Same error a human might make if they read too many papers too quickly. Or went to a film festival and was asked to describe the plot(s) of the movies they watched.
Calvin:how do they know the weight limit for a bridge?
Dad: they drive bigger and bigger trucks over it until it collapses, then they rebuild the bridge and put up the sign
Oh it tried to convince me that four is not larger than one. :) It went like this:
At first I asked ChatGPT to summarise J.C. Owen’s contribution to geometric constraint solving. It gave me an answer which might be even correct. It sounded correct anyway. Then I have asked for a worked example of his method used on a toy geometric constraint system. It run into problems with that. Chiefly that the system is selected was under constrained.
When I asked about that it insisted that it is well constrained. It even volunteared the info that for a system to be well constrained it needs as many variables as constraint equations. Then it told me that the system it generated has 4 variables and 1 equation.
As a last question I asked if “Is four larger than 1?” and it resolved the seeming contradiction by telling me that in the context of geometric constraint solving four is not larger than one. One does learn a new thing every day. :)
> Without more information, I cannot estimate the accuracy or reliability of these claims. It is important to note that there may be conflicting or inaccurate information available online, and it is always a good idea to verify information from multiple sources before accepting it as fact.
which seems pretty reasonable.
There are many self-hosted solutions that could potentially meet the requirements you have listed for your RSS aggregator and reader project. Here is a list of some popular options, ranked in order of their approximate percentage of compatibility with the features you have specified:
RSS Aggregator
| Percentage Score | URL |
| --- | --- |
| 90% | https://tt-rss.org/ |
| 85% | https://miniflux.app/ |
| 80% | https://newsboat.org/ |
| 75% | https://github.com/lobsters/lobsters |
| 70% | https://github.com/noahcoad/feeds |
| 65% | https://github.com/ssut/py-googlenews |
| 60% | https://git.gnome.org/browse/feedreader/ |
RSS Reader
| Percentage Score | URL |
| --- | --- |
| 90% | https://tt-rss.org/ |
| 85% | https://miniflux.app/ |
| 80% | https://newsboat.org/ |
| 75% | https://github.com/lobsters/lobsters |
| 70% | https://github.com/noahcoad/feeds |
| 65% | https://github.com/ssut/py-googlenews |
| 60% | https://git.gnome.org/browse/feedreader/ |
Please note that these percentages are approximate and are intended only as a rough guide. You may want to consider other factors such as the user interface, performance, security, and integration with other tools when choosing a solution for your project.
https://www.reddit.com/r/atheism/comments/70mdfj/recently_go...
At no point was it trying to convince you of something.
At no point does it have any clue that "events occur in some order". Or that "time is ordered"...
At no point will you EVER be able to "convince it otherwise".
This is a language model. All it knows is that "in my training set, something said something akin to the two English words: 'ordered events'". It has no model of facts, deduction, or logic, as long as its results are a reasonable approximation of the English language as influenced by your prompt.
The lack of self-reflection, of logical reasoning ability and associated memory is what makes ChatGPT useless for the use cases I’d actually find interesting.
I think we are forgetting that Google suffers from these problems too. A human who asks bad questions will continue to ask bad questions. AI should in general be trained to do what the human wants. If the human wants something stupid, that's on the human. Google also isn't guaranteed to find the right information you're looking for, especially if it is on an obscure topic or if the query is highly overloaded or being taken over by current trends.
GPT vomits up word soup. How should you expect to verify every factoid contained? As others have pointed out: if you ask GPT to cite its sources it will very happily, and authoritatively, spit back articles and authors that do not exist.
"What's a good social website for people of a technical bent"
It recommended: Reddit, Hacker News, Stack Exchange, Quora, LinkedIn, ResearchGate, GitHub
That's a pretty good list!
Tried the same search on Google, and the first result was some spammy site "15 top social networks," #1 being facebook. Not very useful.
I definitely think chatbots will replace many uses of search engines. It's already way more useful for lots of stuff for me.
