Is the ChatGPT and Bing AI boom already over?

https://www.vox.com/technology/2023/8/19/23837705/openai-chatgpt-microsoft-bing-google-generating-less-interest

by kristianp • 3 years ago

48 69 3 years ago

ph4evers2• 3 years ago

Doesn’t seem to be “over”, I know many people that use it on a daily basis. The initial hype might be cooling off a bit which is not strange.

arkitaip• 3 years ago

I use it several times per week. It's a tool with its time and place, not a magical wand that will replace any effort and thinking.

ph4evers2• 3 years ago

I agree, after a while you get a feeling for its pros and cons and how to leverage it.

t0mas88• 3 years ago

The big hype "anything can be done by ChatGPT" was never going to last long.

The next step will be embedding these models in other products as practical tools (for example automatically summarising things) and they become part of day to day usage. That's already happening.

dbg31415• 3 years ago

Remember when tesla told us their cars could drive themselves?

Then, like five years later, they still weren’t really driving themselves. (=

AI feels sort of like that.

ChatGPT is fun, but gets as much wrong as it gets right.

The only things I consistently use it for are rewriting my emails in different tones and to summarize large documents / emails that I don’t feel like reading.

numbers_guy• 3 years ago

But ChatGPT is already useful if you use it correctly. I don't try to make it write my code. I use it as an expert knowledge system. If I need a specific BASH command or I want to figure out how to do something in some badly documented but widely used API, I just ask it and it gives me good hints.

quonn• 3 years ago

This is spot on, I also use it to write bash scripts where I could never remember the exact syntax to accomplish a task.

wudangmonk• 3 years ago

This reflects my experience with it so far but I see so many claims of multiplicative "productivity" boosts but there's always a lack of concrete examples of what this means. Avoiding a quick google/stack overflow search is not my definition of productivity boosts.

ChatGPT is useful for generating text that look okay at a distance. I can see the use for creating low quality content to drive traffic to a website, something like medium.

For coding its not useful for any language you are proficient in. There is just so much hype around it but I just can't find the usecase for it.

ttctciyf• 3 years ago

I just can't find the usecase for it

Evidently: for coding in languages you are not proficient in! What could go wrong?

danielbln2• 3 years ago

Every HN thread has plenty of examples, refactoring/extending/explain8 code, structuring text, knowledge summary and so on. Where do you guys live that you are still looking for the plethora usecases that people are using this tech for?!

vouaobrasil4• 3 years ago

This is my opinion as a professional content creator: of course, the boom is over, if by 'boom' you mean the frenzy generated on the internet. But, the ONLY reason why this is true is because nowadays the internet functions on trends. It was always true that people followed trends, but the difference between attention to any one trend between when it first becomes trendy and mere days later is far greater than it's ever been.

On the other hand, the economic and social impact of AI has only just begun. Now it will move more quietly to slowly integrate itself in society like a virus, making us more and more dependent on AI.

This integration will push us to becoming more like automatons, needing people less, and further concentrating the wealth of the world towards Silicon Valley, because it will create a worldwide addiction and dependency on something we never needed in the first place.

chii• 3 years ago

slowly integrate itself in society like a virus, making us more and more dependent on AI

so you could say the same for electricity. And yet i dont see you calling it a virus!

needing people less

no, needing people to do less isn't the outcome. The same amount of people can now produce _even_ more. Just like having tractors pushed out farmers that used to hire lots of manual labour.

It's a good outcome in the long term. It sucks for those who get displaced - but the train of technological progress runs over tracks made of the bones of those it displaces. this has always been the case in history, and will continue to be until the day we reach post-scarcity.

vouaobrasil4• 3 years ago

so you could say the same for electricity. And yet i dont see you calling it a virus!

It is like a virus in a way.

no, needing people to do less isn't the outcome. The same amount of people can now produce _even_ more. Just like having tractors pushed out farmers that used to hire lots of manual labour.

