Does the technology take off, or does it plateau in its present state?
Is it VR and 3D printers all over again?
As a non-expert in the field I was hesitant last year to disagree with the legions of experts who denounced Blake Lemoine and his claims about Google's AI being alive. I know enough to know, though, of the AI effect <https://en.wikipedia.org/wiki/AI_effect>, a longstanding tradition/bad habit of advances being dismissed by those in the field itself as "not real AI". Anyone, expert or not, in 1950, 1960, or even 1970 who was told that before the turn of the century a computer would defeat the world chess champion would conclude that said feat must have come as part of a breakthrough in AGI. Same if told that by 2015 many people would have in their homes, and carry around in their pockets, devices that can respond to spoken queries on a variety of topics.
To put another way, I was hesitant to be as self-assuredly certain about how to define consciousness, intelligence, and sentience—and what it takes for them to emerge—as the experts who denounced Lemoine. The recent GPT breakthroughs have made me more so.
I found this recent Sabine Hossenfelder video interesting. <https://www.youtube.com/watch?v=cP5zGh2fui0>
ChatGPT is not a tool with which you can build a bigger moat. Huge amounts of money are going to be made in the short term, but in the long term, I think your work being amenable to aid or replacement by LLMs is an indication you should be looking for higher ground, even if it's just to survive some plausible AI Winter.
It is accelerating technological evolution. Meaning there is no island of stability on the other side. There is no adaption to change and then we move along for a while. It is continuous. What makes this disruption different than all others is AI is not a narrow disruption. It is a disruption for everything because at its core it is a machine for the replication of skill and technology. A concept that has never existed prior with any other technological disruption.
I've described this somewhat as the shrinking innovation, disruption and adaption cycles that leave us completely unable to keep up.
"Climbing the skill ladder is going to look more like running on a treadmill at the gym. No matter how fast you run, you aren’t moving, AI is still right behind you learning everything that you can do."
But if you use it as a coach/consultant/pair-programmer/R&D exploration/ brainstorming session, then you have instant access to an "expert" in any field.
That's something that can supercharge the productive output of any worker. And/or lead to dismissal of most of the team...
So much human activity is about structuring our own thoughts so we can ascend to a higher level of activity and insight.
I mean everyone knows marketing plans are BS but they're part of a process of group thought.
I am genuinely amazed at some of the chats I've had with AI but I hope the outcome will simply be a clarification of what we are all actually doing.
If we don't share the gains, then overall I see this as possibly being a loss for society.
Not gonna lie, it's kinda fatiguing seeing people hype lazily generated AI content as really good, when it's more often than not mediocre. I don't know if it's because people are intentionally hyping their results, or if they have poor taste/standards.
I think the real lesson here is less is more, and I'm afraid with generative AI there's gonna be so much churn of content, we'll all become fatigued.
https://www.theverge.com/2019/7/2/19063562/ai-text-generatio...
https://www.theverge.com/2023/1/19/23562966/cnet-ai-written-...
The website doesn't look great. The emails are a bit generic. But we are in the very early stages of these models. I think the fact that a website can be generated from text prompts is remarkable.
I wouldn't scold my toddler for not walking very steadily.
Sure all the content is mediocre - but it's enough to start, and you could choose where to invest your budget - video editing, artwork, web site - to improve on this stuff that is an actual poc - in half an hour?
For example, I’d trust 1 video review over 1000 text reviews, and even then, a family member’s opinion over 1000 video reviews. The number of “agendas” out there is staggering, and it feels naive to assume that most of them would align with mine.
Cool, so lets see what Bing spits out.
> I’m sorry but I’m not able to create a document that outlines an email marketing campaign and a single webpage to promote the game. However, I can suggest some steps that you can follow to create an email marketing campaign and a single webpage to promote the game.
> snip
---------
What the hell is up with this? I copy/paste the prompts exactly as outlined in this blogpost, and I get completely different results.
I know I'm not the only one having this issue. But it makes me extremely distrustful of these blog posts. If I can't replicate their prompts or how they work, how the hell am I supposed to believe them?
And yes, I did start with: "Look up the business simulation market. Look up Wharton Interactive's Saturn Parable" as prompt#1, so that Bing/ChatGPT already had Saturn Parable "in its memory".
