> They use a high mghz signal to measure the tip temperature using impedance measurements IIRC. Then they control the tip temperature using a feedback control loop.
That's not how Metcal fixed temp induction soldering irons work. They don't have a control loop, which is what makes them so much better than other soldering irons.
They exploit the Curie temperature [1] of some alloys, in which the metal loses its inductive properties when it hits a certain temperature. A Metcal power supply pumps a simple 13.56 Mhz signal into the tip which heats it up and when it reaches its Curie temperature, it just stops heating. Since the signal is constant, whenever the temperature of the tip drops it just heats back up without any PID loop. The downside is that you have to switch tips (alloys) with a pair of pliers to change temperatures, but the upside is that there is no control loop delay.
It's also why their station are so reliable. There's basically no "modern" electronics in them and the worst you have to do to fix them is replace an electrolytic capacitor. I've got a power supply manufactured in the late 90s that's still as good as new and like you said, going back to a Hakko or any other soldering iron is downright painful.
(Side note to anyone who cares: when the patents expired, a couple of Metcal engineers left to form Thermaltronics, which sells cheaper stations and Metcal-compatible tips)
Thanks for filling in how the metcal's work! The 13.56 mghz signal made me figure an impedance measurement. Though as you say that explains why metcals are so bulletproof.
Side note: I found Thermaltronics stations to not be much cheaper than Metcal ones. At least for the lower end stations. Gotta love capitalism.
> Yet, it's all the most likely token and my brain hurts trying to understand how that can be.
You and everyone else. That's the great mystery of transformer architectures as applied to language.
To be clear though, they're only good at schematic capture, which is very much a textual representation. Most of the data basically boils down to netlists, which are a text based format mapping connections between abstract pins that only later map to physical copper. The actual schematic portion is for human consumption and LLMs don't need to produce those to be useful.
Where LLMs completely break down is the next step, PCB routing. That's an NP-complete research problem that's been ongoing for decades without much progress. I've had some fun playing with using LLMs to better specify DRC rules in Altium so that the "classical" algorithms are more usable, but at the end of the day their geometric intuition is nonexistent.
They actually can route just fine. I used Sol to design and route mine from start to finish. Sent it to PCBWay and had a working prototype in a few weeks.
It was a pretty simple rp2040 based thing, similar to Adadfruits USB feather.I just gave it kicad and it wrote python to route it. The board was probably larger than it had to be, and two of the silkscreens were swapped, but it worked on the first go.
FWIW - Computer vision is also NP complete, but we do that all the time now.
I'd love to see that chat log, and the final board. To be fair I've only been testing on nontrivial PCBs with 6+ layers and I haven't had the luck you have.
> FWIW - Computer vision is also NP complete, but we do that all the time now.
I have no idea what you mean by this. What's your definition of NP complete?
NP-complete means that it's easy to test if we're right, but because of that complexity we can't always find a valid solution to test within a predictable period of time. Both circuit board routing and computer vision are variations on the same fundamental problems. Once we solve we, we solve the other.
However, when I was growing up most serious computer scientists believed that CV (computer vision) was a 'hard' problem that would never be 'solved'. After all, to do it right you must first at least solve subgraph isomorphism and a bunch of other things that are also NP-complete.
What they missed was that we don't actually NEED to solve it in a fixed amount of time. Even for things like driving a car the stochastic heuristic based answer is 'good enough'. e.g. - Cars driven by computers don't have to be perfect, they just have to kill other drivers less often than humans do.
We can find AN answer in polynomial time, and that's good enough. It might not be the ideal answer, but that doesn't matter in the real world.
People use NP complete as shorthand for 'impossible to do with a computer', but we now 'solve' (bypass?) NP complete problems regularly and at scale by just ignoring the fact that our answers aren't perfect.
> I'd love to see that chat log, and the final board. To be fair I've only been testing on nontrivial PCBs with 6+ layers and I haven't had the luck you have.