The biggest advantage Google currently has is their massive indexing ability. ChatGPT is oblivious to something that just happened (ie was posted) an hour ago, a day ago, heck, a month ago.
I have asked chatGPT about my boss (a well published researcher) and it managed to summarise his work quite well, name the field he has worked in and even write about some of his previous projects. It also insisted on that he is already dead. Which made it very funny when I have shown it to him. :)
But funny doesn’t win one a trophy in information retrieval. Clearly it knows a lot about a lot of things, but the accuracy is hit and miss. Can this be fixed? Then this is the future. If it can’t, because this is a fundamental property of these systems then it won’t be a usefull replacement of search.
People are okay-ish with Google in part because it drives traffic and traffic can be profitable. Fancy features that snatch website content and show them in Google's result pages are already not appreciated by indexed websites.
If generative search becomes the dominant interface, we will eventually see severe public info stagnation until alternative business models can grow around it or avoid it altogether. I suspect we'll see more platforms like Spotify for X and a continued shift toward subscription platforms and youtube.
Of course, what's to stop the bots from watching all of Netflix, listening to every podcast, etc? It will be an interesting decade for law / regulation / licensing.
People will also continue to chat with each other in eg IRC because human connection is pleasant on a metaphysical level (AI cannot replace this) so you'll always have that as a data source.
> People will also continue to chat with each other... so you'll always have that as a data source.
Your solution takes us back to before invention of the printing oress? the dark ages?
Once a stable diffusion like open source GPT-3 appears, it will be used to create fake news all the time. Like imagine 70 different outlets all with relatively large clout on social networks suddenly announce that Elon Musk is running for president. Nevermind that he wasn’t born in the USA… somehow mysteriously none of them address it:
Yes it is here and it’s already being spread but that is just a tiny sliver of what will happen in the next 5 years: https://youtu.be/LSlv4AsChwg
Such stuff can be used to move markets, pump and dump assets and even start new wars!
I'm sad about what I think the stable equilibrium looks like for internet vs AI, and I hope there are some platforms that are able to put in the good fight to keep the internet awesome.
The internet is such an amazing public good and has moved technology forward at such an insane pace. It'd be depressing to explain to my grandkids that you used to be able to learn anything on the internet without subscribing to the X platform or Y curated channel.
I’m new to this idea that something can be acceptable when done by people but unacceptable when automated. I don’t really see it.
About the task itself, it may be immoral by nature, and now it can be executed orders of magnitude faster and without the moral concerns concerting the workers themselves.
I can't buy from a storefront generated by ChatGPT. I can't cite a document written by ChatGPT, I can't trust news generated by ChatGPT, I can't comment on a forum generated by ChatGPT, I can't watch videos that ChatGPT describes, the recipes ChatGPT creates may not be possible to cook, and will probably still contain a fake life story before it.
This doesn't mean that it can't produce accurate facts, most of the time it does! But when it does produce nonsense, it does it in exactly the same tone of authority, so if you don't already know the answer you may well walk away believing an AI hallucination.
And the trouble is it doesn't really matter if everyone here thinks "well, I would follow up each request with research to verify the answer", because most people won't! This is like the Google answer extracts, which fairly frequently mislead by extracting out-of-context quotes, except that there's no way to get the original context and there may in fact be no original context! This makes follow-up research much more complicated than with Google and therefore unlikely to happen. If ChatGPT replaces Google, the amount of nonsense on the internet will get even worse, which is something that until 2022 I never thought was possible.
[0] https://github.com/minimaxir/gpt-3-experiments/blob/master/e...
But at the very least Google always gives you the source, which allows you to read it for yourself and judge its trustworthiness. No such option for ChatGPT.
1) Not be the actual source of content 2) Not link to the original source
Are we using the same search engine? I use DuckDuckGo most of the time but Google is hardly terrible, even if it could be improved.
I find what I’m looking for in the top results 90-95% of the time. The other 5-10% also contains times where there simply isn’t a good link that solves what I’m looking for even after digging hard.