-------
EDIT: I tried these two prompts in "Creative Bing Chat mode". I got the first sentence out of Bing Chat, but the rest of it failed. There must have been a timeout of some kind, because Bing Chat just hangs and fails.
Especially if the models grow quicker with realtime data.
I know this thing isn't deterministic. But never have I even gotten past step 2 of this blog post.
I dunno. Has anyone else gotten the prompts to work as the blog post alleges? If so, can you share your prompts?
Superficially it does that, but that would be the case edge-wise if ChatGPT was just available to you. You have no business advantage because of it over anyone else using it.
What it does do, is devalue your skills (if you had the skills before to manually create all that material), and devalue the final product.
Once, having such online marketing material used to be a great asset, even if it was crudely made by today's standards (think 1996). Later, as there were all kinds of services to help create one (with assets, etc.), more people that could do it for cheaper, template-based website builders and so on, it was far less valuable. Now, with ChatGPT churning good-enough material in 30 minutes, it would be as valuable as spam.
In fact, there will be (already is) an entirely huge industry of automated AI spam content, including fake companies with marketing material. Not the hand/template build of today, where someone has made 30-50 slightly different BS companies to e.g. scam or drop-ship. But where every scam artist can have 1000s of them within an hour, and get them be topical on the latest products and trends, complete with "chat support" and everything. And of course any person who has some BS idea, but couldn't even use Wix to make a website before, even less so to write copy for it, now will have one (they'd probably wont be able to use ChatGPT directly, but they'd be able to use a turnkey "make me a website" GPT-powered version of something like Wix.
The bussiness advantage of using GPT to boost your productivity is like getting rich by the UN giving everybody on earth 100 billion dollars!
Force multiplier is not equal to quality multiplier, and the availability of the tools will generate mediocre junk with the speed of the light. Soon we will have to add to our information journeys another blocker for the A.I. generated marketing content.
After seeing Developers gainfully employed, justifying their horrible SQL as, "I dont know the ORM wrote it". Others mentioning they never heard about transaction isolation levels, the old mantra of "NodeJS never blocks" so your concurrency issues are gone. Even recently and incredibly, having to argue with somebody about a Cloud Architecture design where as surprisingly as it might seem, the argument from the other side at a moment was, "but ChatGPT says..."...Taking all this into account I strongly recommend you keep brushing your skills.
I predict Consultants and Developers, able to fix the bugs in these ChatGPT Driven Development Applications, will be rewarded with hourly rates that will make FAANG salaries look like Monopoly money...
It's a huge boon, but nothing is perfect. If it's that important that absolutely nothing is missed, maybe try multiple approaches concurrently. Take this as a value add, not a replacement.
I'm not a lawyer, so when I search British copyright law, I wonder why those forms of words don't result in the staff of search engines and social media sites being arrested and imprisoned:
https://www.gov.uk/government/publications/intellectual-prop...
Although, probably best to ask a lawyer for legal advice even if they end up using GPT-n themselves; they've probably got public liability insurance if they get something wrong.
AI can figure out from context, a keyword search will miss it. And no, you don't know the "code words".
My experience so far has just been asking chatgpt questions and then researching it myself to confirm what it says, so maybe I'm missing something. But, it has been confidently wrong on important details a large enough percentage (right now) to make it absolutely not a fire and forget tool.
The worst part is the confidence: it's like having a coworker that just straight up lies to your face randomly. Even if it's only 5% of the time you basically can't trust anything they say, and so you need to double check all of it.
This doesn't make it useless, but it means it lends itself to "hard to do but easy to verify" tasks. Which afaict your example is not: you can verify the documents it picked out are relevant, but not that the documents that it didn't, weren't.
* their reputation with respect to the question domain (if I ask a basic C++ question to a C++ expert I'll trust them)
* their own communicated confidence and how good they are at seeing their own shortcomings (if they say "but don't quote me on that, better ask this other person who knows more" it's fine)
5% of bad answers doesn't matter if 99% of these times I knew I should look further. ChatGPT and others are missing this confidence indicator, and they seem to answer just as confidently no matter what.
To be clear I don't see a fundamental reason why LLMs couldn't compute some measure of confidence (which will itself be wrong from time to time but with less impact) so I expect this to be solved eventually.
