Replication of Science Is Massively Underestimated

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i think replication is massively underestimated as a driver of the use of science. Once that's actually considerd like a component of it, justlike what crypto has done. Composable science, composable science, where papers are composable with each other. The kes suetians are composable, just saves everybody just insane amounts of time. And then, you know, now you ask the specific question, you want to repeat that specific question, i kind of like how you see cand of like the most of the mystic visions of cloud laps, a g i, et cetera, influence sciense.

Welcome to Episode Nr. 2 of the DeSci Podcast - Today we're exploring the decentralized science reformation together with no other than Balaji Srinivasan! We're incredibly proud to be joined by such a smart and well-known mind as a second guest on "The DeSci Podcast" show!

Topics of this episode:
→ Key factors holding back scientific progress and how to change it (also via DeSci). 🧪
→ What role does AI play here?
→ The future of human optimalism.
→ How to make predictions in technology?
(+ many more & some great advice for DeSci builders at the end from Balaji)

Due to his nature, we're slipping in many other interesting topics while tackling those above! 💙
A huge thanks again to Balaji for taking the time and for the valuable input - We hope you all can take something away from this episode on your DeSci journey.

Feel free to skip around the timestamps to find your favorite topics and thanks again for tuning in! Also, if you prefer listening to podcasts on audio apps, feel free to search for "How To DeSci" on Spotify, Google Podcasts & Apple Podcasts. You'll also find all links to the podcast apps and the show-notes below.

If you want to join us on the show as a speaker or have guest ideas, please shoot us a mail at podcast@molecule.to
You'll also find all links to Spotify, Discord, Twitter and our website via the link below - https://linktr.ee/thedescipodcast

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Special thanks to:
Alex LaBossiere (Host): https://twitter.com/adlabossiere
Vincent Weisser (Chief Ecosystem Development Officer of Molecule): https://twitter.com/vincentweisser
Balaji Srinivasan: https://twitter.com/balajis
https://balajis.com/
https://balajis.com/the-purpose-of-technology/
https://thenetworkstate.com/

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Timestamps:
00:00 - Intro
01:30 - Introduction of Balaji & The Network State
06:45 - Key factors holding back scientific progress
14:17 - How to change the research & funding structure
21:00 - Commonalities between New York Times and the nature of the Scientific Journals
38:00 - How does scientific progress unfold?
44:50 - Can AI be a dominant driver here?
49:10 - How to make predictions in technology
54:40 - The cyclical approach of history
01:02:48 - Advice for builders in the DeSci space
01:04:29 - Last words, book advice & outro

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Show-notes of the episode:
https://twitter.com/balajis https://balajis.com/
https://balajis.com/the-purpose-of-technology/ https://thenetworkstate.com/
https://nexus.od.nih.gov/all/2021/11/18/long-term-trends-in-the-age-of-principal-investigators-supported-for-the-first-time-on-nih-r01-awards/ https://newscience.org/nih/
https://twitter.com/patrickc/status/1544067890403389441
https://project-evidence.github.io/ https://www.quantamagazine.org/in-new-math-proofs-artificial-intelligence-plays-to-win-20220307/ https://github.com/camoverride/lit/blob/master/The-Princeton-Companion-to-Mathematics.pdf

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Let's connect:
Website: https://bit.ly/3BXtFUn
Twitter: https://twitter.com/Molecule_dao
Discord: https://discord.com/invite/moleculedao

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