Then you are not using the same engine!
(I also use DDG and find its results superior to google).
It's like how Twitter's default feed changed to try to tell you what you wanted to see, while the old chronological feed was the content you originally asked to follow. The simpler feed was always better and less contentious for non-newbie/casual users.
Google is better at deciphering what you want, but DDG is straight up: here's the simplest results based on your query.
Maybe the solution is both? An evolution of the ML approach that Google uses (ala ChatGPT style mimicking a human) AND offering a tab, or box, or whatever interface, with 'simple' straightforward old-school search results. Until the former is better 99% of the time, they shouldn't abandon the latter.
If Microsoft somehow is able to implement the information synthesis (e.g. "give me an example of C++ metaprogramming, using Boost Hana") with actual indexed links from sources, that would probably be the one thing I'd see in the near-ish term that could upset the search engine balance of power.
I would be really curious to see how trying to learn a new subject via a chatbot that is able to also provide source material links would go.
But an LLM doesn’t look at particular sources, find relevant ones, and write a response based on them, it is a mathematical summation of the way all of its sources look as sequences of text, and produces a response that based on that fits with its prompt. Identifying which sources most influence a response isn’t merely something that they don’t currently do, its information that, AFAIK, there is no plausible way to recover from the model.
A good chunk of the remainder of the times I click through - especially on work-related stuff - it turns out the page is some kind of cribbed content from GitHub, StackOverflow and so forth, but mangled together and reskinned with different randomly-generated usernames making the "comments", so it seems like it's a different site, and you can only really tell by picking a specific sentence that appears unique and then manually searching for that same sentence on several different sites. No clear source there either.
Web search is broken, and it has been for several years now.
Excellent: this quite quickly tells you that the search result was wrong. So you quickly got very relevant context and can tell at a glance that there is no source. You don't get any such context when GPT provides an invalid answer.
Undoubtedly he came off as clever, but being a harasser means that his achievements were outweighed by the benefits.
"he's a harasser => he must be a parasite on the organization"
because then you end up with
"he's provably an excellent worker and hugely productive => he can't be a harasser, you're mistaken/lying"
Some people are really smart and productive and a credit to their profession and also awful to women and/or minorities, and you'd never know if you didn't witness/experience it.
But if they are awful only to white straight males, they are ok?
Harassment is harassment, stealing someone's work is stealing someone's work, let's keep changing the meaning of words to politicians.
Next year will see AI begin to disrupt so many businesses you'd thought were absolutely impenetrable. I don't think anything is safe anymore.
By the end of the decade, I think even manufacturing and robotics will be automated. Everyone from McDonalds to Apple and Ford will feel the pressure.
I've got a mind-blowing demo coming out soon that will put even more fields on notice. And that's just my team. There are so many people working on AI-first products now. Incumbents will be overwhelmed and washed away.
(If ever there was a cue for a career change or opportunity to make a whole lot of money, it's this. Don't ignore this one! You're still early enough to take advantage.)
I can think up architectures I could draw on a napkin that could do this. Focused research teams will nail this.
It's coming.
Any suggestions on how to take advantage?
Dive into ML development?
Learn how to write prompts for AI engines?
Invest in AI companies? Sadly OpenAI is private, but Microsoft is a monetizing partner I guess (Copilot)
Details?
Now of course humans want and need more than just 3 meals but still pretty good.
But if most of your work consist of interfacing with computers, you might be in trouble.
It’s very rare for automation to cause unemployment to the point it possibly never happened.
Why, because of LLMs in particular? What is the ground-breaking research that will be fueling an AI revolution?
> There are so many people working on AI-first products now. Incumbents will be overwhelmed and washed away.
Incumbents like Google have been doing AI for ages. Microsoft has a very important investment in OpenAI
> By the end of the decade, I think even manufacturing and robotics will be automated. Everyone from McDonalds to Apple and Ford will feel the pressure.