I wish I could share it, but it's for a commercial project that hasn't been released yet and I'm not sure if it will be open source, but a few folks have asked. I might do a blog post on it this weekend with as much detail as I can safely post.
It's only 3 layers, and less that 30 components, but the fact remains that I didn't design any of it by hand and it worked on the first go.
In your opinion, do you think ai can make eutorack modules by now? This is what I am waiting for: explain an idea to an ai, and sending the files to jlpcb to receive a complete working module (minus some THC soldering)
I'm sure that the best models can glue some basic synthesizer functions together, but I wouldn't waste a minute on anything less than Fable/Astra-class models for that kind of application, and I wouldn't expect the result to work the first time. It could get expensive.
Here's a question - are there software simulators for things like Eurorack modules? That would make the question somewhat more interesting, since you wouldn't have to build the circuit (or pay someone else to assemble it) to hear how it sounds. It strikes me that SPICE-like algorithms should be fast enough to do this kind of thing in real time now.
> at the end of the day their geometric intuition is nonexistent
This isn't true anymore.
I use LLMs for 3D CAD using OpenSCAD and they understand geometry fine. I've had more success with Sol than with Opus (Opus 5 is around 10 times slower because it does too much verification) though. I haven't tried Astra or Fable for it.
That is indeed impressive, but at least the excerpt given from the layout seems very easy to route, due to high regularity and an ample routing channel.
Even so, there remained some "dozens" of unrouted traces, which are likely to be much more difficult to route, after the easy traces have already occupied the space.
Many decades ago, I have written a PCB routing program, which would have routed the example shown at that link at least as well, while using many orders of magnitude less resources, i.e. while running on a single-core 233 MHz Pentium MMX.
Obviously that program would have had great difficulties to complete a real high-density PCB design, including many irregular parts and analog circuits with special requirements. I doubt that Fable would fare better.
Major ISPs in the US have been doing it for at least a decade. Xfinity Wifi [1] claims over 20 million wifi hotspots provided through customer routers.
It was donated without CCDs or electronics, which is what makes the difference between earth and space observation satellites. NASA only got the body and optics (mirrors), they had to provide their own sensors.
They've been used for over 20 years but until they became a weight loss drug recently, almost all of the research was on diabetics which introduces two confounding factors: diabetes and the diets diabetics already have to follow to manage the disease. It's hard to draw any conclusions when the results are muddied by those two factors.
> Can you give an example of an incomprehensible piece of writing (any writing, never mind a proof) that has commercial value commensurate with the costs involved here?
It depends on what exactly you mean by "commercial value commensurate with the costs involved" but I'd volunteer the 3G/4G/5G specifications and the other documentation required to implement the mobile network protocols. 5G is currently sitting at over 50,000 pages and it's one of the reasons Qualcomm/Broadcom/Apple are the only ones who can realistically make a mobile radio.
I don't think there is a single human to whom more than a few thousand pages would be comprehensible at a time except for the occasional genius.
Read the rest of the discussion. The claim is about text which is in principle incomprehensible to humans.
If there exists a text which only one person can understand, that person can communicate their understanding to others, even if that doesn't help them with the original text. That dissemination of knowledge is what provides the value, not the mere existence of the text. If that person forgets or dies before they can share their knowledge then it will be lost.
We have many examples of this from history: ancient texts written in a lost language. These texts provide us with no value until the day they can be deciphered, unless you count linguistic puzzle-solving as a virtue.
> If there exists a text which only one person can understand, that person can communicate their understanding to others, even if that doesn't help them with the original text.
If there exists a text which only an AI can understand, that AI can communicate their key conclusions to others, even if that doesn't help them with the original text.
The only difference here is the amount of meat involved. Perhaps tossing a few steaks on the server racks could help with that.
If an AI can communicate its findings to us in a way that we can understand it, then its findings are by definition intelligible to humans. Your claim was about texts for which this is not possible.
So, you're willing to claim that a conclusion that you don't understand the reasoning for is equivalent to comprehension?
