There's a huge gap in what is official and what happens in reality. I'm in the legal space and it's clear that there's no massive documentation repository or data set containing the advice lent to clients because that advice does NOT always match a logical deduction based on the rules. Some professions have an enormous store of personal experience and poorly documented data that plays a key role in their success.
There is a lot of ai training data from online content, journals, articles, enterprises and such but do you feel like there is a gap in ai training data somewhere?
Cynthia has a powerful algorithmic moat, and it is highly unlikely that competitors such as Algolia and Bloomreach will reinvent it anytime soon, as their value setting is at odds with the discovery.
Additonally, no LLM such as GPT-4 can achieve this use case as an entire product catalog, or an entire music streaming app and associated playlists, can be loaded into a context window, let alone queried in real time with guaranteed correctness.
Building on your general argument. This is a useful post from a16z https://a16z.com/the-empty-promise-of-data-moats/
Also, purpose-built UIs can be a moat.
There's a huge gap in what is official and what happens in reality. I'm in the legal space and it's clear that there's no massive documentation repository or data set containing the advice lent to clients because that advice does NOT always match a logical deduction based on the rules. Some professions have an enormous store of personal experience and poorly documented data that plays a key role in their success.
There is a lot of ai training data from online content, journals, articles, enterprises and such but do you feel like there is a gap in ai training data somewhere?
Completely agree... Unfortunately most of the organaisations running behind THE BEST models instead of managing better data quality...
Have a look at Cynthia Systems and one of our recent blog posts:
Paving the Way for Bias-Free Artificial Intelligence
https://cynthiasystems.com/blog/paving-the-way.html
Cynthia has a powerful algorithmic moat, and it is highly unlikely that competitors such as Algolia and Bloomreach will reinvent it anytime soon, as their value setting is at odds with the discovery.
Additonally, no LLM such as GPT-4 can achieve this use case as an entire product catalog, or an entire music streaming app and associated playlists, can be loaded into a context window, let alone queried in real time with guaranteed correctness.
We don’t have moats, but we may have a garbage collector of all the stupid things people want our llm to do?