The researchers found that the new material’s elastic modulus — a measure of how much force it takes to deform a material — is between four and six times greater than that of bulletproof glass. They also found that its yield strength, or how much force it takes to break the material, is twice that of steel, even though the material has only about one-sixth the density of steel.
The point of this story is to illustrate that the Dunning-Kruger effect has nothing to do with human psychology. It is a statistical artifact — an example of autocorrelation hiding in plain sight.What’s interesting is how long it took for researchers to realize the flaw in Dunning and Kruger’s analysis. Dunning and Kruger published their results in 1999. But it took until 2016 for the mistake to be fully understood.
We’re told Google has used this AI system to produce the floorplan of a next-generation TPU – its Tensor Processing Unit, which the web giant uses to accelerate the neural networks in its search engine, public cloud, AlphaGo and AlphaZero, and other projects and products.
In effect, Google is using machine-learning software to optimize future chips that speed up machine-learning software.
“The quality of the signals is sacrificed a little by the electrodes being in a blood vessel, rather than directly on brain tissue. But it’s good enough to allow the two participants in the study to accurately type up to 20 characters per minute with predictive text disabled, and do online shopping and banking, all without lifting a finger or using voice commands. “
We are not generally allowed to use Foreign Keys in our databases at my job. This article presents several reasons why this is a good idea:
By bringing AI collaboration to the fore, every system will be able to learn from every other, and there will be a coordinated approach to data sharing.
A very useful comparison of MySQL and MariaDB.
As computer vision quietly spreads through our lives and landscapes, it’s entertaining and practical, powerful and flawed, amusing and disturbing. The same goes for AI as a whole. You can’t see it. But it’s everywhere.
“There were no conclusions,” said Henry Dills, a photographer and cellist who watched the performance dressed in a brown sport coat and a white scarf that reached past his waist. “These machines are starting to massively overshadow us. It used to be God. Now it’s machines.”
Overall I have mixed feelings about the value of a computer science education, mostly because of the personal benefit I have gotten from mine. For most cases though, I think it is severely overvalued. It’s very strange to observe an industry with major talent shortages, and then to know perfectly good self-taught programmers get prematurely rejected in interviews because they don’t have a computer science background. I hope to see the industry improve in this respect, but in the meantime I’m happy to exploit this imbalance as a competitive advantage.