We have reached the point of diminishing returns when it comes to technological development. We do NOT need to produce more things more efficiently. That only leads to more resource usage, which this planet can no longer accommodate.

Instead, we need to concentrate on sustainability rather than productivity.

It's a good outcome in the long term. It sucks for those who get displaced - but the train of technological progress runs over tracks made of the bones of those it displaces. this has always been the case in history, and will continue to be until the day we reach post-scarcity.

If we go down that route, we will use up too many resources. We should not aim for post-scarcity, but rather post-productivity. Technology is no longer making the world better, it's making it worse. If you live in a city, simply look out the window. We're destroying our planet all in the name of endless economic growth, which is only making us slaves to the technological machine.

rvz2• 3 years ago

In this AI cycle, we are now currently at the late stage peak of inflated expectations in the Gartner hype cycle.

There is going to be a ton of losers with the incumbent big tech companies ending up as the winners.

danielbln2• 3 years ago

Weekly reminder to not take Gartner's hype cycle as gospel or dogma, it's as much a marketing instrument for Gartner as anything else.

rvz2• 3 years ago

My point still stands.

LASR• 3 years ago

It’s getting started. Serious use cases never have the glamour of hype. But I am starting to see generative AI cover more and more ground into business utility.

Saying it’s over is like saying that the internet is over after the dotcom bubble burst.

Nah. This is a revolutionizing foundational tech. Bigger than the internet even IMO. More like computerization of business, or the steam engine.

HPMOR• 3 years ago

Completely agree. These foundational models are more akin to the invention of transistors or the internet than anything else. It's a little disheartening from a startup perspective to see already large "incumbents" in the form of Google, Open-AI but I think most of the value created, in the future, from generative AI, will not be captured by these players.

croes2• 3 years ago

The question is if the models can get significantly better or are they already near the peak of their capabilities.

tmikaeld2• 3 years ago

Also, the open source models are getting closer and closer to the (current) closed models.

Hopefully more and more tinkerers are going to fuel this fire even further, making it possible to run AI on-device with custom native chips.

toxik• 3 years ago

Which current public models do you think are getting to ChatGPT levels?

spaceman_20202• 3 years ago

What sort of business use cases are you seeing?

I hang around a lot of solopreneurs and there is a serious cohort of founders/hustlers who are using AI tools to greatly improve their productivity.

Not sure how much of that can carry forth to a major corporation though.

yyt884• 3 years ago

This is a revolutionizing foundational tech. Bigger than the internet even IMO.

Oh is it? Maybe you can tell us then how you'd get the models home without the internet? On a DVD? Or interact with a server that runs the model for you? Or how we'd even be having this discussion?

People said similar delusions about Second Life back in the day.

andybak3• 3 years ago

Something can depend on another thing and still be "bigger" than it. (as woolly as that definition is)

I don't actually agree with the point you're contesting with but your reasoning here is flawed. Also - you might want to check your tone for future posts. It's slighty combative.

Frannyies• 3 years ago

'delusions' and your first thing is second life?

GitHub copilot and sit.ilar will become defacto standard.

Image generation is already here.

School systems already have to act on this due to pupil using it for essays etc.

AI literally creates a new ara for us: it's the first time we structure or learn on data to have a knowledge agent.

isoprophlex• 3 years ago

People miss the "hidden bit of the iceberg" when dismissing gen AI, or making claims that the hype is over. It's just getting started, indeed.

Anyone who did data work in big, boring enterprises knows the staggering amount of dark, unstructured data they have. Free-form text input, chat/phone conversations, but also plain old documents (pdf scans, PowerPoint files, anything).

Have a LLM interpret what is there and you turn this unstructured mess into data with a clear schema that can go into a relational database for further processing or summarization.

LLMs are groundbreaking for this kind of automated data structuring. And many use cases don't need perfect accuracy; detecting trends or summarizing at a high level is good enough for inputs to downstream process mining tasks.

nuc1e0n• 3 years ago

Present LLMs have not been designed to and cannot process audio data or scanned images.

halotrope• 3 years ago

This is such a naive take. I’m using gpt4 daily for anything coding, sql, directions, text editing, research etc. It’s absolutely invaluable and if it was $1k a month I’d seriously consider getting it.

