The robot arm is expensive because it needs precision hardware (backlash free bearings/gearing).

Your idea also requires precision hardware to move the sphere.

Actually besides 3 step motors ( for rotating in three axis ), rubber wheels to hold the sphere and a sensor to measure the water level, I don't think you need more. What I don't know is how much water you need, probably this can also be computed.

It's a better idea than dipping with a robot arm. And also faster.

Thanks for writing this, the post is super helpful! I didn't see anything about the circuit design/iteration process. Would be great to hear what software was used to design the circuit (if any) and how that eventually translates to mass production.

The circuit is actually really simple in our case. It is just a voltage converter and then an adapter for the lightning connector.

Getting the custom lightning connector and chip was more of an ordeal though! I'll see what I can dredge up on that process.

Cool! I had an idea for something like this but instead of having each build be it's own lambda event, I wanted to make each individual test it's own lambda event. The goal is to have the build time for a complex project boil down to the time it takes to setup + run the longest test.

Have you written any code to that effect? I've been trying to think through how booting up dependencies might work (for things like integration tests).

I have aspirations for QA (https://github.com/ajbouh/qa) to learn this trick, but it needs some lambda-specific smarts before it gets there.

We're doing something similar, but using mesos. We bundle tests up, so we don't have to eat the setup costs for every test, and try tracking test pollution by splitting bundles when they fail & running them separately, again.

That is more or less the same reason I started the eremetic framework. We were tired of dealing with the trouble of using a lot of VMs as jenkins-slaves, and long test suite runtimes.

https://github.com/klarna/eremetic

where do you store build caches? npm/gems ect?

Dependencies? On the host; they're ephemeral but they'll run multiple builds between coming into existence and disappearing.

but first build always take a hit making the build times unpredictable making build time regressions hard to track.

I love that idea. Map -> Reduce of unit tests.

Yes, it would be helpful. Of course, other forms of treatment would still be needed.

I was thinking about this today. Neuroprosthetics with feedback is the most exciting. The type where people can actually sense touch on the prosthetic limb...but it's probably still in the "research" phase. Any startup trying to do this may need to work with a doctor. You may also need to do surgery to access the nerves...or maybe there's a better way..

I'd love to work on something like this too!

Exactly, neuriprosthetics is one, we also have exoskeleton, soft bionics too.. I think it's a pretty wide and active field to work in.

This is an interesting thought. The point of logging in would be to save user state, but maybe users can opt-out of that for certain apps... hmm

There are better ways.

I was debating including that option :P

I've just never actually seen anyone else do it.For some reason, it feels 100x more complicated than checking my SMS app for an SMS code when in reality its not that different.

Would you say that's a small percent of your user base? Most of my friends hate the idea of needing to login via Facebook, but it is truly the simplest for them - and I'm not sure if my friends are just disproportionately biased. I'm also not sure if I want to depend on a third party.

This is great. I've wanted to start a project in Rust but I'm hesitant since I haven't found any profiling tools akin to VisualVM. I'd feel a bit blind writing multi-threaded code where I can't see what's going on. What do people use to sanity check this sort of thing?

One nice aspect is that Rust gives you many kinds of threading errors at compile time, so that helps. :)

Any profiling tool that works for C or C++ should work just fine for Rust. For example, people often use perf for performance work.

Thanks for answering questions! I'd be curious to know where you got your (presumably massive) data from to train a NN to spit out what seems to be binding affinity between two candidates (drug and target). Do you guys use a NN for each target? I know you may not be able to answer these questions :)

I hope your team succeeds, keep up the hard work!

Thank you for the kind wishes!

Over the past few years, there's been a huge increase in the amount of data available for this kind of machine learning. We curate our data from a number of private and public sources. For example, as part of my doctoral work (http://en.wikipedia.org/wiki/SCRIPDB), I learned how to parse chemical information out of U.S. Patent data, which is public domain. That said, if you're interested in working on something like this and need a quick million data points, I'd point you to PubChem as a first step: https://pubchem.ncbi.nlm.nih.gov/