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I’ve been looking for a good solution for doing the exact opposite, being able to connect stuff through USB in my bench, and see them pop up in my office desktop as if they were usb devices.

The closest I’ve gotten is using a raspberry pi in the workbench, but for some weird devices that’s sometimes not good enough.


In a Windows world I've used the hell out of these devices for licensing dongles on Windows virtual machines: https://www.silextechnology.com/connectivity-solutions/devic...

They're much cheaper than the competing devices from Digi and they've been bulletproof for me. I've got some out there running >10 years.

I've even done stupid stuff like hung a USB Ethernet adapter off of one and made it a NIC on my local PC to talk to another of the same unit hanging off that USB NIC (just to be cheeky-- not for actual use). Stacking things on top of other things is fun.

My only complaint is I wish they did PoE. I use a cheap PoE splitter for that but it would be nice not to have to do that.


If you have CAT5/6 between the locations, USB-over-CAT5/6 adapters are inexpensive and work quite well. I've used OREI's successfully over >60m. But there are many options, with varying limits on cable length.

https://www.orei.com/products/usb-over-ethernet-extender-upt...


There USB over IP. I think Linux supports it. It could be possible to have Pico implementation, use WiFi like this, and connect to computer or another dongle.


Author here: I have wanted to make a wireless USB mouse and keyboard switch out of RPI Pico Ws for a long time. I would go a layer deeper than USB/IP, because I want to cache the USB handshake to keep the connection enumerated on multiple systems without dropping.


I've used USB over Network in the past, worked well on Linux


Germany, France and Spain are some of the biggest offenders here.

Some years ago a case became quite famous in Spain. Someone wanted to turn a winery into a eco-tourism boutique hotel with a winery tour and experience. Should be simple in theory, in practice they were waiting for authorization to open for more than 4 years.

I’ve been involved with startups and small businesses for more than a decade, and I haven’t still heard of any of them doing things 100% by the book, because it’s just impossible.

People just start and hope the taxman doesn’t come.


> Someone wanted to turn a winery into a eco-tourism boutique hotel with a winery tour and experience.

Because a agricultural business and a hotel business are two different things, and Spain has, rightfully so, their thumb on the spread of tourism, because it affects local communities negatively.

Otherwise investors could just come in, buy a random agriculture business and then turn it into luxury hotels/lodging.

> I’ve been involved with startups and small businesses for more than a decade, and I haven’t still heard of any of them doing things 100% by the book, because it’s just impossible.

Because entrepreneurs are notoriously bad thinking further than their own interests. It always, "just" something they want to do.

Zoning rules and regulations have their purpose. Are some of those in some places idiotic? Yes. Do most of them still have their reason? Also yes.

Otherwise we can stop protesting datacenters and the trump family building a eco-luxury resort in a nature reserve.


Rules exist for a reason, it shouldn't take 4 years to get an answer on how to proceed in one direction or another. In NYC for example you often need to hire a "permit expediter" just to get a yes/ no/ maybe answer on your apartment renovation within a year. These bureaucracies are often literally impenetrable without professional help.


I’m guessing they did receive an answer earlier than four years, but they wanted it to be Yes.


I cannot believe there are people defending this.


What? So you should just be allowed to do as you please? Start with an eco-retreat on your winery. Then build out luxury apartments? Then where to go from here? Maybe get rid of the winery for a golf course? Creep your way into a luxury resort?

Where is the line?


Probably somewhere between luxury resort and nuclear weapons development facility, and probably closer to the nuclear weapons development facility.


I think these simplifications end up hurting more than helping.

30% tree cover looks very different depending on the trees your municipality chooses.

For example, Barcelona covers everything with a variety of Platanus, which is easier to keep than other trees, but it’s quite dirty and produces A LOT of pollen. For me, that I’m allergic to it, it just makes the city unavailable for 2-4 weeks every year.

Having smaller plants, with more variety also feels much better than just sprinkling the right amount of massive trees with equal spacing. I’m pretty convinced part of the “we need more green” feeling people get is actually “I need something in my environment to not look like a grid”.


> Having smaller plants, with more variety also feels much better than just sprinkling the right amount of massive trees with equal spacing.

The thing people want from trees is shading and general cooling of the environment. Small plants provide much less of that and the summers are increasingly hot.


I also think these are harmful simplifications, for several reasons.

First of all, I'm skeptical about the study that proves that people seeing three trees have better mental health. There are so many factors that it's hard to separate one. A solid study would compare families living in the same building, roughly at the same floor, and with similar parameters (family size, income, education, street noise, etc.). Comparisons from different buildings induce too many side factors. I think that collecting this sample would be very hard. I can't access the full-text behind the paywall, so I don't know their methodology, and their abstract is vague, so I fear the paper is meaningless.

Then do people really watch that much through their windows? I'd be surprised that having a glimpse of a few trees at home once a day could change anyone's life.

Even if trees did has a positive impact on mental health, I suppose inciting people to bike or walk (at least partly) to workplaces and stores would dwarf that impact, for mental and physical health.

