Most people aren't in a quiet environment when they listen to music these days. Compression helps significantly with this.

What would be neat would be to have a compression metadata 'guide' that would allow a compressor on-device to perform the compression, rather than baked into the audio track.

This would allow the user to tune 'severity' of compression. In a car / fancy headphones, you could sample the ambient noise level and adjust accordingly.

It might be better to think of ourselves as individual fish in a school of fishes, and Oracle is the boat with a mile long dragnet. It doesn't care about the individual fish; it's not worth it's time to consider us individually. It's thinking in terms of tonnage.

It's still malware though. Unlike some backdoor that you could plausibly claim was just a simple memory leak, the instructions for this one are literally written in plain english. Wouldn't be very difficult to show intent to a jury with that one...

I don't think I've ever seen a manual that expected me to use DeMorgan's Theorem as part of a test procedure... :)

"...And what is the 'Self', if not a pattern of data? What is consciousness, if not an illusion of intelligence residing within meat?" — Prime Function Aki Zeta-5, "The Fallacies of Self-Awareness"

For such low frequency stuff, it feels way safer to just buy a cheap <$500 scope for this kind of work. Using a $50k scope when it's not needed just seems needlessly risky.

Also, float the DUT, not the scope... Sometimes that's not possible, and the temptation is there, but it's really not worth it. Just buy the right gear like a diff probe. You can get one for a few hundred bucks if you don't mind going downmarket.

You can also use two probes and do CH2 - CH1. (Disconnect the GND clips!)

Looking at: https://journals.plos.org/plosone/article/figure?id=10.1371/...

I'm not sure I believe the graphs.

For example, here's another frequency response chart of some stethoscopes: https://www.researchgate.net/figure/a-Frequency-response-of-...

How is it that professional stethoscopes can be that different, and yet this 3D printed one can match a gold-standard one almost exactly?

From what I can tell there's no audio engineering / modelling that's been done here -- It's just some crude openSCAD tubes. And it's not even optimized for 3D printing; a 3D printed tube with a circular cross-section is going to have bridging issues at the top which will result in internal roughness. I have to imagine that results in attenuation. (A better internal shape for a tube is something that looks like "ô". The ^ will print much better)

The type of plastic used and its frequency response, the thickness / stiffness of the silicone tubing, the height / width of the bell... There are so many variables that I think would make significant differences in performance. The fact that they see basically no difference is highly suspect.

This feels like one of those "3D-print everything" fads that was popular a few years ago. Yes, you can make a 3D-printed adjustable wrench, but even the most miserable dollar-tree metal version will beat it in every possible metric.

Likewise, on Alibaba, if you order 200 pieces, I'm seeing metal ones as low as $1.22/pc. I don't believe that this 3D printed one will even be as good as those.

It seems like joules would make more sense, right?

Enough that the prompt is different at a token-level, but not enough that the meaning changes.

It would be very difficult for them to catch that, especially if the prompts were not made public.

Run the variations enough times per day, and you'd get some statistical significance.

The guess the fuzzy part is judging the output.

I'm in the bay area, did a roof mount system. ~9.5kW with Enphase microinverters.

I think it cost be ~15k all in. The usual installer price is normally around $2.5-$3/w (so about $25k - $30k).

I got someone to do the plans (because I was under the gun to get on NEM2), but that was $300 well spent.

Did it all myself -- mounting, running conduit / wiring etc. Wasn't too bad. Probably about 3-4 Saturdays of work.

Here's my install log: https://www.reddit.com/r/diySolar/comments/1c6jfjv/finally_d...

Feel free to create a "how does it compare to Claude 3.5 Sonnet" benchmark. If people find it useful, it will be run against new LLMs to generate additional points of comparison.

I will also say; it's really easy to just skim past comments. I suspect your ROI time-wise in creating this account to complain will never be recouped compared with just skimming past pelican comment chains.

...

"This isn’t a calculation error – it’s revision to better estimate how these payments are made," said H.D. Palmer, a spokesman for Newsom's Department of Finance. "We told legislative leaders and the LAO back in February that we would update how we estimate these payments once this issue was identified. We’ve already made that adjustment, and it will be reflected in the revised budget next month."

Can someone please explain to me how double-counting isn't a calculation error? Best attempt wins.

When a political organization has no qualms about putting out a statement like that, it's a sign that they do not respect you.

One suggestion: The main splash screen image is nearly 8MB big. It takes a noticeable time to download on my connection. I'm not sure what bandwidth costs these days, but seems like that could be something to optimize.

But I bet you'd have a significantly easier time converting a child rather than a 30/40/50-yr old to a religion.

My point is that LLMs are suggestible, perhaps more so than the average adult, but less so than I child I suspect. I don't think suggestibility really solves the problem of whether something has AGI or not. To me, on the contrary, it seems like to be intelligent and adaptable you need to be able to modify your world model. How easily you are fooled is a function of how mature / data-rich your existing world model is.

Tell a 5-yr old about Santa, and they will believe it sincerely. Do the same with a 30-year old immigrant who has never heard of Santa, and I suspect you'll have a harder time.

That's not because the 5-year old is dumber, but just because their life-experience ("training data") is much more limited.

Even so, trying to convince a modern LLM of something ridiculous is getting harder. I invite you to try telling ChatGPT or Gemini that the president died a week ago and was replaced by a body-double facsimile until January 2027, so that Vance can have a full term. I suspect you'll have significant difficulty.

You could make the argument it's closer to the blocks of a CPU compared with a brain, and it's no different to copy-pasting some IP block for eg, HW JPEG decoding. But I feel like the difference here is we're 'discovering' these blocks / organs. They weren't designed, they were evolved.

Maybe it's plugging your laptop into an external projector, or getting to sleep and wake correctly without the WiFi driver segfaulting, or maybe it's trying to get HDR working, or audio routing or...

Sure, there may be shortcomings, but they're well understood. The closer you get to the cutting edge, the less characterization data you get to rely on. You need to be able to trust & understand your measurement tool for the results to be meaningful.