#AI at IA this Wed's #DWeb Meetup: come hear how decentralization & open data may be key to #AI's future w/ talks by @StabilityAI, @OpenAI, @AiMozilla & Gun Database founder @marknadal.
Food, drinks, networking & deep learning about #AI:
https://t.co/pTXsTBioQk
But the nerdy enthusiasts will build stuff for them on top of AI as well. Which will also presumably have higher adoption rates, since so many end users will already be believers.
@OfficialLoganK@Suhail Second movers get to eat the cheese while the first movers lie with their back broken... appreciate those willing to be first movers.
@corcoranwill@igorsyl@TO@johnennis@paulg@TerjeNorderhaug Hah! I leveraged Common Lisp for my first startup in grad school, having independently had the same insight as @pg in "Beating the averages". In 1995 we shipped the first social web platform. https://t.co/4i8I2rRkmw
@dotta@OfficialLoganK Functional languages should benefit generative AI by keeping computation/semantics local. Unfortunately, due to the selection of training examples, current models are biased in favor of imperative languages.
@dotta@OfficialLoganK If you use lisp you can almost fit the whole program into the context window - if it weren't for that a dash `-` count as a token, so symbols with dashes will quickly eat up the limited number of tokens available.
@OfficialLoganK Pre-trained language models seem to have hidden representations of abstract syntax trees. I am leveraging this in a language with a syntax close to the AST.
@TO Lisp is also great for programs that process Lisp code. That's why the Clariform linter & formatter for @clarity_lang smart contracts is written in Lisp: https://t.co/G0uJZHoIzs
@TO People new to programming may be quicker to pick up Lisp syntax than many developers already set in their ways from programming in other languages. Lisp has a minimalistic syntax that is easy to introduce.