liquidmetal

How do your benchmarks compare against CoreML?

In my experience there are many lesser significant hyperparameters that can impact performance when going from the released code to your personal favorite framework.

Nothing you can't figure out by reading source code of the two frameworks or by reading the documentation closely.

Generally, people don't seem to care about reproducing exact metrics - as long as it is close enough they're happy. You need to dig a bit deeper if you want the full quality.

Permanent residents are also subject to the expatriation tax AFAIK.

Chicago Tribune doesn't show the website in India?

+1

There can be hidden variables that the PID system failed to account for. Workload distribution over time, temperature at the time of day, heat leaking into the datacenter, etc. I'm not sure if a PID based controller would account for such things.

What remains to be seen, however, is whether these manipulations keep the machines working at similar efficiencies and if they fail at similar rates as before turning on the control system.

Tangent here - self-awareness is an evolutionary cul-de-sec? Do you have any further reading suggestions on this?

And then submit a paper to the same conference from where we collected the papers.

The fact that this file format doesn't enclose the AdobeRGB vs sRGB information is a deal breaker.

A lot of computer vision research datasets uses a similar file format - so I can see its use there. But things like movie creation, publishing, etc will probably never adopt this.

They probably already have you fingerprints.

Not again.

No machine learning? Really?

It seems like for every problem out there - at least some tiny bit can be solved by machine learning.

General pattern recognition (identifying peaks, predicting disk outages, etc) at the minimum seems like a requirement that will show up in the next few years.