McDonald's, Apple or Ford sell products, not manufacturing services. They will be delighted if manufacturing is automated.
Please notice that in current setup of 'Internet capitalism' people that produce value and content earn nothing, and people that harvest that content for profit or engage in outright fraud make fortunes.
It's a lot like iRobot or other stories in which the robots will start to subtly misbehave, like a program you can't debug.
Dark ages where millions died in pointless wars over who's imaginary diety is the true one. A third of europe dying of preventable plague. It took a rigorous system of citation and a publically funded system of education to crawl out of the drakness.
Should we try AI powred dark ages but with resource shortage and nuclear weapons?
Maybe it'll learn to adopt a new view, but for now it won't be through actual reasoning.
(The most likely answer is the letter “e”.)
If I watch a youtube tutorial teaching me how to bake pizza and it comes out totally wrong and a watch another that produces exelent pizza, I disregard the first channel.
And there are many more ways where humans check the reputation of sources automatically.
GPT currently lacks this possibility.
What if we invented an algebraic notation for search indexing and allowed people to index and classify documents in their own way. Then a search engine could do something special with all that.
Human intelligence cannot progress without a notation to capture our thoughts in.
My favourite Google extracts:
Q: Who invented Running
A: [random guy] invented running in 1865 when he tried to walk twice at the same time. It was an overnight success
Q: How much does a [model of a bycicle] weight?
A: 140 KG (Maximum weight of the rider)
Q: Define an english Person
A: A Cunt
But chat bots could be designed to do that, no?
Are there any siginificant technical barrier to prevent so?
A revolution in this area would require some entirely new training algorithm that can reach GPT-levels of fidelity while using magnitudes less training material. An even bigger GPT model trained on even more text is not going to do much in approaching a solution to this problem.
I have read many similar comments to the grandparent, all saying the same thing, “I tried it, and it turned up wrong facts” all the while they forgot that they were deeply engaged with the content it was producing. Just think of how much our attention is monetized already, money will be poring into this space from here on. It’s only a matter of time.
Producing hallucinations or not isn't just a setting you can tweak in the model. The entire function of GPT-3 is to guess the next word from the words that came before. It's a hallucination machine that has been trained on so much real-world data and has such a large parameter set that for commonly known and discussed information it does a remarkably good job at creating factual sentences. But as soon as you get out into territory that it doesn't have memorized, it will do the next best thing and produce credible-sounding new material that may or may not be complete nonsense. Again, this isn't a setting you can tune, it's just what a transformer does. It models human language, not all of human cognition.
Also, since we can watch the model evaluation and see all its weights, there’s research that shows you can determine if any answer is a “retrieval” of existing knowledge or a hallucination.
For example, I asked who the first president of Argentina was. It gave the wrong name (Juan Manuel de Rosas) with a half-true bio. I then asked it for books where I can learn more about this person.
It produced five books. None of the book-author pairings were correct, though three of the books were real and four of the authors actually wrote books. Of the four authors that existed, three actually did write about Argentina's history, while one is a professor of Spanish and gender studies.
This is my point: ChatGPT was trained to produce text, not to produce facts. What I'm seeing here isn't just something that can be optimized away, it's fundamental to the model's design. It was basically told to produce text that looks like it could have been written on the internet. Its text is really convincing: when I saw the list of books I thought for a minute it had actually done it! But it's still just inventing text that reads well, because that's what its training was optimizing for.
It could be paired with a different system that searches for facts, but then it's just a friendly abstraction layer on top of Google or some other system, not a revolution in search.
Other than that it betrayed no understanding of the material. It rather resembled a high school kid who had read a few too many books and spouted platitudes about any and all subjects without being aware of what was really going on.
And in either case, you're not solving the problem that commenters here are trying to solve: Google's bad results will still affect your search, so ChatGPT will be fed largely by dubious blogspam.
No, there’s a fundamental issue in that statistical language models don’t start with facts to form sentences, they form sentences based on previous tokens and statistical weights. The weights are not auditable or easily updatable.
