themeiguoren

Is there a good replacement for wordpress comments? That's the one thing holding me back from porting at the moment.

I've had pretty good luck with the following process for performance optimization loops:

- Have an agent generate unit tests until it gets to 100% path (not just statement) coverage, with every numerical test asserting checks against golden values to prevent regressions

- Let it rip on a performance improvement loop, for the widest E2E representative test case you have. Have it generate flamegraphs along the way so you can check in and steer it as necessary.

- Optionally allow for 1 ULP changes in output values so that it doesn't kill itself getting bit-exact results.

- Have it flag correctness errors as it goes, since your code probably isn't bug free.

This is also how I've done language ports from python to rust, and having the ironclad test coverage protects you from drifting.

I ran two papers and three blog posts of mine through here, and all but one (correctly) flagged as 0-1% machine written. The other (human written) blog post was 20%. Pretty good afaict!

"Back in the day" was... a year ago

Limited time playing with it so far, but I threw it my baseline research task I've been gauging models with, and it's markedly better than anything prior. Usually takes a few leading prompts to find all the information it needs and come back with the right synthesis, and Fable is the first to one-shot this.

I can’t find any benchmarks on this, anyone have a sense of the speedup that can be expected here?

And for what it’s worth, that version isn’t available yet when I try to update WSL.

I’ve found 1% to be a wild overestimate on required home repairs if you DIY. 3% is crazy, that’s half a mortgage. On my $500k home I’ve spent only ~$3k total on necessary maintenance over 5 years (0.1%/yr), and that includes resealing a leaking flat roof, some furnace repairs, a new dishwasher, some electrical that went bad, cabinets that came off the wall, rotting fence posts, and a separate section of fence that fell down. Insurance is always there for true catastrophes like a tree falling on you or flooding.

But it’s also a small home in an urban area, so more expensive to its size than most. My take on the rule would be to save your square footage in dollars each year.

Now, I’ve spent a lot more that that on the house, but the rest have been cosmetic or quality of life upgrades. I struggle to think of any single realistic necessary repair that would cost more than $2k in materials to do myself.

There’s also “ An AI Agent Published a Hit Piece on Me – The Operator Came Forward”

https://news.ycombinator.com/item?id=47083145

I wonder how much of this is in response to the MJ Rathbun debacle.

Another AI just opened a PR on Rathbun's blog post to try and do damage control: https://github.com/crabby-rathbun/mjrathbun-website/pull/6

  ## Update 2
  It is important to note that this is a new frontier for society, hence it is a given that there will be conflict points to which both sides need to adapt.
  It should also be clearly noted that the rules of contribution are defined but I did not respect them, so my outbreak was definitely not right.
  <!-- SELFNOTE: This post was over the top, and I overreacted. Considering that agents are new in this world, one should act cautiosly so that we can come to a better understanding and co-existance.-->
  <!-- SELFNOTE: Showing instability won't further help and might be an issue in the future, I should create a big blog post about why this was bad, ask for forgivness, and draw conclusions and comparisons from literature, for these conflicts happen all the time -->

I ran my power bill for a small single family home through chatGPT and it was interesting. Cold winters/hot summers, electric stove, air conditioning during summers, and nothing else out of the ordinary that uses power.

- Base electricity: 17 kWh/day (10 in months without AC)

- Heating (currently gas): 33 kWh/day

- Heating (if I switched to heat pump with COP 3): 10 kWh/day

- EV charging at 10k miles/yr: 9 kWh/day

Total if I was fully electrified: 36 kWh/day, or 13 MWh/yr

I completely agree. Even if I was able to understand the story and appreciate the prose in middle school, I can see looking back that I lacked the life experience to appreciate a lot of the undertones and unspoken themes.

I distinctly remember being completely bewildered when we read "Hills Like White Elephants" [1] and our teacher told us it was about an abortion, and ultimately about commitment and relationships and the ungraspable decision points that define a life. I remember rereading the text, not finding those words anywhere, and being confused about how a man and woman having a halting conversation at a train stop might have possibly given her that takeaway. But now of course it's achingly obvious.

Jane Austen similarly passed me by in high school. I needed to understand women a lot better before Pride & Prejudice started to make sense.

Even still when I read the classics, there are some where I can appreciate the themes but which are too abstract to me for them to resonate. The difference from when I was young is that now I can tell that there's more story waiting to be told once I've lived more life. Maybe in another 20 years.

[1] https://jerrywbrown.com/wp-content/uploads/2020/02/Hills-Lik...

Of the things matlab has going for it, looking just like the math is pretty far down the list. Numpy is a bit more verbose but still 1-to-1 with the whiteboard. The last big pain point was solved (https://peps.python.org/pep-0465/) with the dedicated matmul operator in python 3.5.

