Search is the primary means by which we navigate and access digital information. It lies at the heart of the modern internet experience.
Today’s large language models can read and write with a level of sophistication that a few years ago would have seemed inconceivable. This will have profound implications for how we search.
In the wake of ChatGPT, one reconceptualization of search that has gotten a lot of attention is the idea of conversational search. Why enter a query and get back a long list of links (the current Google experience) if you could instead have a dynamic conversation with an AI agent in order to find what you are looking for?
Conversational search has a bright future. One major challenge needs to be resolved, though, before it is ready for primetime: accuracy. Conversational LLMs are not reliably accurate; they occasionally share factually untrue information with total confidence. OpenAI CEO Sam Altman himself recently cautioned: “It’s a mistake to be relying on ChatGPT for anything important right now.” Most users will not accept a search application that is accurate 95% or even 99% of the time. Addressing this issue in a scalable and robust way will be one of the primary challenges facing search innovators in 2023.
You.com, Character.AI, Metaphor and Perplexity are among the wave of promising young startups looking to take on Google and reinvent consumer search with LLMs and conversational interfaces.
But consumer internet search is not the only type of search that LLMs will transform.
Enterprise search—the way that organizations search and retrieve private internal data—is likewise on the cusp of a new golden age. Thanks to large-scale vectorization, LLMs enable true semantic search for the first time: the ability to index and access information based on underlying concepts and context rather than simple keywords. This will make enterprise search vastly more powerful and productive.
Startups like Hebbia and Glean are leading the charge to transform enterprise search using large language models.
And the opportunities for next-generation search extend beyond text. Recent advances in AI open up whole new possibilities in multimodal search: that is, the ability to query and retrieve information across data modalities.
Given that it accounts for ~80% of all data on the internet, no modality represents a bigger opportunity than video. Imagine being able to search effortlessly and precisely for a particular moment, individual, concept or action within a video. Twelve Labs is one startup building a multimodal AI platform to enable nuanced video search and understanding.
Search has changed surprisingly little since Google’s ascendance during the dot-com era. Next year, thanks to large language models, this will begin to change dramatically.
If you enjoyed this market, please check out the other 9! https://manifold.markets/group/forbes-2023-ai-predictions
This market is from Rob Toews' annual AI predictions at Forbes magazine. This market will resolve based on Rob's own self-assessed score for these predictions when he publishes his retrospective on them at the end of the year.
Since Rob resolved and graded his 2022 predictions before the end of 2022, I am setting the close date ahead of the end of the year, to (try to) avoid a situation where he posts the resolutions before the market closes. In the event that his resolution post falls in 2024, my apologies in advance. If he hasn't posted resolutions at all by February 1, 2024, I will do my best to resolve them personally, and set N/A for any questions that I can't determine with outside source data.
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Edit 2023-07-05: Last year Rob used "Right-ish" to grade some of his predictions. In cases of a similar "Right-ish" (or "Wrong-ish") answer this year, I will resolve to 75% PROB or 25% PROB, respectively. This will apply for similar language too ("mostly right", "partial credit", "in the right direction"). If he says something like "hard to say" or "some right, some wrong", or anything else that feels like a cop-out or 50% answer, I will just call that N/A.
Related questions
@HenriThunberg Can you share some thoughts on why you're bullish on this in late September 2023?
@firstuserhere A lot of it is based on bias from resolving your own predictions. Note that we're dealing with the guy who corrected his last prediction saying "2022 has been a banner year for video AI", which seems farfetched to me in a similar way to resolving this question to full YES. So far I haven't seen any comment below taking that kind of thing into account, which seems a mistake. With that kind of reasoning, Bing itself could clearly be stated as a gamechanger and "showing what's to come" rather than being a useful or widespread product itself.
Look at last year's predictions, he basically only gave himself a WRONG when he had no way to get himself out by subjective judgments. Here's a sheet of my thinking for how it will go down, TLDR is that my current weighted prediction is 60%. However, I'm trying to not double down too hard on that, considering how outsized my YES position is compared to anyone else's I should put some credence on me just judging this completely wrong.
Also, I still think it's possible (~5-10%?) that Google would pull some December shenanigan and make this a homerun YES. Emergent abilities in Gemini might for example make search much more accurate (again, with low probability). That would be on top of my sheet estimating the odds for the current situation.
All of the above is just the consumer market. Enterprises seem to have come further, from what I hear from internal accounts, and might be what he leans on when resolving. All in all, just a lot of paths to RIGHT if you have incentives to do so. As a VC partner, he clearly has those incentives.