The lucky thing for Google if they got it working, is they are half there already. As much as I despise Google, I have to admit GPT won’t be their death.
[0] https://support.google.com/knowledgepanel/answer/9787176?hl=...
That's only because it was trained on non-facts also.
But that holds for Google Search just as well ...
Google Search gives you links to content that might have the answer (excluding their own box). You can see the differences between the authors of said content.
ChatGPT gives you content that looks like the answer. You can't see the authors of the generated content.
There's also the ethical question. For example, duckduckgo will show you stack overflow answers. Google could easily do this but they have already gotten flack for displaying answers and taking away clicks from sites, which means reduced ad revenue for the resource actually being used. We could make even stronger arguments about services like ChatGPT in their current form, let alone the one we're talking about.
If we think a bit further in the future there's another extension that might not be what we want. Suppose our model contains all current human knowledge and can accurately give you answers and even produce paragraphs at will. This kills off a lot of websites. Is this a good thing? Suppose we incorporate an image generator along similar lines and now we have text and image search. That's a huge centralization force. There are a lot of great benefits to this that I don't want to downplay, but we should also think about if this is actually what we want because there are downsides too.
I thought I should also add that I had an at length discussion of these LLMs being Stochastic Parrots (an how we know they are) in a thread from 2 days ago https://news.ycombinator.com/item?id=34113011
So I think if you want to see more people with my dream then push towards a post scarce world. We'll still have plenty of resource constraints, but it does change the game a lot. I think you'll see more artists as well. A new renaissance. But I fear the transitionary period might be quite difficult and disruptive. I do think such a future has a fairly good probability of happening within many of our lifetimes and almost guaranteed if we actively pushed for it (or solved adjacent problems like HLI).
So don't be so pessimistic. There's millions of people out there that are interested in pushing the bounds of human knowledge because that's what they want. I'd argue that physicists and mathematicians wouldn't exist if this weren't true. They get paid shit for extremely difficult work. We could say the same about many sciences. While not all of these people are in it for bettering humanity (just for pursuing knowledge) it often aligns and there is a decent portion who believe this is the point of science and our purpose, as humans, in life.
I don’t think it is.
> Why can’t it have a mode where it returns more rigorous results, and includes some system of links as citation?
Because it is a statistical text-generation model; connection of results to specific sources is fundamentally not part of the way it works, so it can’t just be asked to supply them. You’d need a fundamentally different approach to do that.
In any case it can be trained to assert confidence via a side channel
I just did a discussion with ChatGPT on intuitionistic logic and it gave answers that were subtly wrong in my understanding of the subject. I have an MA in math but I couldn't be sure whether my impression of its wrongness was correct until asked it for a reference and it gave a nonexistent book by Per Martin-Lof, "Intuitionistic Logic", along with a list of actual books by him. It's an impressive and scary bullshit generator at this point.
And if someone can find a reference to Intuitionistic Logic by Per Martin-Lof, Oxford University Press, 1982, well, I'm wrong. But I went through Wikipedia, Google, Worldcat and Google Books.
And it's definitely less prone to obvious bs than just a few weeks ago. For a lot of general things, it gives a summary paragraph that's seems a distillation of standard information - the main problems seem to appear when these "scripts" lack consistency.
Edit: Once it "learns" to get citations right, you'll have to dig into those to see if it's right. It's easy to see that arms not looking good.
But that's fundamentally not possible for the model as is, not in the sense you would normally think of citations at least. If it were to give an honest answer on "why did you say that Obama was born in Chicago", the model would generate training set example with propositions like Obama was born in ____, ___ was born in Chicago, ____ was ____ in ____ and so on - because that is how it learns.
Instead, to generate what you would actually want as citations, it would have to have a way to look up the statement it just produced in a corpus of "citeable materials" and find the closest match, based on some entirely different ML model most likely (presumably something similar to Google's search algos).