Computer just had their GUI moment again and we’re just getting started.

spaceman_20202• 3 years ago

I’m using it to generate social media content, code, and for digging through documentation

yyt884• 3 years ago

For many companies, it's already hard to get a human support person on the line. "It's all on our website, just look there!" In the future this will be even harder.

danielovichdk• 3 years ago

Yes. As a programmer gpt is a very valuable tool.

I use it as an extension of my mind towards getting answers for grey areas. A grey area such as "write a unit test skeleton for this method signature", where the method in my head is either too abstract or has complexity that increase my short term memory span.

I find it a helpful extra pair of eyes that seems to know a lot more than can be expected by a human.

pjmlp• 3 years ago

Until architects can talk to them, when models are able to deliver the same quality as many offshoring projects, it is going to be a great cost saver.

nunodonato• 3 years ago

same. I happily pay my 20$, such an invaluable tool. And now much more with the app on the phone

voz_• 3 years ago

It’s just begun baby

stranded22• 3 years ago

It is getting blended into life - so you won’t realise AI is being used. Companies are too focussed on efficiency.

I have bought a perplexity pro subscription which is excellent - it creates useful summaries of search results across various sources but also has generative AI with chatgpt 3.5 FT, 4, Claude 2 along with llama 2.

I personally have difficulty trusting generative AI - too many hallucinations- so to see sources is helpful.

Roark662• 3 years ago

BTW, people get excited with "chatgpt for enterprise", but bing is doing something somewhat similar. For example if you go to bing.com from the internal network of one company I work for you get a "work" menu item(in addition to "news" "images" etc). If you search there it's not only searching all the company wikis, sharepoint sites, and any shared documents you might have access to, but it also answers questions "a la chatgpt" in company's context.

I'm not sure how long this has been available. I noticed it last month, but it is pretty useful to search for documentation or if you don't know internal procedures. You can just just describe what you want to achieve and it is reasonably good in finding the right documents. The AI boom is far from over. It hasn't even started properly yet.

pletnes• 3 years ago

To me, the hype is about big flashy use cases. The usage is like google search - scattered throughout my work week. Generate a power BI function (I don’t know the syntax at all), extract info from a strange document in english (not my mother tongue), write boring copy for marketing (I don’t do it often, I can fix the facts myself but ChatGPT’s english is better).

Some use cases are enabled just the last few weeks by company-internal models.

This will accelerate and evolve. Generative AI is a new appliance. We just got started.

andrewstuart• 3 years ago

The next step must be something like wikigpt where humans can actively teach it what it doesn’t know or how to do things better.

j-a-a-p• 3 years ago

An acquaintance of mine wrote commercial content for a living. Pretty repetitive work, which he performs remotely. He recently quit because of AI. This will happen more and more and the people concerned will often have a negative bias on AI.

To wrap AI technology into a chatbot is a deceiving, strategic move. It is a wolf in sheep's clothes aiming for people to believe the technology is there to help them. As such it is a solution looking for the problem, and now a year later there are not enough problems that a chat interface can solve.

In reality the genie is out of the box, but not to help people rather to replace them. Reduction of ChatGPT traffic does not tell us what is really ahead of us.

sublinear2• 3 years ago

Well, yeah. The use cases are fundamentally limited by its approach. Statistical techniques underperform compared to symbolic rules no matter how much hardware you throw at the problem. This has been known from the start.

Anyway, all known AI techniques struggle with common sense reasoning. The majority of ambiguities in natural language are distinct and uncorrelated. Combining known techniques is not going to solve the problem. Either we discover new theories, or revise our natural languages to be less ambiguous (likely a deeply unpopular social change). Both will probably occur in this century.

