Lest we forget, here is their piece de resistance, dripping with VC gravitas, about the role of tech in the midst of the covid crisis: "It's Time To Build" [0]
What did they end up investing in? NFTs and shitcoins.
I haven't read too closely, but no one is building meaningfully affordable housing in Atherton. Each unit in the development would easily sell for millions.
CA/the bay area should focus on packing high density housing closer to transit lines, not lifting apartments in areas that are an hour+ walk from transit to score political points.
To the best of my knowledge it's mandated by the state — our old city council used to refer to our town as "complete" and slow rolled housing an approach which, to the best of my knowledge, would just yield state intervention with local decision-makers removed.
The fallacy of the excluded middle, also known as a "false dilemma" or "false dichotomy", is what happens when two options are presented as being the only possibilities when, in fact, there may be other options that exist.
TBF, the roll of a VC isn't to be on the cutting edge of science, but rather business, and generative AI is very new business, even if it isn't very new science.
Let us not forget history. Generative AI (informally defined as "algorithmic generation of stuff" for the sake of argument) has been around for more than 40 years. For example,
Sure, if we define "Generative AI" as "algorithmic generation of stuff" then it has been around for a long time.
I disagree that this is what people are really referring to when they use the phrase generative AI and basically none of the techniques being used can really be said to be 40 years old.
A buzzword - generally I would say it refers to using unsupervised training of some neural network model and then generating new data in the domain from the model.
I believe it originally grew out of the phrase "generative model" (which models the joint data probability distribution) but most of the prominent 'generative AI' models (like GPT) are not actually generative models but discriminators.
Regardless, outside of simple things like matrix multiplication, the theory of backpropagation (although not the implementations), language modeling as a concept, etc. - almost all of these techniques are within the last decade and a half or so.
Click back a couple years and you'll find this page: https://news.ycombinator.com/from?site=a16z.com&next=2981684... with submissions like "DAOs, a Canon" https://news.ycombinator.com/item?id=29440901