I turn on a 'certain kind' of Movie or TV show and it becomes apparent that the scriptwriter really isn't an FBI agent, or Doctor or IT person. They have a feature length story, with amazing CGI, lighting, 4k video and Dolby...but the writing isn't believable and the end product is shit.
I'm wondering if this will allow more people do more things, but the things that are turned out will look average, and the people that dedicate the time learning and skill to %product% will still turn out things that stand out.
I have a similar old man gripe about CGI and music...the end result is that many more people have the ability to do the thing, and the end result is that the thing becomes commonplace and loses some of the wonder as a result. You have more and more and more people turning out music, and as a result, more and more people can't make a living making music.
Have you watched nerdforge? “I spent 1, 10 and 100 hours on X…”
Excellent content. High rated. Highly successful.
Here’s the thing: yes. Spending 40 seconds clicking on the “generate image” button can indeed produce some random crap.
…but, I’ve already seen that. I’ve done it. Here’s a pro tip: any content that takes you 30 minutes to do is something almost no one is interested in.
It’s too trivial.
So, here my challenge: ok, now go and spend 10 and 100 hours to see how far you can actually take it if you devote real effort to using these tools to actually do something.
It might get a few clicks today, but the barrier to spending 30 minutes to generate this kind of stuff has become so low that it’s basically worthless.
We get it. You can click on the generate content button.
Does it scale? Can it generate prompts for itself when you don’t have time to do it yourself? Can you refine the content so it’s not so bland and generic?
…or is that a problem for GPT5?
“ChatGPT, please update the website to the latest meme framework”
And with that they were all obsolete
Humans are good at coming with good explanations.
There is nothing super human about generating a lot of crap marketing noise in 30 minutes.
I think the pace of AI advances may turn these disruptions into long-term issues and not lead to employment growth.
Yes, ChatGPT can be a multiplier on human productivity. But that's assuming you can learn how to use it correctly. The author here seems to know how to scale the complexity of the prompts in such a way that they get meaningful output (a complete website). That sort of prompting is a skillset in itself.
The problem as I see it is: how long is that skillset relevant before an even more advanced LLM comes along, forcing you to re-learn how to interact with it. Now consider that the next advancement need not come from an LLM, but some entirely different system that doesn't work via prompts. That skilled prompter needs a new skillset.
Technological innovations of the past have always come slowly enough that people could learn and master them before something new came along. It seems like things are moving so quickly in the AI space that may no longer be true.
With all that said, an example that gives me hope is chess. The rise of chess AI's has not killed chess in any sense. The players of the last few years are actually much stronger than pre-AI. Can the best players in the world beat Stockfish or Alpha-Go? Not even close. And so far that hasn't mattered. People still prefer to watch two human players.
But I feel underwhelmed everytime I see people coming up with examples about how LLMs are going to revolutionize the job market.
Prototypes for sites are something very old, it's not that you have not been able to create a good looking mock site in record time in the last 10 years. The rest of the article is also underwhelming, AI for generating content for a marketing strategy is not impressing honestly, and I guess that similar tools already existed.
AI answer: More ram is better. Computer go faster with bigger files and less swap. Business needs demand. (Useless answer)
What the boss wants: I assess that software X requires 32gb to perform the task we need. We tried with 8, hard fail. We tried with 16 and it crashed every 30min. And we havent asked for new laptops in years so you owe us.
"Dear [Boss's name],
I hope this email finds you well. I am writing to request your approval for the purchase of 3 laptops with 32GB RAM.
As you are aware, we have been experiencing frequent software crashes, particularly on laptops with 8GB of RAM, and even on those with 16GB of RAM. This is affecting our productivity and causing delays in our work. Additionally, our current laptops are several years old and require frequent maintenance.
To address these issues and ensure that we can work efficiently and effectively, I believe it is essential that we invest in new laptops with increased RAM capacity. With 32GB of RAM, we will be able to run our software smoothly and reduce the frequency of crashes.
I have researched several options and identified three laptops that meet our requirements and are within our budget. I have attached the details and prices of each laptop for your review.
I would appreciate your prompt approval for this purchase so that we can continue to work without interruptions and complete our projects within the given timeline.
