I have been thinking about picking this one up for a while, do you think it would be helpful for learning ML in general, or should I start somewhere else?
You might try buying higher quality bacon that doesn't have sodium phosphate or other "pump-up" fluids added. I prefer Kiolbassa brand, as it's truly a different product than most bacon you buy in the store. I believe it is a regional product though, so you may not be able to get any.
I don't use sugar as I try not to eat it, so I substitute stevia. Sugar would change it quite a bit (possibly for the better). This is the only major change.
My apartment-life rib making method is to sous vide for 48 hours in a custom dry rub and liquid smoke, then finishing in the oven to caramelize the sugars and proteins. To someone who doesn't like super smoky barbecue, it's close to perfect and nearly indistinguishable from the real thing. The best part is it's so quick to get started and clean up. It's much more trouble to fix proper sides. They're so inexpensive, too.
Siri is obviously behind Google Assistant on general knowledge queries. It seems like if Siri doesn't understand something, it falls back to unhelpfully searching the web, something that is not useful if you can't look at your phone. Assistant on the other hand attempts (with decent accuracy) to extract a useful answer to your question, and reads it back to you.
This is a great comment, but I feel like you might have missed out on all of the fun of upgrading Rails 2 => 3, which was especially painful. Some large applications are still stuck on 2.x and pay third parties for support because the changes were so large. They were mostly for the better of course, but there's a good chance the parent comment experienced this pain, and this is what they're referencing.
Copied and pasted the quote into Google, with quotation marks. It was on the front page but not the top result. Wayback Machine has it too, but this archive.is (A site I've never used before) is a much higher quality archive.
Structured longitudinal patient data (diagnosis and procedure codes, lab data, step data from fitbits, etc), but with AI unstructured may become more useful as well. This is probably an opportunity in itself.
My parents recently bought a new Windows laptop because their modern iPad can't do all of the things they want. If tablet software can't compete with PC, then their sales are bound to go to zero as PCs like the Surface become more prevalent. Personally, I don't own one as my phablet does everything that I would want a tablet to do, and my PC and Kindle do the rest.
Before you make any of these you need to make sure you're complying with various fire-related regulations and testing against ASTM standards. We ran into this issue at a startup doing something similar about a year back, and it's one of the things that led to its downfall. From the looks of it, you've built a tinder box. Wood paneling, backed by insulating foam, which is likely quite flammable. All wrapped up in a metal container.
If you've ever used Mirth[1] then you've used E4X, for better or worse (usually the latter). It's still used very heavily inside of the transformers, even though Mozilla deprecated it years ago.
After sourceforge bundled malware with downloads, it's hard to trust a project that stuck with them, especially with health data, especially when there are numerous alternatives that are better.
Why would an Allo/Duo user ever want to join a server, or something analogous? They just want to call or message their friend. I think it's obvious to merge some of their consumer point to point apps, but criticizing their group chat solution because they have consumer point-to-point apps is wrong.
This is exactly what I plan to do. Not really because of any specific issue with Docker, it's just that databases have very different lifecycles than your typical container.
Monolithic apps suffer from design for the least common denominator. Business team chat and calling/texting your friend are entirely different problems and deserve different solutions.
From the comments here you would think there is a negativity competition. Chat and Meet are sorely needed, and make GSuite a viable replacement for heterogenous services: HipChat, Slack, GTM, Zoom, Uberconference, etc. Some organizations have all of these deployed simultaneously, along with GSuite, this is a huge win for easier management and lower cost. You can complain about fragmentation of their chat strategy all day long, but most of the apps mentioned here are designed for consumers, not businesses.
It's a great idea. Customers can start using it today to host the databases for their dev and QA environments, which will help suss out any issues with it before GA.
I can't wait! If you read the entire schedule it was pretty clear, but the following is about as clear as mud:
"Learn about what Google Cloud offers today and hear from Google leaders Diane Greene, Sundar Pichai, and Eric Schmidt about Google Cloud's vision for the future. Hear how big customers and partners are embracing the cloud."
Spoiler Alert: Day 1 is apparently just enterprise partner/customer announcements, and some self-congratulatory words, except for the single new product announcement: Cloud Video Intelligence API. Apparently all of the product announcements are tomorrow, which was announced at the end of this mostly poorly presented keynote.
They definitely complement each other, but HTTP2 helps out with the request/response cycle and reduces latency in general, which reduces the threshold between rendering on the client and backend.
Sure it's possible to ignore, via Turbolinks or similar. I have witnessed the shift back to the backend over the past year or two, including in the Phoenix community. With HTTP2 inbound and microsecond response times via Phoenix, the case for making your new app a SPA is harder to make, if you take an honest look at things. There are some benefits to be had with React Native, or Angular2 Dart + Flutter, but mobile apps are very difficult to justify, given the increased friction they cause to new users.
A Spanner node is not related to a VM instance, they are entirely different concepts. A Spanner node refers to a collection of regional (and eventually global) compute and storage resources, while a VM instance is just a virtual machine running on a single physical host.