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erikbern

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erikbern
·há 2 anos·discuss
Spoiler alerts but this exactly the plot twist at the end of the book "Around the World in 80 Days" by Jules Verne

https://en.wikipedia.org/wiki/Around_the_World_in_Eighty_Day...

The following day Fogg apologises to Aouda for bringing her with him since he now has to live in poverty and cannot support her. Aouda confesses that she loves him and asks him to marry her. As Passepartout notifies a minister, he learns that he is mistaken in the date – it is not 22 December, but instead 21 December. Because the party had travelled eastward, their days were shortened by four minutes for every degree of longitude they crossed; thus, although they had experienced the same amount of time abroad as people had experienced in London, they had seen 80 sunrises and sunsets while London had seen only 79. Passepartout informs Fogg of his mistake and Fogg hurries to the Club just in time to meet his deadline and win the wager. Having spent almost £19,000 of his travel money during the journey, he divides the remainder between Passepartout and Fix and marries Aouda.
erikbern
·há 2 anos·discuss
> Pay yourself and a VC-appointed board member below market rate, hire six good engineers, lease some office space, buy equipment, pay for legal and accounting services… and presto, you’re burning through $5M a year

Would love to see the math behind this. How does this add up to $5M/year??
erikbern
·há 2 anos·discuss
Founder of Modal here. We've spent a ton of time on this, including building our own distributed file system optimized for low-latency high-througput workloads. We don't use K8s or Docker and built our own custom infrastructure instead.

Cold starting containers quickly is a fascinating problems. We've gotten a long way but there's still a lot more to do. For GPU-based inference, starting containers isn't enough – you also need to initialize the model GPU quickly. We are working on a long list of things that will bring down cold start latency even further.
erikbern
·há 3 anos·discuss
Annoy author here. What you're describing is Locality Sensitive Hashing (LSH) which is something I spent a lot of time trying back in 2009-2012 but never got it working. It has some elegant theoretical properties, but empirically it always has terrible performance. The reason I don't think it works well is that data often lies near a lower-dimensionality manifold that may have some sort of shape. LSH would "waste" most splits (because it doesn't understand the data distribution) but using trees (and finding splits such that the point set is partitioned well) ends up "discovering" the data distribution better.

(but HNSW is generally much better than this tree paritioning scheme)
erikbern
·há 4 anos·discuss
I don't really buy this argument that you can rent and pay $1000/month, or you can buy an equivalent home and pay $1000/month, but now you can deduct interest rate and build equity.

Landlords can also deduct their interest expenses and so they benefit from leverage too (meaning they don't want to build up equity).

In a reasonably efficient market, this means that the equivalent cost of homeownership would be higher than rent, to offset these things (the rate at which you're paying down the principal, and the deductability of interest rate expenses). This is obviously a very simplified argument, and there's a lot of other factors going into this.
erikbern
·há 5 anos·discuss
haha, author here, I do admit that Matt Levine is one of my favorite writers today