bertday

The model can return the internal details of a potential future product. For example, the next Pixel phone.

The language is supposed to tell you if your thinking is broken. If a program is a logical statement, and your logic is impossible, the program should not compile. Reading dead memory or having race conditions should not be possible, yet look at security vulnerabilities today.

It doesn’t have to be a totally new language. Javascript is an example where there are multiple front-end languages. You can go as far as formally prove the implementation is correct, too. Language theory is an abstraction for mathematical logic and proofs, so it touches anything logical at all.

Quora is often self-promotion now. The template I think of when replying to your comment is:

Great point you bring up on how useless <website> is. As the CEO of <random company>, this is a problem we have put a lot of effort into addressing. You may consider the following as a solution: …

Sure, writing bug-free code is not possible for most programmers. The language can reduce the occurrence of bugs.

New York Times ran an article yesterday saying otherwise. First tier cities, in terms of size, are losing people, but second tier cities are growing. The cost of living in the largest cities puts a negative force on moving to them.

Being near profitable is the obvious way, though I find that surprising early on.

Randomly perturbing the weights and then finetuning would probably make it impossible. If someone had access to the finetune dataset and you didn’t add noise, they could see if the finetuning curves intersect.

I guess in practice, it’ll look suspicious if you have an identical model architecture and have similar performance.

Postdocs are sometimes used as a mechanism to play games with tenure rather than getting the an academic job. You get a publication “head start” without invoking the countdown, and you already often have a future job in hand early.

The diagram has 3 input companies and 3 output companies, so at a surface level it seems nothing has changed. Even Google Fiber couldn’t compete with the big guys because (at least partially) these utility companies are so entrenched in lobbying etc.

I don’t doubt the break-ups are effective in the short term, but the long-term behavior in this case seems to be less affected.

AT&T just re-merged after the break-up, so it’s a bad example.

See the diagram: https://www.theverge.com/2016/10/24/13389592/att-time-warner...

Same is true in academic research (though old-timers catch it often). The common pattern is:

* approach “A” was invented in 1970 or so and didn’t work

* “B” extends “A” in multiple ways and now works

* noobs assume “B” invented “A” and treat “B” as the root of modern knowledge. “B” often has more market presence so noobs (without deep understanding) don’t see the relationship to prior attempts.

Examples:

* AlexNet/deep learning/ML in general

* MapReduce/databases/functional programming primitives

* Docker/chroot “Jail” Containers

* Bitcoin/90s coins/blockchains

Ego and ignorance are rarely a great combination :)