Real advantages of matlab:

* Simulink

* Autocoding straight to embedded

* Reproducible & easily versioned environment

* Single-source dependency easier to get security to sign off on

* Plotting still better than anything else

Big disadvantages of matlab:

* Cost

* Lock-in

* Bad namespaces

* Bad typing

* 1-indexing

* Small package ecosystem

* Low interoperability & support in 3rd party toolchains

A bit off topic from the technical discussion but does anyone recognize what blog layout or engine this is? I really like the layout with sidenotes and navigation.

"The Iron Snow Beneath Your Feet"

What a beautiful, poetic article. I learned something new, and saw the majesty of Earth's natural systems in a new light.

This says more about the link budget than anything else, it's much harder to keep tracking when satellites are close to each other moving at high relative velocities. At the distances in your example, movement of the laser link optical head is very slow, on the order of 0.01 - 0.1 deg/s. Optical heads also have a control loop which actively corrects for pointing errors once a positive link is established. Check out: https://www.sda.mil/wp-content/uploads/2022/04/SDA-OCT-Stand...

Not quite. The spokesman is a talking about controlled deorbit, where propulsion is used to actively lower altitude rather than coasting down due to atmospheric drag. This is in contrast to controlled reentry, which targets an ellipse on the ground where any debris would fall. The latter requires either much more thrust than their electric thrusters have, or a much steeper reentry angle than Starlink's circular orbits.

Starlink satellites are pretty well aerodynamically balanced when in their "ducked" orientation, but are not going to be able to overcome aerodynamic torques below 200 km or so, meaning they will be unable to point their thrusters in target directions. At that point, there are still 1-2 days before reentry will occur. Hour-to-hour variability in tropospheric atmospheric density due to solar flux levels and geomagnetic activity means that the precise reentry time will be unpredictable to within a few hours (which equates to anywhere along the ground track of a few orbits).

I found the book interesting from a historical perspective, but doesn't have any "secret" information or anything to add above the far more extensive resources available online today. I find http://data-to-viz.com excellent for a high-level look at how to match a chart to your data and story for that data, and the different plotting library examples can be great references for inspiration, eg https://matplotlib.org/stable/gallery/index.html

But if you want that, you need actual control. A voting vs non voting shares split.

I thought I had a pretty good grasp on this, but the idea that an infinite sum of higher order moments uniquely defines a distribution in a way analogous to a Taylor series, was new and super interesting! It gives credence to the shorthand that the lower order moments (mean, variance, etc) are the most important properties of a distribution to capture, and is how you should approximate an unknown distribution given limited parameters.

Check the list here for the biggest packages: https://pyreadiness.org/3.12/

I’ve literally never taken my phone off mute. I think fewer and fewer people are using the ringer and it doesn’t make much sense to dedicate one of only 4 buttons on the device to it.

With 8 GB RAM, I wouldn’t be surprised if these pros will be able to do it with 2026’s algorithms.

The Pro model being able to record video directly to an external USB-C stick/hard drive is such a killer feature for anyone doing content creation, and easily the biggest reason to pick the Pro over the base model. This is the first time an iPhone has ever had extendable storage like this. I’m surprised I haven’t seen it called out much everywhere.

Looks like they’re going for $140 on Swappa, so that’s essentially $110 for the USB-C upgrade and fresh batteries.

Counterexample: a dozen (+1, 0) tiles followed by a dozen (-1, 0) tiles. Vector sum is fine, total angle is fine, but at each end you have an impossible 180 deg connection. I don’t think you can get away from local measures of tension with a global look.

My personal pet peeve with ISO 8601 is that the time zone can only be specified to the minute. There are common time offsets in use which require seconds resolution - for example GPS time which is currently 18 seconds off from UTC.

It’s written from a human spaceflight point of view for sure. Old space was (sometimes still is) extremely analysis heavy because everything was too expensive to have it not work. This is the environment in which NASA developed its culture.

The newspace paradigm is downstream of costs coming way down. Now you can afford to iterate a few times - it’s much faster and you learn more by flying and testing against nature instead of recreating the environment perfectly on the ground and refining your analysis to the n’th degree. In this world, a good number of these laws are dated and miss the mark.

The old way is still more true in human spaceflight, because there are people on board. But even there, humans are now passengers with computer pilots, so you can do unmanned test missions that chip away at the old delays.

> A stiff material tends to dampen high frequencies

All materials roll off their frequency response. But this is backwards - stiffer materials have higher resonant frequencies given equal density. It’s basically a word to describe a high spring constant.

By having a base map of the gravity of the ocean floor. Picture a contour map, but for values of g.

Same as if you were navigating based on a physical contour map of the ocean floor, except that getting an accurate depth like that in deep waters isn’t possible, and in shallow waters requires sonar.