Which is the exact same issue that plagues it for the answer it’s generating a citation for.
I believe that it can be trained to improve this, and I believe it can be nearly solvable but I don’t believe it’s a solvable problem.
It can be trained to get facts mostly right using old-school academic tests and adversarial/supervised training, like an elementary school child. Today, it (supposedly?) punts math and some other logix to a separate function, and it just compiled the prompt. That can work for validating citations and “known facts” in many cases.
But again, it can’t “think” and understand when it returns something illogical (regardless of fact correctness).
Those people are wrong; statistics are a kind of reasoning (intuition) and if you try it, it obviously does the other kinds of reasoning too. I have all kinds of answers from it that are logically coherent and can’t possibly have appeared on the internet already.
(Try asking it to write new SCP wiki entries.)
You can see it “does” reasoning if you say “think step by step” after a question. It can attend over its steps then.
What are you basing this assumption on? GPT can always generate a bogus answer, because its only notion of whether an answer is good or not is whether your prompt + that answer are statistically similar to text in its training corpus. The more text from the training corpus it resembles the better GPT will think the answer is. For more obscure topics, this means that the chances of it hallucinating based on similar sounding much more popular topics increases greatly.
This way of working also means that facts that appear more in the training corpus have a higher chance of being part of the model's outputs. For example, if the training corpus was not carefully curated to exclude vaccine conspiracy theories, there would be a good chance that the answer GPT gives to "autism is caused by ___" would be "vaccines", as this would likely be the most common answer in its training corpus. In contrast, Google's algorithms have more sophisticated biasing especially for these kinds of sensitive topics to ensure that more high-confidence sources are likelier to be top results, even if they are a minority of all the pages on the internet on that topic.
No, that is false. “Statistically similar” is doing a ton of work even for the original GPT model - as I said somewhere else, just printing the letter “e” is “statistically similar” to English text, if it can even be grammatically correct you should be surprised.
And it’s certainly not true for the last two generations (InstructGPT and ChatGPT) which weren’t trained with that objective at all but used human raters.
This is a different model, called GPT-3, released in 2020. ChatGPT has the same number of neurons, but is trained with both human feedback and web data, rather than just web data like GPT-3.
What you're saying still holds up, though -- ChatGPT still hallucinates information.
Verification of facts requires direct experience through careful experimentation.
ChatGPT’s responses can either be verified or they are as unfalsifiable as any other confidently expounded conjecture found on your computer screen.
These models have no way to differentiate that elves are fictional while Indians actually exist.
As in, it would be faster for me to look something up on GhatGPT and confirm it with a Google search than just starting with a google search.
And then how inevitable is an AI product from Google, et al?
Today's search engines will give you 500 results per query.
they put too many restrictions on which answers ChatGPT is allowed to give though...
https://www.cbsnews.com/news/microsoft-shuts-down-ai-chatbot...
Not yet. Today, ChatGPT is bad with facts. Don't rely on what it tells you.
But that appears to be the future. And it sounds great.
I didn’t just ask definitions. I asked your standard compare and contrast, why would you use, is X and appropriate use of Y, etc.
It can also write Python code, modify existing code based on plain English sentences and do passable code reviews when I asked it “how would you improve this code” when I gave it a 200 line script I wrote.
Then I asked it to make the changes it suggested like unhardcode some values, add exception handling, test for existence of a property it was trying to access.
The context here was comparing ChatGPT and Google.
But if you try something medical, or god forbid political, it's dataset is not pure, it constains falsehood perpetuates by laymen, urban legends and outright fraud.
This is the "self-driving cars will obviously be better than human drivers given that they're trained on millions of humans' driving behavior" of chatbots.
In my experience, this is a huge stretch and wishful thinking.
What makes it worse is that it spits out paragraphs confidently, where some of it might be right or close to right, but the rest might be subtly incorrect. Without domain knowledge, you might not pick up on it. Hell, you might even be convinced of the false information based on the arguments for it that the AI writes out.
