I came across this company called OpenEvidence. They seem to be offering semantic search on medical research. Founded in 2021.
How could it possibly keep up with LLM based search?
It is a little more than semantic search. Their value prop is curation of trusted medical sources and network effects--selling directly to doctors.
I believe frontier labs have no option but to go into verticals (because models are getting commoditized and capability overhang is real and hard to overcome at scale), however, they can only go into so many verticals.
> Their value prop is curation of trusted medical sources
Interesting. Why wouldn't an LLM based search provide the same thing? Just ask it to "use only trusted sources".
They're building a moat with data. They're building their own datasets of trusted sources, using their own teams of physicians and researchers. They've got hundreds of thousands of physicians asking millions of questions everyday. None of the labs have this sort of data coming in or this sort of focus on such a valuable niche
> They're building their own datasets of trusted sources, using their own teams of physicians and researchers.
Oh so they are not just helping in search but also in curating data.
> They've got hundreds of thousands of physicians asking millions of questions everyday. None of the labs have this sort of data coming in or this sort of focus on such a valuable niche
I don't take this too seriously because lots of physicians use ChatGPT already.
Lots of physicians use ChatGPT but so do lots of non-physicians and I suspect there's some value in knowing which are which
I don't think you can use an LLM for that. For the same reason you can't just ask it to "Make the app secure and fast"
This is completely incorrect. This is exactly what LLMs can do better.
> Why wouldn't an LLM based search provide the same thing? Just ask it to "use only trusted sources".
Is that sarcasm?
why?
How does the LLM know which sources can be trusted?
yeah it can avoid blogspam as sources and prioritise research from more prestigious journals or more citations. it will be smart enough to use some proxy.
You can also tell it to just not hallucinate, right? Problem solved.
I think what you'll end up is a response that still relies on whatever random sources it likes, but it'll just attribute it to the "trusted sources" you asked for.
you have an outdated view on how much it hallucinates.
The point was: will telling it to not hallucinate make it stop hallucinating?
Much of the scientific medical literature is behind paywalls. They have tapped into that datasource (whereas ChatGPT doesn't have access to that data). I suspect that were the medical journals to make a deal with OpenAI to open up the access to their articles/data etc, that open evidence would rely on the existing customers and stickiness of the product, but in that circumstance, they'd be pretty screwed.
For example, only 7% of pharmaceutical research is publicly accessible without paying. See https://pmc.ncbi.nlm.nih.gov/articles/PMC7048123/
Do you think maybe ~10B USD to should cover all of them? For both indexing and training? Seems highly valuable.
Edit: seems like it is ~10M USD.
If it turns out that AI isn't much more productive, it could also turn out that people still believe it is, and therefore don't value software companies.
If that happens, some software companies will struggle to find funding and collapse, and people who might consider starting a software company will do something else, too.
Ultimately that could mean less competition for the same pot of money.
I wonder.
I left software about 10 years ago for this reason. I saw engineers being undervalued, management barriers to productivity and higher compensation possibilities for non-tech functions.
I'm not really understanding why Thomson Reuters is at direct risk from AI. Providing good data streams will still be very valuable?
They’re one of the two big names in legal data - Thomson Reuters Westlaw and RELX LexisNexis. They’re not just search engines for law, but also hubs for information about how laws are being applied with articles from their in house lawyers (PSLs, professional support lawyers - most big law firms have them as well to perform much the same function) that summarise current case law so that lawyers don’t have to read through all the judgements themselves.
If AI tooling starts to seriously chip away at those foundations then it puts a large chunk of their business at risk.
The commodification of expertise writ large is a bit mind boggling to contemplate.
TR will not disappear. But their value to the market was "data + interface to said data" and that value prop is quickly eroding to "just the data".
You can be a huge, profitable data-only company... but it's likely going to be smaller than a data+interface company. And so, shareholder value will follow accordingly.
Seems like they should hold tight to that data (and not license it for short-term profit), so customers have to use their interface to get at it.
If customers start asking Claude first, before they ask Thomson Reuters, that's a big risk for the later company.
Got it, thank you for the insight.
The assumption is that Claude has access to a stream of fresh, currated data. Building that would be a different focus for Anthropic. Plus Thomson Reuters could build an integration. Not totally convinced that is a major threat yet.
Huge legal tech business units
Could this lead to more software products, more competition, and more software engineers employed at more companies?
I think the argument is that tools like Claude Code will cause more companies to just build solutions in-house rather than purchase from a vendor.
This is correct. AI is a huge boon for open source, bespoke code, and end-user programming. It's death for business models that depend on proprietary code and products bloated with features only 5% of users use.
possibly also a boon for automated testing tools and infra designed for ai-driven coding.
> Could this lead to more software products, more competition, and more software engineers employed at more companies?
No, it will just lead to the end of the Basic CRUD+forms software engineer, as nobody will pay anyone just for doing that.
The world is relatively satisfied with "software products". Software - mostly LLM authored - will be just an enabler for other solutions in the real world.
There are no pure CRUD engineers unless you are looking at freelance websites or fiver. Every tiny project becomes a behemoth of spaghetti code in the real world due to changing requirements.
> The world is relatively satisfied with "software products".
you can delete all websites except Tiktok, Youtube and PH, and 90% of the internet users wouldnt even notice something is wrong on the internet. We dont even need LLMs, if we can learn to live without terrible products.
I kind of imagine more people going off and building their own companies.
I think so too. But because of code quality issues and LLMs not handling the hard edge cases my guess is most of those startups will be unable to scale in any way. Will be interesting to watch.
Not if they don't have access to capital. Lacking that, they won't be building much of anything. And if there a lot of people seeking capital, it gets much harder to secure.
Capital also won't be rewarded to people who don't have privileged/proprietary access to a market or non-public data or methods. Just being a good engineer with Claude Code isn't enough.
maybe eventually, not in the near-term future.
I think companies will need to step up their game and build more competitive products with more features, less buggy and faster than what people can build
It’s demonetizing process rent-seeking. AI can build whatever process you want, or some approximation of it.
Can this really be a kind of herding stampede behavior over Cowork? It’s been out several days now and just all the sudden today, all the traders suddenly got it into their little herd animal heads that everyone should rush to the exists… after that equally sketchy silver and gold rug pull type action last week?
Something seems quite off. Am I the only one?
Markets are not as efficient as the textbooks would have you believe. Investors typically rely on a fairly small set of analysts for market news and views. It might take those guys a while to think about stuff, write a note etc. The deepseek crash last year lagged by several days as well.
I'm out of the loop, but I thought there were sophisticated automated trading algorithms where people pay to install microwave antennas so they can have 1ms lower latency. And I thought those systems are hooked up to run sentiment analysis on the news. Maybe the news is late?
It could also be that we have been in an economy-wide speculative bubble for a couple of years. Whispers of an AI bubble were a way to self-soothe and avoid the fact that we are in an everything bubble.
Paypal fell 20% today.
PayPal reported an earnings miss and a new CEO before market open today, that’s why it sold off.