Lastly, the 30% of tree cover seems arbitrary. For the same percentage, would covering every street with trees have the same impact as keeping trees inside parks? I think the goal to provide places where people go for a walk requires different solutions than the goal to reduce the heat in a concrete jungle.


I think shade is a big factor here. Trees can really cool down a neighborhood.


Big factor is evapotranspiration. Shade is less useful.


But that isn’t the point at all.

For most businesses, you’re not the target audience of your website, your potential customers are.


Yes. That’s the point. You’re in a conversation with your customers, their website interactions is your opportunity to develop your identity/brand. The way you yourself (assuming you’re the founder for example) feel about it does matter quite a lot


This is how your company goes broke. There was a company, Amie, that had this [0] as their landing page initially, without the /art path. Guess what, visitors didn't convert, and then the company redid their landing page [1] to actually explain and convert customers. They literally host their prior landing page as "art" because it was so terrible at acquiring customers.

[0] https://amie.so/art

[1] https://amie.so


They had a "normal" page before the art one for the longest time according to my memory but confirmed by web archive.

Also: the current website is for a different product altogether. They pivoted.

Attributing low conversion rate to the style of the page isn't really fair when it was apparently a last attempt at attracting customers for an idea that was eventually abandoned.


Don’t know the specifics of the Espressif RISC-V cores, but in general they can’t really compete on those aspects with ARM.

ARM is a much more mature platform, and the licensing scheme helps somewhat to keep really good physical implementations of the cores, since some advances get “distributed” through ARM itself.

Compute capabilities and power efficiency are very tied to physical implementations, which for the best part is happening behind closed doors.


Well, that depends on what you count as a backdoor, but Espressif has had some questionable flaws:

- Early (ESP8622) MCUs had weak security, implementation flaws, and a host of issues that meant an attacker could hijack and maintain control of devices via OTA updates.

- Their chosen way to implement these systems makes them more vulnerable. They explicitly reduce hardware footprint by moving functionality from hardware to software.

- More recently there was some controversy about hidden commands in the BT chain, which were claimed to be debug functionality. Even if you take them at their word, that speaks volumes about their practices and procedures.

That’s the main problem with these kinds of backdoors, you can never really prove they exist because there’s reasonable alternative explanations since bugs do happen.

What I can tell you is that every single company I’ve worked which took security seriously (medical implants, critical safety industry) not only banned their use on our designs, they banned the presence of ESP32 based devices on our networks.


You can hide malicious intent, so the repeated negligence patterns you’re pointing out make a better signal. Smart. Thx for the perspective


Obviously... They are not made for safety critical systems. It's for hobbyists.


These parts are in a massive number of retail smart switches 3d printers and iOT devices.

They are definitely beyond a hobby device.

They're made well, designed well and the libraries are some of the best in class.

My concern is purely on risk.

What would any responsible state security agency spend to have devices behind every single firewall of an adversary?


Except if you penetrate the market with modules that cost 5% of similar US made solutions, you start to win mindshare. At least some of those hobbyists start making a product, and sometimes the determination of whether a product is "safety critical" isn't agreed upon until after it's failed catastrophically.


Except that strategy gets you killed through a thousand paper cuts.

What would have you done when the Bitcoin fork happened 50/50? Would you have gone int ICOs? Which ones? Etc…

There’s simply too many “new things”, so by trying to get exposure to them you’ll be massively in the red.

Let’s say you get into 1000 “new things”, and you strike it lucky and hit BTC. You’d had to buy BTC in early 2013, hold it over the whole period and sold at the historical maximum for you to be at break even.

If instead of buying 1000 “new things”, you’ve put your money into the S&P you’d be at +250% by the same time.


This depends very much on your line of work.

As a freelancer I do a bit of everything, and I’ve seen places where LLM breezes through and gets me what I want quickly, and times where using an LLM was a complete waste of time.


For sure. The more specialized or obscure of things you have to do, the less LLMs help you.

Building a simple marketing website? Probably don’t waste your time - an LLM will probably be faster.

Designing a new SLAM algorithm? Probably LLMs will spin around in circles helplessly. That being said, that was my experience several years ago… maybe state of the art has changed in the computer vision space.


> The more specialized or obscure of things you have to do, the less LLMs help you.

I've been impressed by how this isn't quite true. A lot of my coding life is spent in the popular languages, which the LLMs obviously excel at.

But a random dates-to-the-80s robotics language (Karel)? I unfortunately have to use it sometimes, and Claude ingested a 100s of pages long PDF manual for the language and now it's better at it than I am. It doesn't even have a compiler to test against, and still it rarely makes mistakes.

I think the trick with a lot of these LLMs is just figuring out the best techniques for using them. Fortunately a lot of people are working all the time to figure this out.


Agreed. This sentiment you are replying to is a common one and is just people self-aggrandizing. No, almost nobody is working on code novel enough to be difficult for an LLM. All code projects build on things LLM's understand very well.

Even if your architectural idea is completely unique... a never before seen magnum opus, the building blocks are still legos.


the building blocks never were the hard part tho


> I've been impressed by how this isn't quite true.