Because, again, I can point to hundreds of examples of texts where nobody but the author understands it, and they're only giving summarized "commandments" that you should follow if you want good results.
If I told you "don't use spin locks, call futex instead", do you think have gained an understanding of the Linux scheduler?
If I told you "don't use spin locks, call futex instead", do you think have gained an understanding of the Linux scheduler?
Yes, because I already knew what schedulers are, what spinlocks are, and if I want to know what futex is I can go look it up. Comprehension is within my grasp.
Your original claim, which you’ve repeatedly distanced yourself from (by trying to use comprehensible examples) but won’t admit to, was about incomprehensible stuff. That is, text that no human could possibly understand, ever.
You’re repeatedly engaging in intellectual dishonesty rather than simply admit that “human comprehension probably will continue for the foreseeable future”, which is really not a controversial idea at all.
Bullshit. Human comprehension will not continue, it will reduced to "when the AI tells us to add Bismuth, strontium, and copper together in this way, we get a superconductor", but that doesn't mean we understand high temperature superconductivity.
For what it's worth, we've known about BSCCO for nearly 40 years, and we still don't have a great physical understanding of how it works, thought we made decent progress in 2022.
You're using a very bad definition of incomprehensible. We don't understand the chemistry behind how these things work, it's that simple. If you're going to argue it's comprehensible, you'd better show how it works and go collect your Nobel prize.
All we know is that if we melt the right rocks together, we get a superconductor that works in some mysterious way that we can't explain. We know it's not Cooper pairs.
Since it's comprehensible, please point me to someone that can comprehend high temperature superconductivity and how it works, and then explain why they didn't explain it.
With the definition you seem to want to use, it's impossible for anything to be incomprehensible, and therefore it's tautological that there's no incomprehensible LLM output: nothing at all is incomprehensible.
Do you have an example of anything incomprehensible? Anything at all? Even the things that Gödel would say are inaccessible could, in theory, become accessible: we just don't know with absolute certainly that the mathematics it was based on got all the axioms right, though we see no errors now.
I think we're underestimating just how much low hanging fruit there is. I've been trying to apply this LLM research process to physics (QM and solid state) and there is so much missing in Physlib and the rest of the Lean ecosystem that most of my work has been trying to formalize the theories and validating them against the specification problem (and mostly failing badly).
The important part of the professional certification like PE or MD is the liability that comes with it, which means that the professional has a lot more agency. A construction firm or hospital can't really force their professionals to do anything because the consequence is criminal prosecution (and a lot of legal liability for the employer).
Bring a software engineer into a courtroom as an expert witness, and the jury's eyes will glaze over. Bring in the PE who told their firm not to cut that corner, and the hammer comes down hard.
Even if the certification for software engineers starts as barebones as knowing what WASP is, it still provides an avenue for the feedback mechanism to work (the rules "written in blood"), so that the entire industry can study and learn from what happened, instead of this mess we have now, the peak of which is postmortem blog posts. Even now we have plenty of examples of regulatory frameworks where the regulations adapt to the field like the FDA where you've got a huge spectrum ranging from diagnostics to medical devices of which where are many classes, and drugs where every clinical trial can be tailored to the exact nature of the disease.
I have been a professional software developer for decades and worked in several roles where quality and security were at a premium but I have no idea what you mean by WASP. And yet you described it as "barebones" - an interesting illustration of the problem here. Real engineers have many years seeing the hard way what actually works. In software we don't have that kind of consistency and shared understanding of how to reliably get good results yet.
In my experience, good software engineers are often better "engineers" than those working in more physical disciplines, because they get a lot more practice. But traditional engineers have a far better culture when it comes to testing and validation. Since the cycle time is longer, and the cost of mistakes is higher, analysis and testing are generally baked in from the beginning. In software, it's easier to skip that stuff. But software engineers who do get indoctrinated into that culture learn most of the same lessons that traditional engineers do (i.e. how can a component be tested and maintained? what makes for a good design?) and the speed of development means they get more exposure to those types of challenges in general.
