dgax

It will be interesting to see how it plays out, but it's worth noting that there is a healthy amount of suspicion, some fear, and even a little bit of animosity toward google in the US health care industry. Opinions about surveillance and marketing (mis)uses aside, getting data can be a long and difficult process even for seasoned researchers in teaching hospitals. Personally, I don't fancy giving them my medical records any time soon.

I can't wait to see these in Pittsburgh. If they can merge into traffic going into the Liberty Tunnels after a Pens game they can handle anything.

That being said, with the bulk of the reliable automation being on largely uninteresting well-labeled stretches of flat highway, doesn't it make sense to test these on long road-trips before we subject them to the volatile nature of city driving? I'd be interested in any insight into how engineers are tailoring these vehicles to their -at least by my standards- comparatively challenging urban testing grounds. Even if they've been trialed on road trips, this will be a very public and thus very decisive debut.

The article, especially some of the examples, seems abusive to low-wage employees. How many of us would give a job description that said 'this is not a preparation for a slow motion contest' a second glance?

The meat and potatoes of the article is mostly just complaints to be honest. A lack of candidates is always the go-to excuse for managers and executives when explaining poor productivity or vacancies. Job seekers will gladly tell you that the pay stinks or that they just flat out don't want to work for a company.

Dig deeper and ask the managers and executives to show how they reward and retain employees with these skills.

It's not surprising that TF is the slowest in many cases. It has been widely, sometimes harshly, criticized in the past for that reason. On the other hand, despite its speed TF appears to be the only tool that doesn't have to sit out any of the tests due to incompatibilities or lack of features.

Other tools like MXNet deserve a shoutout as well, and it would be interesting to see how a wider group compares. MXNet also integrates seamlessly into R, something of a rarity in deep learning tools (excepting the also excellent h2o package).

The article seems to focus more on instances where food production is a limiting factor. Land use is less of a problem in places where we have (collectively) enough food and people tend to focus more on the very serious environmental impact of large-scale agriculture. In the latter case, I would except a diet lower in meat to fare much better than the alternatives simply because it requires fewer acres to be farmed (or the same acres less often as the article points out) and thus has lower pollution output.

I had the same issue with my VW where it was activated without me signing the paperwork. The official line I got from VW was that it couldn't be removed or deactivated because it is 'safety equipment'.

VW is shady.