Thank you for your attention to this matter.
Best regards, [Your Name]"
This is typical of generalize AI. Everything it writes sounds like it comes from a total stranger. It has no internal voice, no distinct style. It sounds like it comes from a child writing an essay ... which is basically what it is.
I don't know if I'll feel the same way tomorrow; just thought it was a perspective worth sharing.
With respect to the ongoing argument about the social and economic disruption of this “tool,” we need to remember this:
Over short periods of time, we “feel” like the slope of change is relatively flat. But it’s not. The slope of change is getting steeper and steeper ever day. Technology change and capability is exponential.
I have seen a crazy amount of change in my lifetime, and it’s accelerating.
I recommend him as a follow: https://twitter.com/emollick/status/1636454151272931337
It’s helpful and I wouldn’t have the energy to work on this hobby project without GPT. But for now at least, at some point I have to understand every line of non-trivial code eventually.
I wonder how quickly we gonna put any ML-generated email directly to spam folder? I personally would like to have at least a marking of such content in my inbox.
I have seen myself visiting much fewer websites after I incorporated chatgpt in my workflows. why would I visit some random dev blog that promises me an answer, when I don't need to? and now I don't have to be annoyed by that pesky popup asking me to suvscribe.
it will be the same with marketing. it might be easier to create the content, but way fewer people will even see it.
it is gong to be interesting to see if there will be an implosion of more a fizz out.
it is also going to be interesting to see how marketers will target LLMs.
I doubt AI can find these recipients and that's the most critical element.
Regardless of the role... GPT as a helping tool, absolutely!
But as a replacement for the role... You're setting yourself as a joke.
That's the problem with this stuff: it's formulaic, unimaginative, etc. Like a lot of real world marketing. If you look at what companies actually do, it's mostly pretty low quality and bad right now. For every well run marketing campaign there are hundreds of really poorly thought out and cringe worthy campaigns. Trying to imitate what the good ones do.
So, AI is going to run circles around that crowd. Just like any competent marketing person would. Except an AI will do it a lot cheaper. This is going to decimate the market for incompetent charlatans and create a new market for effective directors that can work the tools more effectively and cheaply.
That kind of is the point. These tools are really effective in the hands of a skilled professional that knows what to ask for and has a notion of what good and bad look like. It's an iterative process of asking and refining and directing that allows them to take a lot of short cuts.
Imagine Steven Spielberg directing a movie. But without the actors, camera people, post production, makeup, lights, CGI, and all the rest. That kind of is what this could be. How would somebody like that use AI to produce a movie. Well, he'd be directing and refining and iterating and be getting results a lot quicker than is possible now. Maybe he'd raise the ambition level a little and ask for things that are really hard right now. But in the end they'd produce a movie that is hopefully very entertaining and interesting to watch.
Now imagine a young inexperienced director with some vague ambition to be a better director. Would that person be able to produce something with the tools. Sure. And they'd learn a lot in the process. As you iterate, you better yourself. It's not a one way street. The more you engage with some activity, they better you get at it. We'll have a lot of very skilled directors in a few years. And they won't just be directing movies.
And now imagine a very cynical third rate director that produces straight to dvd content for the masses. No budget, hilariously bad scripts, actors that don't give a shit and can't act, etc. That guy is going to produce some amazing results. But there will be so much of it that it won't have any value.
We will probably have tons of movies with Avatar-like graphics, unfortunately, also with Avatar-like story, since that's really the hard part: encapsulating emotion in the artifact.
Meaning, you might be extinct as banging out code for a living, you might become assisted by the computer and focus on higher tasks like architecture design, communications and ... probably, rewriting half of what the AI did.
When I started, being a web developer was NOT a thing! There were some classical graphic designers that came from Print and started doing web stuff, and it was regarded like a dirty work.
Even today a lot of system developers will look at web developers and say this isn't programming.
Things are in flux, always, so embrace the change, don't deny it, and trust that there will always be something to be adding value to later on. The worst thing you can do is become a denier of change and lock yourself up.
That said, a certain common sense is required, like jumping off the band wagon and calling yourself a web3 crypto bro developer isn't going to do much for your resume. So sit tight, admire the show, and learn what you can.