1) Machine learning can help rationalize the "experience and intuition" of chemical research by finding patterns and exceptions from large amounts of chemical data to predict new materials and phenomena.
2) While in theory chemical structures and properties can be described by Schrodinger's equation, it is impossible to solve for realistic systems, requiring approximations. Machine learning may help address this challenge.
3) Chemists have successfully created compounds with desired properties through "experience and intuition", which involves inductive reasoning from experiments rather than purely deductive logic, incorporating serendipitous findings.
8. 帰納 (経験と勘) と 演繹 (科学法則)
The grand aim of science is to cover the greatest
number of experimental facts by logical deduction
from the smallest number of hypotheses or axioms.
─── Albert Einstein
仮説・モデル 実験的な事実(データ)
演繹
帰納・仮説形成
「経験」
「勘」(Serendipity?)
9. 帰納 (経験と勘) と 演繹 (科学法則)
The grand aim of science is to cover the greatest
number of experimental facts by logical deduction
from the smallest number of hypotheses or axioms.
─── Albert Einstein
仮説・モデル 実験的な事実(データ)
演繹
帰納・仮説形成
「経験」
「勘」(Serendipity?)
ここは確かに
logicalだけど…
…
10. 帰納 (経験と勘) と 演繹 (科学法則)
The grand aim of science is to cover the greatest
number of experimental facts by logical deduction
from the smallest number of hypotheses or axioms.
─── Albert Einstein
仮説・モデル 実験的な事実(データ)
演繹
帰納・仮説形成
「経験」
「勘」(Serendipity?)
ここが全然
logicalじゃない…
ここは確かに
logicalだけど…
…
11. 帰納 (経験と勘) と 演繹 (科学法則)
The grand aim of science is to cover the greatest
number of experimental facts by logical deduction
from the smallest number of hypotheses or axioms.
─── Albert Einstein
仮説・モデル 実験的な事実(データ)
演繹
帰納・仮説形成
「経験」
「勘」(Serendipity?)
ここが全然
logicalじゃない…
ここは確かに
logicalだけど…
…
今⽇日の話:(⼤大量量)データに基づく推論論により合理理化可能?