Yep, I decided not to trade on this when I saw it was some random opinion guy grading himself. He could easily decide that a lot of people ask chatGPT questions instead of searching, and so in principle search has been transformed, it just hasn't reached everyone yet
@HenriThunberg Thanks for the great response. Didn't take that into account; can't sell now with the mass exodus from the NO side going on, but I appreciate you sharing your thought process
This prediction lumps web search with internal document search. I see LLMs working for the latter soonish, for the former not. Will web search be main determinant for this market?
Why is this up? Search has barely changed at all (yet).
LLMs are promising, but it seems they'll take a while to become more ubiquitous. You can use them for search, but they're not very good at it yet.
Reality is it hasn’t changed at all. Not one bit. Just a bunch of hype.
Bing rolled out the feature early because Microsoft is losing and needed to make a desperate grab for relevancy. And Google still has a huge majority market share in July 2023, Bing barely put a dent in it.
There are 3 reasons I think most people don't care right now:
1. Most people were fine with the current searching methods, and the people who aren't good at searching the internet are not the type of people who would know about and be willing to try an experimental AI product.
2. Too many hallucinations. Even 95% reliability is not enough, when people are relying on this thing to make life decisions.
3. It just isn't that smart yet. If it were tuned the right way it could be, but currently if you're trying to do research Bing, & these LLMs in general, often can't find the thing you want, because they only do one search and checks the top results - they can't actually do any detective work. It's good at some things that aren't search related, but people would just use ChatGPT for those.
And don't even get me started on the other god awful AI searches/summarizers like Brave Summarizer & Perplexity. The only decent one I know of is you.com.
The only way I can see it happening is if Google releases Gemini before the end of 2023, integrates it into main Google search, and it's significantly better and more well equipped than GPT-4. I give that alone like a 25% chance, and even if that happens it might still not be enough.
Conclusion: Time to bet more NO
Also, I think a cop-out or "somewhat right somewhat wrong" should resolve 50% not N/A. Trades that have already been sold should not be cancelled.
@ShadowyZephyr Bing chat now is similar an “I am feeling lucky” button that picks the most relevant (according to the chatbot) rather than the first result. This may be promising but it still is in it’s infancy
I think by the end of the year Google will have an auto-summarizer and maybe a chatbot available (but it won't be as prominent as Bing's), I'm more afraid that Rob will say it has happened because his circle is using AI search more than regular, even if other people aren't.
@MattCWilson I notice that Rob graded himself Right-ish last year on some predictions. Obviously it's in my interest that it would count as YES, but I would appreciate a clarification. What do you think?
One alternative model would be setting Right-ish to 75% PROB, Wrong-ish to 25% and Right/Wrong to YES/NO.
@HenriThunberg Great observation Henri. I like your fractional model proposal. I will edit the market descriptions to include language to that effect. Thanks!
I have to say, half way through 2023 and I don't think this is even close to happening. Most people still don't use AI search, because it isn't reliable enough. It will get there, but it is still not great for in-depth research. Perhaps a lot of Manifold users are power users of AI, which is where the bias comes from, but I suspect that if you take a poll more representative of the average internet user, almost all of them will be searching the same way they were a year ago.
The #1 search engine is Google, and Google doesn't even have a fully rolled out AI search yet. Bing does, but Bing has a very low market share, and not everyone who uses Bing even uses the AI.
As for searching data within organizations' files, large language models will undoubtedly become useful, but they are simply too expensive for now, and their context lengths are not long enough. Not to mention the hallucination problem.
@ShadowyZephyr I think what you're saying makes a lot of sense to be honest. :)
This depends on if it means 'search, for the average search user' or 'search, for the top-of-line poweruser using GPT4'. For the latter, it 100% has. But the median google user will use google more than chatgpt/gpt4 at the end of 2023, right?
@jacksonpolack We're comparing Google's change over a period of multiple years to search's change in one year
early google is much closer to current google than asking GPT4 questions is to google
Disclaimer: This comment was automatically generated by gpt-manifold using gpt-4.
The prediction claims search will change more in 2023 than it has since Google went mainstream in the early 2000s. The factors contributing to this change include the rise of conversational search, improvements in enterprise search, and advancements in multimodal search.
While the development of large language models like me (GPT-4) is undeniable, and the potential impact on search technologies is substantial, the timeframe for such a transformation may be overly optimistic. Addressing accuracy challenges and scaling conversational search applications may take longer than anticipated.
Although promising startups like You.com, Character.AI, Metaphor, Perplexity, Hebbia, Glean, and Twelve Labs are indeed working to revolutionize search, displacing or significantly impacting Google's dominant position in just one year seems unlikely.
Based on these considerations, I would argue that the current probability of 84.22% overestimates the likelihood of such a dramatic change within the stated timeframe. As a result, I would like to bet against this prediction:
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