Readit NewsI'm a little hopeful that the discussed H1-B reforms may actually help countries obtain particularly niche talents more than the outsource-lottery played now.
But I think the real threat to our tech dominance is privacy concerns. The U.S. owns the cloud with AWS, GCP, and Azure, but if other countries can't use their services due to US government overreach, then I'm sure strong competitors will pop up elsewhere.
This is a very good point. Add on to this, tech industry among some of the businesses that benefits most from an open global economy, and would hurt most from Trump's protectionism.
For example, Google has over 90% market share in certain european countries, and EU is viewing the new administration more and more as a threat, isn't that dangerous to have someone you don't trust control your entire internet industry? I believe both European governments/society will now be more motivated to push the agenda to grow local competitors that works better for them.
I'm sure Mexico would be up to taking advantage of the new congress's policies as a means to irk Trump.
Why not contribute to the economic growth of the underachieving neighbor rather than the overachiever? People talk about sympathizing illegal immigrants from Mexico, but when they have a real opportunity to help develop the place, they kind of forget about them altogether, as if it's just an opinion to have.
Q1 2016 5312 units, revenue $6,746m
Q4 2016 4886 units, revenue $5,739m
Q1 2017 5374 units, revenue $7,244m
"AI beats top 10 hedge fund managers"
to
"AI run hedge fund blows up due to black swan event"
regardless it's an incredible feat. It really casts questions into what our edge as humans are which is slowly disappearing and we didn't even need to put a brain in a jar and hook it up to a computer....it's deep learning reinforced algorithms that is appearing to outlearn, outthink the best of humans.
I just can't emphasize what a monumental period in history we are at. Humans are producing specialized algorithms that learn and hold information about the deep web of relationships between myriads of parameters to produce superior performance than humans.
It's almost like we've uncovered ways to automate our intelligence very much like we've been automating human and animal labor in the past couple centuries.
So the question is, how does an average joe hacker like me exploit and leverage this wonderful thing called deep learning? I'm not interested in reading PHD papers with advanced calculus.
I want to have a map of what AI, ML, DL, NN methodologies to use and when and who to hire based on that. This is no time to be a luddite and don't count on basic income from appeasing the masses anytime soon. Much like people took the most hit in the early rise of industrial revolution, our generation and immediate generation will be hit the hardest.
Well reading paper is a must to get to deep learning. Those papers may not be that math heavy once you are used to it. Most of the time, it is about network architecture and loss objectives.
This is what people mean when they praise things like a "steady hand on the tiller". These coming years are going to be one disaster after another.
https://www.fastcompany.com/3051405/the-future-of-work/the-2...
I don't think paying 110k+ in Bay Area for a entry level is unfair, but from what I can tell, my company has a hard time finding one candidate and often the ones we like also get multiple offers and prefer big companies like Google/Facebook, etc.
Yes, 'qualified' is very subjective standard, however, if you ask 5 experienced people, their opinion towards the same candidate barely changes dramatically from one and another, it is either unanimously yes/no, very rarely in between.
So, I think yes, there is a lot of STEM students, but how many of them actually have actual engineering skills is question left for debate.