emailgregn

Select count(*) takes a surprisingly long time, even on an indexed table. Apparently thus is because of the MVCC model and row count estimates are available to mitigate.

Are the newer ships more environmentally friendly? I'd assume only slightly because they're still burning bunker oil, only slightly more efficiently. Which I find perverse given the attention focused on car pollution.

Cool. It sounds dumb but just shaping the inputs was a problem for me. I wanted an LSTM/RNN but epochs, batches and recurring sequences didn't click together for me. I also had trouble plotting the learning curves.

Congratulations on hitting 1.0, Keras really looks like the way forward for python ML. I tried to use Keras after doing Andrew Ng's Coursera course but found that I just couldn't connect the dots from what I'd learned on the course to the concepts assumed familiar by the keras documentation though.

wasn't that the idea with OLPC Sugar [http://wiki.laptop.org/go/Sugar]?

The whole desktop and apps in python and hackable.

It's interesting to hear that having recently experienced the wholehearted enforcement of KYC rules and general efforts avoid/shed that reputation.

This is worth consideration too. Getting a bank account can be difficult.

How long before these vacuous AI assistants will be useful in the real world?

* "Siri, check if there are better deals than renewing my car insurance with current provider."

* "Cortana, book my brother a flight from Milan to Toulouse on Monday, and don't forget to check budget airlines that aren't on expedia."

* "Alexa, change my phone contract to the new daysaver tariff."

Telling me it's raining outside or being able to make a restaurant booking in a handful of places in NYC is just not interesting^W AI.

Context and identity seem to be major missing ingredients.

The LSTM would be trained against an existing high quality Rust code base and it's IR; so I wouldn't expect a bunch of unsafe literal translations.

Whether the C side IR has enough debug metadata or could be annotated automatically would be the make or break.

I was just recently wondering if an LSTM neural net could be trained as a decent decompiler from LLVM IR to Rust source. Feed that with Clang output of an established OS and coreutils(i was thinking minix3 but maybe seL4) and get a working if not necessarily idiomatic Rust OS. Refactor at leisure.

That code is so -erm- pretty. And by popular accounts, Elm is a pleasure to develop with. I hope it catches on.

I'm genuinely interested to know if the altruistic/community driven ethos of these efforts ever last? Once the NGO leaves town and the local federalè or whoever notices a nice little income stream?

Yup, that's the trade-off.

Install each of the pip/bundler requirements with a separate dockerfile RUN command. Each gets cached into its own container filesystem layer that way and only new requirements are pulled. Use your favourite templating tool to generate the dockerfile with multiple run commands.

I wrote djtempl ( https://github.com/emailgregn/djtempl ) for my purposes.

use perl

There's no simple "this workbook" connection that I'm aware of. So you have to use external connections and Access flavoured SQL to a named file and it all becomes brittle & ugly.

I'm banging my head against Excel, wishing for SQL right now! But I could never go to my boss and ask for a purchase order for something called ThingieQuery. Give it a more bland gray name and make a massively expensive corporate site license available, and I think you're onto a winner.