Close Encounters of the Third Kind. (E.T. communication will be weird). The Man from Earth (What it might be like to live through several ancient ages). Citizen Kane (Simple things in life matter--Rosebud). The Fountain (What it might be like to live through several ages with unrequited love). FernGully (Don't mess with nature, or small humans will mess you up).
Same here. One of the few movies that really stuck. Explores the philosophy of human vs mortality, and how time may not cure all wounds. I will now try to watch it again this weekend.
Good point. It seems that in the first case, "sitting in the kitchen" is a restrictive clause and we might want to have "John threw out the old trash that was sitting in the kitchen." to eliminate ambiguity. However, this clashes with DLM. The second case would be better as "Sitting in the kitchen, John threw out the old trash." I think they gave a bad example.
"We will try to do this for every company..." If for some reason this term is not exercised, it will now unequivocally reflect badly for the company. I don't question the good nature and authenticity of a YC "try", but the sentence does naturally express doubt.
We will do it whenever we possibly can--our goal is 100%. There have been occasional instances where a company doesn't get us docs until 3 hours before a close or something.
The subtitle of the article is "What Machine Learning Teaches Us About Ourselves"; This is backwards. Brain sciences inform ML (In fact, ML techniques are often coined after the biological counterpart). A result or finding in ML does not necessarily, or at all, imply anything for neuroscience.
Artificial neural networks do not teach us about biological neural networks, or 'Neuronal Networks', a term reluctantly used by a close neuroscientist for contradistinction. We don't need Google's cat research, but Hubel and Wiesel's cat research.
Let's see: Cheap reference to Kant, check. Vague parallel to the Sapir-Whorf hypothesis, check.
The 'intriguing' mapping that involves 3 ML terms is desperate.
This article appearing on the front page of HN shows how delusional some of today's ML lovers are with respect to neuroscience, the discipline that actually studies human brains.
Frederick Jelinek, a researcher in natural language processing, has a funny quote, "Every time I fire a linguist, the performance of the speech recognizer goes up."
In general, I think a neuroscientist would be a distraction to any ML team. I don't mean to say that neuroscience is what drives ML insight, but if asked to pick which field influences the other most, my choice is clear.
