Recent submissions

Comment · 1 year ago
So they’ll just die when Google has a seamless AI-first mobile experience where consumers just ask their Pixel to do X and it happens. Disruption comes for everyone, hardware isnt a moat
Comment · 1 year ago
These numbers are certainly wrong lol
Comment · 1 year ago
It’s more like conditioning the posterior of a response on “Ok, so…” lets the model enter a better latent space for answering logically vs just spitting out a random token.
Comment · 1 year ago
I think you're almost right

I suspect its more a structural issue

e.g. because of Big VC (a16z, other firms with dozens or hundreds of investing staff), VCs don't stick around firms long enough for real returns (cash distributed) to matter. If you're at a place and your stuff is marked up 10x after 4 years, you just hop to become a GP and try to ride the next markup wave. Even if these people exit VC after 10 years that is still 10 years of deals that all flopped.

This might not even be the individual VC's fault -- there may just be too many venture dollars chasing too few power law returns, so you get a surge of startups circa 2019-2022 that all disappear

Comment · 1 year ago
literally how openai attracted talent with deepmind as the boogeyman. its a playbook that works
Comment · 1 year ago
As is usually the case, check the data! A lot of the dataset used has fairly morbid scenarios, so the model is working as expected. All the data was synthetically created with GPT4
Comment · 1 year ago
Comment · 1 year ago
Im reviewing linear algebra now and would also love to know that book!
Comment · 1 year ago
I actually think there are a few, only some have achieved critical mass with smaller subnetworks. BlueSky and Threads both seem to have attracted non-tech networks although Threads downranked political content, so BlueSky seems like the natural next mass appeal product.

Others:

Mastodon: many tech subnetworks (security, data)

Nostr and Warpcast: Crypto

Comment · 2 years ago
This is exactly how Ive seen things occur. It makes a lot of sense, given some tools are great new additions (coding especially), but others fall flat (IMO, search)
Comment · 2 years ago
You can learn things top-down or bottoms-up. I can read & understand most reverse engineering posts like this because I have a strong "bottoms-up" foundation with an EE degree and worked with microcontrollers. But when I read posts by hobbyist mechanical engineers about some 3D printed piston that uses ball bearings I have to approach it in a top-down "recreate what they did and go deep any time I'm lost" manner.
Comment · 2 years ago
I think you’re exactly right, it’s a show for insiders to know what these 4 people think so the next time they directly or indirectly encounter them they are known quantities. Its masked as news & informative media but its principally brand marketing for these 4 people and their funds & companies.
Comment · 2 years ago
Cut 80% of jobs and 80% of revenue

That is not what shareholders want, hence why no one is copying it

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