In my experience this works both ways too. Good engineers working on physical projects have picked up on some of the useful practices that good software developers have adopted for maintaining progress in the face of ambiguous requirements until they can be clarified and allowing as much flexibility as possible without necessarily compromising quality in the meantime. I believe these relationships can be summarised as something like "Good people keep open minds and learn from what has worked well for others".
The problem for regulating software development is still who gets to formally determine who the "good" people are. This kind of thing should clearly be objective and evidence-based but what useful evidence do we have available?
In physical engineering disciplines there are often clearly evident problems if something was built without being adequately specified by the responsible engineers. In a disastrous case a bridge might literally fall down but you're also going to see that a bridge wasn't designed properly if it's distorting in ways it shouldn't under loads that it should be able to support. There are lots of experienced engineers who have proven records specifying buildings or planes or ships that need to not break using established and peer reviewed techniques.
In software we can all agree catastrophic failures that result in loss of life or half the Internet going down are obviously bad. For something controlling a life-saving medical device or the launch authorisation system for the nuclear missiles we can probably all agree that the answer to what quality level we want in the software is "the best quality we can achieve". But those systems have unusually serious consequences if anything ever goes wrong and probably also very high development budgets that can justify such an extreme position on quality. In general we don't have clearly defined levels of software where different trade-offs between cost and risks and other factors might be considered reasonable and acceptable. Nor do we have well tested and universally accepted standards for how to reliably achieve a specified quality level.
> The problem for regulating software development is still who gets to formally determine who the "good" people are. This kind of thing should clearly be objective and evidence-based but what useful evidence do we have available?
There is zero useful evidence because there is no one to collect it.
The Institution of Civil Engineers was founded in 1818, after decades of random civil engineering societies in Britain doing the exact same thing we are now (running around like chickens with their heads cut off). It wasn't until after the ICE's Royal Charter a decade later that civil engineering began to get really systematized into the "real engineering" we know today and that charter effectively established them as a regulatory body that allowed that to happen.
There is zero useful evidence because there is no one to collect it.
I'm not sure that is entirely true. There have certainly been a few people who have attempted to study what did or didn't work in industrial settings - either pure academics or people working in industrial research labs. But I agree that currently we have nowhere near enough data to form robust conclusions about almost anything in this field and I think this is the strongest argument that the industry is not ready for any kind of licensing and regulation regime.
I'm wondering what data you're using and if you can impose a more precise coordinate system into the visualizations with ways to track a specific point (perhaps starting from polygons or GPS coordinates). It seems the visualization includes sea level rise but it's hard to figure out if its getting other details right like the California’s Transverse Ranges uplift (~20 mYa to present) which moved the Los Angeles basin several hundred kilometers northwest all while San Diego and Baja California were also rearranged.
That's not how Metcal fixed temp induction soldering irons work. They don't have a control loop, which is what makes them so much better than other soldering irons.
They exploit the Curie temperature [1] of some alloys, in which the metal loses its inductive properties when it hits a certain temperature. A Metcal power supply pumps a simple 13.56 Mhz signal into the tip which heats it up and when it reaches its Curie temperature, it just stops heating. Since the signal is constant, whenever the temperature of the tip drops it just heats back up without any PID loop. The downside is that you have to switch tips (alloys) with a pair of pliers to change temperatures, but the upside is that there is no control loop delay.
It's also why their station are so reliable. There's basically no "modern" electronics in them and the worst you have to do to fix them is replace an electrolytic capacitor. I've got a power supply manufactured in the late 90s that's still as good as new and like you said, going back to a Hakko or any other soldering iron is downright painful.
(Side note to anyone who cares: when the patents expired, a couple of Metcal engineers left to form Thermaltronics, which sells cheaper stations and Metcal-compatible tips)
[1] https://en.wikipedia.org/wiki/Curie_temperature
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