I’d say it’s true, but the LLMs and humans don’t have the exact same definition of what “obscure” is.

Karel is almost a subset of Pascal with some keyword swaps. And there’s a LOT of Pascal (and similar languages) around.

From the PoV of a statistical based tool like an LLM, Karel is just another flavor of a very popular structure.


Specialized is probably not the word I'd use, because llms are generally useful to understand more specialized / obscure topics. For example I've never randomly heard people talking about the dicom standard, llms have no trouble with it.


I think there is a sweet spot for the training(?) on these LLMs where there is basically only "professional" level documentation and chatter, without the layman stuff being picked up from reddit and github/etc.

I was looking at trying to remember/figure out some obscure hardware communication protocol to figure out enumeration of a hardware bus on some servers. Feeding codex a few RFC URLs and other such information, plus telling it to search the internet resulted in extremely rapid progress vs. having to wade through 500 pages of technical jargon and specification documents.

I'm sure if I was extending the spec to a 3.0 version in hardware or something it would not be useful, but for someone who just needs to understand the basics to get some quick tooling stood up it was close to magic.


The standard for obscurity is different for LLMs, something can be very widespread and public without the average person knowing about it. DICOM is used at practically every hospital in the world, there's whole websites dedicated to browsing the documentation, companies employ people solely for DICOM work, there's popular maintained libraries for several different languages, etc, so the LLM has an enormous amount of it in its training data.

The question relevant for LLMs would be "how many high quality results would I get if I googled something related to this", and for DICOM the answer is "many". As long the that is the case LLMs will not have trouble answering questions about it either.


> llms are generally useful to understand more specialized / obscure topics

A very simple kind of query that in my experiences causes problems to many current LLMs is:

"Write {something obscure} in the Wolfram programming language."


One tendency I've noticed is that LLMs struggle with creativity. If you give them a language with extremely powerful and expressive features, they'll often fail to use them to simplify other problems the way a good programmer does. Wolfram is a language essentially designed around that.

I wasn't able to replicate in my own testing though. Do you know if it also fails for "mathematica" code? There's much more text online about that.


> Do you know if it also fails for "mathematica" code?

My experience concerning using "Mathematica" instead of "Wolfram" in AI tasks is similar.


Several years ago is ancient with the rate of advancement that LLMs have had recently


> Building a simple marketing website? Probably don’t waste your time - an LLM will probably be faster.

This is actually where I would be most reluctant to use an LLM. Your website represents your product, and you probably don’t want to give it the scent of homogenized AI slop. People can tell.


They can tell if you let it use whatever CSS it wants (Claude will nearly always make a purple or blue website with gross rainbow gradients). They can also tell if you let it write your marketing copy.

If you decide on your own brand colors and wording, there’s very little left about the code that can’t be done instantly by an LLM (at least on a marketing website).


I just read Claude's front-end design instructions, and it now explicitly bans purple gradients. Curious to see what new pattern it will latch on to.


But this learning is also value.

Without playing around with it, you wouldn't know when to use an LLM and when not.


But the models change every 3-6 months. What's the use of learning what they can and can't do when what they can and can't do changes so frequently?


Some subscriptions offer "unlimited tokens" for certain models. i.e. GitHub co-pilot can be unlimited for GPT-4o and GPT-4.1 (and, actually, GPT-5 mini!). So: I spent some time with those models to see what level of scaffolding and breaking things down (hand holding) was required to get them to complete a task.

Why would I do that? Well, I wanted to understand more deeply how differences in my prompting might impact the outcomes of the model. I also wanted to get generally better at writing prompts. And of course, improving at controlling context and seeing how models can go off the rails. Just by being better at understanding these patterns, I feel more confident in general at when and how to use LLMs in my daily work.

I think, in general, understanding not only that earlier models are weaker, but also _how_ they are weaker, is useful in its own right. It gives you an extra tool to use.

I will say, the biggest findings for "weaknesses" I've found are in training data. If you're keeping your libraries up-to-date, and you're using newer methods or functionality from those libraries, AI will constantly fail to identify with those new things. For example, Zod v4 came out recently and the older models absolutely fail to understand that it uses some different syntax and methods under the hood. Jest now supports `using` syntax for its spyOn method, and models just can't figure it out. Even with system prompts and telling them directly, the existing training data is just too overpowering.


I would say they are not changing but evolving and you evolve with them.

For example: gemini became a lot better in a lot more tasks. How do I know? because i also have very basic benchmarks or lets say "things which haven't worked" are my benchmark.


If you had to hold on for dear life during the ~2014-2017 JavaScript framework chaos, then 3-6 months is peanuts.

This is an industry that requires continuous learning.


Honestly I think this is the primary explanation for why there is so much disagreement on if LLMs are useful or not. If you leave out the more motivated arguments in particular.


The way early adopters got rich was by scamming others, so not sure I see your differentiation there


I’d expect this crap from Google, but not Apple.

If this doesn’t get fixed, I’m going to have to rethink a lot of my digital life, including my company’s.


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