As for ChatGPT and Bing? I expect these brands will be dead long before we get to the next wave of AI.

Additional reading for the curious: https://en.wikipedia.org/wiki/Winograd_schema_challenge

akomtu• 3 years ago

I feel like a passable reasoning will be achieved by an equally dumb / brute force approach. Basic reasoning isn't different from pattern matching. When one calculates an integral, he matches the function against known patterns until something sticks and applies the transformation. Similarly, logical reasoning is often just noticing patterns (a or not b) = (b -> a).

wcoenen• 3 years ago

palm-2-l-instruct scores 0.909 on Winogrande few-shot. Where are the symbolic rule systems that get such results?

https://github.com/LudwigStumpp/llm-leaderboard/blob/main/RE...

nopinsight2• 3 years ago

LLMs still do not match humans on Winograd Schema Challenge but the top ones already get pretty close.

The current top model, Vega v2, is already at 98.6 (compared to human’s 100.0). https://super.gluebenchmark.com/leaderboard

Several other LLMs score higher than 95.0 as well.

I suspect some upcoming multimodal LFMs will be very close to human level since their training data would include video, audio, and possibly even physical interaction input.

Moreover, top LLMs already surpass the human baseline on SuperGLUE, a suite of many language tasks.

This is my experience when using GPT-4 as well. It’s like an extremely well-read intern who follows instructions much better than an average person on the street. It is just often a little drunk or sleepy at work ¯\_(ツ)_/¯, ……for now.

sublinear2• 3 years ago

All these responses are missing the point.

Like the Turing test, Winograd is not a very good test and more of a philosophical question than a metric for engineering.

Sure there's nothing wrong with a model that at some point in time passes 100% and is even more consistent than humans, but it's not possible to make an exhaustive list of what humans can disambiguate that these models can't.

It's a moving target. We're just a cultural shift, scientific discovery, or political regime change away from the models needing to be updated all over again. For some applications these lagging inaccuracies are not acceptable. For yet still more applications, it's not possible to allow any amount of time to train the models ahead of seeing novel ambiguity.

There's a lot of work left for AI research and the threat of authoritarian-induced cultural stagnation just to serve the AI gods and the convenience of governance is absolutely terrifying. i.e. You can't speak that way because it confuses the AI, you can't look or act that way because it confuses the AI, etc. AI in its current form totally sucks and is unfit for much beyond low risk tasks.

gaganyaan2• 3 years ago

What symbolic rule systems are matching the performance of GPT4?

mgax• 3 years ago

This article feels like it’s written by someone who wants the boom to be over. Just spending a few hours with AutoGPT made me realize it’s very far dram over. It just started.

marginalia_nu• 3 years ago

I don't think the technology is going anywhere, but the hype is cooling down, as limitations are starting to be better understood, and the 'Dude! Don't you get it! At this pace[1] we'll have a 1e304 parameter GPT17 model and weaponized AGI by noon on Thursday'-bros have quieted down a bit.

[1] https://xkcd.com/605/

tomjen3• 3 years ago

Chat GPT what is betteridges law of headlines?

hendersoon• 3 years ago

If anything it's underhyped, in that the technology will be foundational to how we do work and sort through tremendous data volumes in the future. The pushback is simply that these giant companies haven't found any clear way to monetize primary LLMs as a service-- and they won't, because open-source models are improving at a breakneck pace and hardware requirements (and thus cost) is dropping due to community development.

Ultimately I don't see those primary LLMaaS offerings being particularly profitable. Secondary LLM applications are a completely different matter. For example, LLMs acting as medical scribes, sitting in your doctor's office and filling out your chart, handling a job that formerly required a skilled human. That sort of thing will make tons of money. It just probably won't use Azure/Amazon/Google LLMs to do it.

redhale• 3 years ago

This is surely the "Why the Apple phone will fail, and fail badly (2006)"[1] of our time.

[1] https://news.ycombinator.com/item?id=37362181

Is the ChatGPT and Bing AI boom already over?

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