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The paradigm is 'declarative AI programming'. When we're done, this will be something like 'differentiable programming' or even 'functional programming', etc. You'll just take it for granted as a way of developing a very large class of software systems and won't bat an eye.
Asst professor @MIT EECS & CSAIL (@nlp_mit). Author of https://t.co/VgyLxl0oa1 and https://t.co/ZZaSzaRaZ7 (@DSPyOSS). Prev: CS PhD @StanfordNLP. Research @Databricks.
GM – Veterans Day 🙏🇺🇸 Today's "45 squared" edition honors US service members with eight overlaid cipher patterns representing the Air Force, Army, Coast Guard, Marine Corps, National Guard, Navy, Space Force, and USO in their respective colors. Once decoded, they combine in formation for the flag. (As square 36, this also happens to be the last perfectly-square token ID in the collection!) As usual, editions are available via private sale at the thematic price of .04545 ETH; some will also be reserved for puzzle solvers. And if you or anyone in your family is a service member (or otherwise connected in a way that would make it particularly meaningful to own a copy), please reach out and I'll gift you one until I run out. Thank you for your service, QED 🟥⬜️🟦
PS: I caught and fixed a very slight encoding error,* so now anyone who collects gets two tokens -- both the corrected and the original version 🇺🇸🇺🇲. * puzzle was probably solvable even with this issue, but didn't want to take any chances 😉
what % of time is cool to spend on explaining to industry friends that DSPy isn't a product so we don't change the paradigm to reach more people? and what % for explaining to academia friends the goal isn't isolated papers but to actually advance a new programming paradigm?😅
The paradigm is 'declarative AI programming'. When we're done, this will be something like 'differentiable programming' or even 'functional programming', etc. You'll just take it for granted as a way of developing a very large class of software systems and won't bat an eye.
and yeah the vintagedata blogpost series was less speculation than actual research program. all the way till small agi.
Reasoning models have come! Co-founder @pleiasfr
RT @getpy: If you are learning DSPy here is a quick reference to help select which module to use when. #dspy
Asst professor @MIT EECS & CSAIL (@nlp_mit). Author of https://t.co/VgyLxl0oa1 and https://t.co/ZZaSzaRaZ7 (@DSPyOSS). Prev: CS PhD @StanfordNLP. Research @Databricks.
I was thinking of the usual cope about «lack of combat experience». China is in a position to do the funniest thing. They produce SO MANY diverse platforms, they can just speedrun the doctrine evolution with internal drills, making any experience gap obsolete.
We're in a race. It's not USA vs China but humans and AGIs vs ape power centralization. @deepseek_ai stan #1, 2023–Deep Time «C’est la guerre.» ®1