Andrew Carr: I've heard a lot of things blamed on...| Robocrunch AI

I've heard a lot of things blamed on the labor shortage recently, which is super convenient for me

Model overfitting? Labor shortage
Failed to reject H0? Labor shortage
Not enough GPUs? ... Well, that one may be true
— Andrew Carr (@andrew_n_carr) May 8, 2022

Question: Why should you care about overfitting in #MachineLearning? Answer: You had ONE job... https://t.co/kPcnDsy1ml

Shared by Cassie Kozyrkov at 11/2/2021

Two forces in manufacturing are converging and manufacturers have the opportunity to improve their production methods while addressing labor shortages. Manufacturing is Getting ‘Futurized’ with #ArtificialIntelligence https://t.co/ddlgIO4a1C

Shared by Neurala at 3/14/2022

It is quite remarkable how ETH mining ends up building clusters with enough GPUs you could train some really large models. (Per this tweet: https://t.co/UXUpxkLdXK ) [Obviously, the networking and other infra isn't quite right for AI training, but what a lot of GPUs!]

Shared by Jack Clark at 12/17/2021

Underfitting versus Overfitting... which one is worse (and why)? https://t.co/gF2JHW8PNM #AI #DataScience #MFML #MachineLearning

Shared by Cassie Kozyrkov at 11/9/2021

On March 22 and 23, from 9am to 5pm ET, see how companies like you are beating the labor shortage at our virtual expo, Collaborate: Amplify Workforce Productivity. https://t.co/LJcGepbgAQ #manufacturing #automation

Shared by Universal Robots at 3/11/2022

This further highlights @sleepinyourhat's point that we should be extremely careful when making system limitation claims about contemporary models. Small gains on saturated benchmarks can be deceptive & correspond to much greater qualitative differences in model capabilities! 🤔

Shared by Max Bartolo at 11/2/2021

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