Why AI for Science?
“We wanted flying cars, instead we got 140 characters.” Peter Thiel said in 2013.
The statement was generally true even years later. Despite the fast evolution of technology and the huge amount of wealth it has created, it seems that science has been disporportionally under exposed to such development. The best minds on earth have been pouring their talent onto making more excuses to show us ads for the past two decades, why not harness their collective wisdom to advance our understanding of the universe?
From generative industrial design to de novo drug development, the application of AI in the scientific domain is as inspiring as it is profound. The landmark achievement of AlphaFold2 is evidence that “AI for Science” is no longer notional but actively in the making. If Steam Engine, Electrification and Computer inked the first three technology revolution, then IMHO, AI for Science has the potential of becoming the forth.
However, just like any other new technology, there is no absence of hype, noise and misinformation. As an active entrepreneur in the field of AI for Science, I would like to share my journey as I go through it and unapologetically enunciate my views and predictions as I try and err.
About me
I’m a Berkeley trained engineer, a humble student of mathematics, a serial entrepreneur and an active angel investor. I have been investing in Silicon Valley since 2016 and have been writing about tech since 2013. If you’d like to connect, I’m mostly active on LinkedIn.
My priorities for this blog in descending order are:
readable
relevant outside of the ivory tower
transparently subjective
Please do not expect the rigor of a scientific paper, or the pseudo neutrality of putting correctness before truth.
