Wouldn't the equivalent be incentivizing employees to rent out their own place on Airbnb? I'm sure that plenty of Uber and Lyft employees are customers without it being a Big Deal.
Yes, that'd be the equivalent to this specific situation. Airbnb incentivizes that as well. I don't remember the exact details, but in an interview with one of the founders, he said they have a program for employees who host Airbnb guests.
I had a similar experience trying to use an LSTM model / TensorFlow based on the Shakespeare RNN example.
This doesn't generate novel, meaningful text content without a template, but I'm unaware of any machine learning model that does this well (OpenAI's included). This model does absorb the 'rules' of the text, both grammar and structure (character names and dialogue, scene introductions, etc)
As someone with a similarly retro web framework ( https://fortran.io ), as far as I know, no one has switched to it. I have gotten a few serious inquiries from coders in the sciences or who are making use of their old Fortran skills... but only a very few in two years.
There's no need to mention it was unpaid, unless it was infrequent enough that you think the company would deny you worked there at all. If the other part-time job was at the same company, I think your CV would look like this (newest role first - so, reverse chronological order):
Other Job, CORP: Other job's responsibilities, and additional sysadmin work (specific technologies or routine tasks)
Yes to both. There are at least two gold-backed cryptocurrencies designed for a strict interpretation of Islamic Finance (HelloGold in Malaysia, OneGram in Dubai).
There is also a basket of 15 currencies plus gold, called Globcoin, though the balance of currencies, what currencies you could buy and sell Globcoins with, and relative share of each coin was difficult to interpret when I was looking into it.
So, is this picking up on large landmarks which are visible in StreetView? Sun position in imagery? In Manhattan can it see a sign reading W 53rd St and know whether to go north or south to its destination? The paper suggests that there are learned landmarks, but doesn't talk about street signs at all. As a New Yorker, that would be the first method I would use to reach a destination.
It's a neural network so chances are, we'll never know how it came up with it's decision. For CNNs we can look at the output of each layers to get a hint but the more diverse the architecture is (such as in this example) the harder that becomes.
I was the only engineer at a not-tech-oriented NGO, so they had me on-site to check up on the team developing their app. At the end of December they had an initial app - I'm not a mobile dev, but it looked OK for an MVP. We showed it to leadership and everyone approved.
We then went on 2 weeks vacation. When I came back, I was surprised to hear the contract was nearly up - they had supposedly been working over our vacation. This app looked identical to the MVP we'd seen before. I was upset, but there wasn't much we could do. Also it turns out the app didn't look flashy enough for leadership. This was a major wake-up call for me - I messed up here by not critiquing the app or making clear work hours expectations - but also I discovered that demo-ing an app to a whole group leads to a lot of group-think. The criticism only comes later and then you are screwed.
