- How we fund 🧫 science today
- Why grants process is wasteful
- Using (partial) lotteries to fund science
1/ Writing grant proposals for raising funds takes a significant amount of time and, unlike papers, they aren't published in journals or valued for their scientific contribution.
2/ With grant rates now in single digits in many fields, scientists are spending more time raising funds than doing actual science.
Is there a better way?
3/ Kevin Gross, professor at @NCState, urges us to explore alternative ways of funding science.
One such suggestion is using partial lotteries to award grants which, according to the models he's built, generate more scientific output for the society than current methods.
4/ Here's what we cover in 1 hour interview.
5/ My favorite bit is at the end.
Why should we care about how science is funded?
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You've heard of AI. But have you ever heard of IA?
🚀🚀
Today, at @VWO, we're announcing a big shakeup of the A/B testing industry.
(a thread about our breakthrough innovation)
1/ Our mission to help marketing and product teams reduce the effort required for figuring what works best for their business
In 2010 we pioneered the DIY visual editor for business teams for editing webpages and creating their variations for A/B tests without involving IT teams
2/ That innovation cut the effort to launch an A/B test from weeks to hours
But, as anyone who has run an A/B test knows, you still have to wait for weeks in order to start getting statistical significant results about which version is better.
1/ Imagine an economy that keeps on growing indefinitely.
It's essentially a non-zero-sum economy - as the pie becomes bigger, *everyone* becomes better as even a small percentage of a really large number is substantial.
2/ A capitalistic economy is a fantastic invention - entrepreneurs compete to give consumers more value cheaply.
Markets create incentives for innovation, and innovation helps the world become richer as over time more and more human desires are satisfied.
- how 🧪 science happens
- why small teams do big scientific breakthroughs
- similarities between startups and 🔭 scientific endeavors
- what research shows about the path to success
1/ @profjamesevans is the Director of Knowledge Lab, and faculty at the Sociology department at the University of Chicago.
He uses machine learning to understand how scientists think and collectively produce knowledge.
Watch the entire podcast here:
2/ Here's all the topics we cover in this interview:
Been thinking about computationalism - that our universe is a computer and/or that we're in a simulation.
There seems to be a contradiction in the argument (below).
Can someone help answer?
Since a simulation of water doesn't wet anything or simulation of a black hole doesn't create a black hole, why do we believe that a simulation of consciousness will itself be conscious?
If a simulation can't be conscious, is computationalism false?
In other words:
I get that consciousness can be a property of certain arrangement of physical systems, but what I don't get is how it can be property of certain computations (since the same computation can be implemented in many ways - microchips, pulleys, vacuum tubes, etc.)