robbles

I was wondering how they'd handle the 2.5 seconds without landing, given that the engine plume is going to heat it back up again. Are the particles being released from a much higher point than the pictures suggest? Otherwise you'd think it would drop into the still molten pad after less than a second, right?

Probably just my lack of understanding of bpftrace, but can it easily be integrated into other tools instead of used interactively / in a script? It seems like this series of posts is about how they built a monitoring agent, so maybe the existing bpftrace scripts aren't practical?

Do you think there's an alternate approach to showing data that would be effective? I can definitely buy the idea that showing a bunch of fancy charts doesn't help most medical professionals, but I don't like the idea of giving up on trying to surface more data. Or is that what you're referring to as "non-dashboard approaches"?

Is there a similar way of detecting the web cam in use on macOS?

I think the term you're looking for might be "postdoc" (postdoctoral researcher)? I've seen "recent PhD" a few times as well, seems pretty clear.

I remember reading that Mars doesn't have a magnetic field like Earth's to protect it from solar wind, therefore the atmosphere mostly gets swept away. Is that not the more difficult problem here? This debate seems to center on generating enough CO2, but that seems a bit irrelevant if it would just blow away. How would you even go about fixing the magnetic field of a planet?

How do you swap out the container in docker-compose?

Do you just have a service defined for each, and only start one of them?

For people wondering what this is useful for: I've been using this as a protocol for a project connecting a Raspberry Pi to a microcontroller project. Currently I'm prototyping using the serial transport, but at some point I will likely switch to using I2C to accommodate a more minimal interface between the two and allow for more devices to be connected to the RPi. This makes it so that I can swap out out with minimal changes to the code on both sides and keep a standard protocol in place. Also the libraries are pretty easily to use, so it's a little nicer to work with than rolling my own serial framing protocol.

What's the advantage of doing this over just making an experiment branch? A branch would be easier to find than a reverted commit somewhere in the mainline branch.

Does running an idle k3s cluster really require adding a heatsink to the rpi?

I would have thought this would generate very little load, and a major temp increase might indicate a bug in k3s?

Is there a bunch of cpu-intensive work an idle cluster needs to do?

My impression after following him on there for a while: he still uses, and sees the platform as if it's the original version of Twitter from ~2006. Most of his tweets are written in a way that sound like a person writing in a public diary, not someone expecting to have a conversation.

They're batching the requests into larger files on S3. The 1M refers to the number of HTTP requests hitting their server.

Synergy (https://symless.com/synergy) does exactly this, cross platform, and really effectively.

You don't need to write your own using a Logitech driver - it works with any standard keyboard / mouse.

  KGIII 1 day ago
  I'm retired but I am a scientist. I am technically a mathematician, but I still apply the method and use the philosophy of science in many areas of my life.

I'm not sure he actually employs anyone...

I'm not sure leaving out sort and dist keys is actually being fair to Redshift here.

I get the argument that you're avoiding any "special tuning", but these are basic features that the docs and most guides will tell you are not really optional. In my mind it's more like leaving out the primary key declaration on a table in Postgres or MySQL.

That's true regardless of the teaching technique though, isn't it? Having someone lecture at you because they assume your knowledge is lacking is the part that makes it condescending, IMO.

Does that mean you can mass-produce queens by separating them from the hive and continuing to feed them the jelly?

I noticed there's a go:noescape compiler directive that seems to provide an escape hatch for a lot of this unexpected compiler behaviour:

https://golang.org/cmd/compile/#hdr-Compiler_Directives

Does that actually work?

Would you mind posting a link to the specific case you use?

Why wouldn't you start with the cache?

Isn't the consistent database only useful if you require it to be used, and don't fall back to a less consistent alternative?

it works exactly like the real PHP interpreter:

   <?php echo "hello"; ?>

I'm not a machine learning expert, but isn't this an easily solved problem?

Similar to TF/IDF, where you mitigate common words by dividing by their overall frequency, you should be able to divide the weight of any particular "like" by the frequency of likes between the two people. That way a genuine expression of interest by an acquaintance is weighted far higher than a relative or close friend that reflexively likes everything you post.

The most important reason I continue to use Pinboard is that it's the only service I'm confident won't be acquired and shut down within a week with no warning or no data export. (based on Maciej and his talks, blog posts, etc.)

The rest of the services mentioned in this thread? Who knows?

That looks like what I'm looking for, thanks! Is there documentation of the format of those JSON logs? CSV would probably be a useful addition just for ease of ingestion into analysis tools and databases.

Once I get a chance to test this out, I'll definitely report any issues through GH.

This looks incredible for work I was previously using Tsung / Gatling for.

One request: please allow the output of either a) a CSV log of every request and it's timing or b) a configurable histogram of request timing, not just some percentiles and averages. That info is pretty much required for doing any more advanced analysis beyond "the service is fast enough". https://github.com/tsenart/vegeta does this really well (but doesn't have the scripting abilities of this tool).

What does "a lot more versatility" mean? Just wondering what the advantages are.

Or do you just mean that R Notebooks are specifically better than the R support in Jupyter?

Federated comments/annotations sound really cool from a developer's point of view, but also seem like a nightmare for publishers. If you cede administrative control over the comments on your site, how do you control trolls/attacks/spam/etc.?

Services like hypothes.is can do some filtering automatically, but this is missing the level above that - editorial privileges on comments on your own domain.

It's incredible that people put up with how buggy these adblocker extensions are. Seriously, blocking an arbitrary URL with "ads" in the path?

Can't they just stick to blocking domain regexes instead of actually breaking the web?

> Rebases automatically set the committer of the rebased commits to the current user, while keeping authorship information intact

I don't understand this. The commits are rewritten - do they overwrite the author to the current user, or don't they? Or is there a distinction between "author" and "committer" I'm not aware of? Which one does blame use?