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The article's point is that fewer managers are required as organizations become more automated, not that managers are being directly automated. However, I'm not sure I agree with the study author's statement "Because managers, by definition, supervise other human beings, so we really cannot replace their functions until the singularity occurs with artificial general intelligence."

This came up on HN a while ago: https://apenwarr.ca/log/20190926 . The thesis was: "To paraphrase the book, the job of an executive is: to define and enforce culture and values for their whole organization, and to ratify good decisions. That's all. Not to decide. Not to break ties. Not to set strategy. Not to be the expert on every, or any topic. Just to sit in the room while the right people make good decisions in alignment with their values. And if they do, to endorse it. And if they don't, to send them back to try again. There's even an algorithm for this." All of that sounds automatable to me using current or near-future technology.

Managers, especially middle managers, also do many other things; but they universally end up spending a whole lot of time in meetings. I'm not a manager, but my own role in many meetings feels automatable. In a handful of meetings I have to be there because I have detailed knowledge about the subject to share. In the other meetings I think it would honestly be fine for an AI that had learned to emulate my writing and speech to represent me in the conversation and write a summary for me afterward.

I'm not arguing that managers _will_ be automated anytime soon, just that AI probably _could_ automate some of the things that take up a big chunk of managers' time.

It definitely did work for me. I've always exercised and eaten healthy food but haven't found any other way to stay at a comfortable weight all of the time.

Initially I didn't eat until noon for a few months. I went from 165 pounds to 135 and lost some strength. (I'm male and 5'6" tall). When I switched to eating at 10:30 or 11:00, I went back up to 145 and am about as strong as I was at 165. I've now stayed within about 4 pounds of 145 for a whole year, which is unprecedented for me. I'm mostly vegan but make a point of getting 20 grams of protein per meal and of eating soon after exercising. I don't have a cutoff time at night, I eat late if I'm hungry.

I sent a similar text to a medically vulnerable friend on Jan 25 saying I thought it was "scary, but not the scariest thing in the world right now", despite having spent some time working with an epidemiology research group. In hindsight, I knew enough to take the risk much more seriously.

This article: https://virologydownunder.com/past-time-to-tell-the-public-i..., plus the rising mortality numbers, spurred me to start warning the medically vulnerable people in my life on Feb 23. I am very grateful to the authors for helping me do the right thing.

At this point, it seems to me that our experts are still letting us down in two important ways:

1. They aren't rebutting this implicit notion that any mortality risk below 1% can be rounded down to zero. As a consequence, the idea that it might be a good idea to let younger, healthy people just go out and get the virus and get immune seems to still have currency, and this is really dangerous. We can't open things back up until we have a credible plan for driving the infection rate toward zero. Leaving aside the risk of life-changing injury, a mortality risk of eg 0.5% applied to eg half of young adults would still be by far the most dangerous thing that happens to most of them this year, and a huge personal tragedy for many of us. Do the math and work out how many people you know would die.

2. Simple, inexpensive measures like widespread masking, handwashing, gloves and eye protection will clearly be important components of any credible plan for driving the infection rate toward zero, unless we get an early vaccine. The experts should be hammering the point that we all need to be fastidious about those things whenever we open back up again.

Notes (http://github.com/pimterry/notes) on Keybase's kbfs. I really like having my notes be plain text files in an e2e encrypted network folder. The main downside is that there's no great way to create notes from keybase's Android app.

I've started using kbfs for personal notes and encrypted git for financial planning code.

We're also trying Keybase out as a family chat channel. I really like the CLI interface and the integration with kbfs, and of course the e2e encryption. We're probably going to stick with Slack for now, though, mainly because it runs on Chromebooks.

It's definitely possible today, I just wish it were closer to seamless. For example, it seems like it would be possible to write a utility that takes a Go source file and emits a .cma, and maybe an .mli so you can see what's in there.

I wish OCaml could just use the libraries of Go and Rust. They can both compile to object files, and their type systems can be mostly modelled in OCaml's.

We definitely don't want to lock you in, just to round off the rough edges of the "on your own" experience. You can create a project from GitHub and push/pull to GitHub from Sense, and our distributed computing setup was chosen to be low-level enough to support many of the existing distributed computing tools like doRedis, but still way easier than provisioning and plumbing servers.

We know that there's room for improvement on some workflows, in particular Git interop, but we have our sights on a platform that plays well with as many others as possible. Please ping us with any other thoughts you may have!

Thanks for the feedback. We're always thinking about how to improve the workflow and will take your comments into account when we next revise. Please ping us on intercom with any other thoughts!

At the moment, not really. In your scenario, you could have a Python dashboard launch a Redshift dashboard with startup code that runs the initial query, then clean the result, then launch an R dashboard and pass the clean data to it either over the shared filesystem or a messaging system such as 0MQ or Redis, then save the results to S3 for consumption by Redshift.

You're probably looking for something smoother, though. We definitely intend to have a good solution for workflows like you describe in the future.

Not at the moment. Right now, the biggest single dashboard is 60GB. You can launch as many dashboards as your plan allows if your application can be distributed, but I'm guessing that isn't the case for you.

Thanks.

I forgot to mention storage. We're planning on about 1GB of disk per project. Because we live on AWS, we get quick access to all of Amazon's storage services as well.

We're planning to charge per core for usage. Each core will be a true physical core, with 5.5 ECU. The container will get 3.75GB of RAM and a slice of the host's bandwidth per core. We'll also have very inexpensive micro tier, and eventually some kind of long-lived services tier, as Tristan mentioned in another comment.

Glad you like it. The IPython engine isn't open source at the moment, but that may change in the future. Out of curiosity, if it were open source, what might you use it for?

Thanks! Yes, we do, and you can install packages yourself and/or let us know if anything is missing.