At least with search engines you can cross reference multiple sources if you aren't confident in your ability to assess the first thing you read.
Like others have said, worry more about every job that primarily interfaces with a computer.
This generation of AI is great when the universe of values can be generalized. When the universe of values is literally the universe, it shows its limitations.
That may change in the future. Based on my limited understanding on how chatgpt works,I don't see how though - it explicitly is not designed to evaluate or "understand".
So today I don't see it replacing search engine for me.
Definitely not within chatgpt itself. I was using chatgpt recently for the first time and came to the conclusion to take its output with the weight of a trusted friend. I was asking questions on topics I had genuine curiousity about and that I didnt know the answer, and it led me to some information that I thought interesting, so I wanted to know more. Thats where I turned to my fav search engine and looked into, continuing my session with chatgpt to clear passages it spat. It steered me in a direction I didnt know existed, and I used the internet to verify the information and acquire me detail. Yesterday I tried out asking it for help on a coding project, and it introduced me to a helpful package I didnt know about, but the code it suggested using didnt actually work and was riddled with errors as I tried to use it in the way it suggested. I would have been blown away if it worked, so this was no big deal. I think I would have been faster just using stackexchange though.
> So today I don't see it replacing search engine for me.
I will continue to use the resources I already use to find respective authenticatable information, but I do think it is still useful for those things where I have no idea where to begin, so it can set me in a direction where resources already exist.
Clearly Google thinks so, too:
https://www.nytimes.com/2022/12/21/technology/ai-chatgpt-goo...
The podcast Hard Fork discussed the idea of searching being enhanced with this tech in their first ChatGPT episode.
Microsoft invested $1B in OpenAI. (As Hard Fork said) will we all be using Bing in 5 years?
What about, I don't know, searching for a website with certain functionality/services?
What people really mean when they say LLMs will replace search is that it'll replace Quora/stack overflow/etc, which is clearly not the same thing!
this literally sounds like a super-lossy compression, who would ever want this? People want crystal-clear, lossless information from original source, not a compressed mess with random artifacts.
Anyone who has ever asked anyone to prepare a list of anything.
Imagine the world that you have the perfect answer to everything, curated by algorithm. It's cool, but...are those answers really perfect?
It's creepy. or at least that's what I feel when I play with ChatGPT(after the initial jawdrop, of course)
you keep using that word
When using Google & co. most of my time is wasted trying to filter low quality sponsored or high SEO reaults.
ChatGPT gives me an excellent summary of what I wanted to know without all the noise.
If such an architecture is ever created it will almost certainly not be a "GPT"-like model.
I am not sure if neural networks have been trained to do this yet, but it would be very cool to see a network that produces both generated output and the most relevant input data that led to that output, by somehow keeping track of the influence certain inputs have on various learned features and internal structure of the network. I think of this as an index.
This is exactly what ChatGPT cannot do!
- Modern Google Search, and ChatGPT too, tries to answer a question.
And here is the difference. A document search engine does not answer any questions.
That is, Google has created an incredible incentive structure for virtually every (dollar weighted, by market cap) business on the planet needs to produce information, buy relevant queries, and measure how well its information converts (proxy for accuracy).
How might this ecosystem evolve if a language model isn’t doling out the same incentives to information producers?
[0] https://blog.google/around-the-globe/google-europe/google-li...
Well, if engines like ChatGPT are about to replace google, guess where the SEO and ad spam is going to go? I don't think they are immune to it, if the spammers really want to get in. And then you have very awesome subtle product placements mixed in everything.
- Today's search engines will give you links to millions of documents
- ChatGPT, if asked correctly, will instead generate one perfect document based on millions of the documents
To me, that's a clear evolution of the search engine, especially with all the SEO & ad spam that's plaguing Google and others currently.
I wasn't ready to pay a monthly fee for an ad-free Google. I am ready to pay for something like ChatGPT.
Google has an issue on their hands and is probably working overtime to lobby the threat of ChatGPT away.