montereynack

Cool to see principles behind this, although I think it’s definitely geared towards the consumer space. Shameless self plug, but related: we’re doing this for industrial assets/industrial data currently (www.sentineldevices.com), where the entire training, analysis and decision-making process happens on customer equipment. We don’t even have any servers they can send data to, our model is explicitly geared on everything happening on-device (so the network principle the article discussed I found really interesting). This is to support use cases in SCADA/industrial automation where you just can’t bring data to the outside world. There’s imo a huge customer base and set of use cases that are just casually ignored by data/AI companies because actually providing a service where the customer/user is is too hard, and they’d prefer to have the data come to them while keeping vendor lock-in. The funny part is, in discussions with customers we actually have to lean in and be very clear on “no this is local, there’s no external connectivity” piece, because they really don’t hear that anywhere and sometimes we have to walk them through it step by step to help them understand that everything is happening locally. It also tends to break the brains of software vendors. I hope local-first software starts taking hold more in the consumer space so we can see people start getting used to it in the industrial space.

Gonna throw in my hat and say that if you’re working on industrial applications (like energy or manufacturing) give us a holler at www.sentineldevices.com! Plug-and-play time series monitoring for industrial applications is exactly what we do.

Gonna throw in my hat here, time series anomaly detection for industrial machinery is the problem my startup is working on! Specifically we’re making it work offline-by-default (we integrate the AI with the equipment, and don’t send data to any third party servers - even ours) because we feel there’s a ton of customer opportunities that get left in the dust because they can’t be online. If you or someone you know is looking for a monitoring solution for industrial machinery, or are passionate about security-conscious industrial software (we also are developing a data historian) let’s talk! www.sentineldevices.com

We’ve finally managed to give our AI models existential dread, imposter syndrome and stress-driven personality quirks. The Singularity truly is here. Look on our works, ye Mighty, and despair!

Seconding the other question, would be curious to know

‘"An ML engineer at Slack says they don’t use messages to train LLM models," Orosz wrote. "My response is that the current terms allow them to do so. I’ll believe this is the policy when it’s in the policy. A blog post is not the privacy policy: every serious company knows this."’

I really wish this advice was followed to the letter. I’m sick and tired of trying to read into policies on AI training (or AI anything these days) that is pure blog posts on how the service works and what the data protections are. Even from Microsoft no less! Even their “documentation” has a bad habit of referring to half-decisions alluded to in a blog post, saying this is how it works, just trust us, interpret this policy vaguely because we interpret it vaguely. None of the cloud vendors will just sit down with you and sign a contract saying what they will or will not do, they all default to as minimal responsibility as possible. And then they have the guts to jump in on regulation - there’s zero components of the current way these giants do business in AI that is amenable to regulation, at least not in a way that helps you unless you’re an uber-enterprise.

I sympathize a lot with the headline statement; it boggles my mind on a lot of the data residency/integrity/confidentiality measures taken around massive data silos (as well as the infra teams companies bring to bear to manage, scale and then inevitably publish gospel articles on the web about) when companies could just opt… NOT to collect that data? I really like the model of “It stays on your device, we never see it. At most we get bare-minimum location statistics.” Although I question the assertion that their metrics system won’t be turned against them; seems obvious that anything programmed can be reprogrammed or updated, especially in the modern update-focused age. I don’t think they addressed that beyond a general statement that they took pains to assure that their users won’t ever be spied on. Would be interested in a technical article on that.

Side note, we at Sentinel Devices are taking exactly this “we don’t hold your data” approach for industrial machinery. Think automated AI pipelines that are air-gapped. And we’re hiring! If you’re interested, reach out to [email protected]

Since this is a topic that’s near and dear to my heart, going to quickly plug my own startup that’s doing exclusively this: www.sentineldevices.com. We make industrial equipment smart enough to self-monitor and self-report issues using AI, but we are specialized in making AI that does EVERYTHING (including training) on embedded devices (think something only marginally more powerful than an RPi 4) so we never call out to a server. As the article notes, a big challenge has been making the AI and all support software resilient and able to “bounce back” from random occurrences in industrial environments (which can be extremely unpredictable and unique). Also as the article notes, this pretty handily opens up the Defense market since we don’t need to clear a cloud component.

Feel free to reach out at [email protected] if you’d like to chat. We’re building and trying to take people on part-time if anyone’s interested in this space! Also if anyone just wants to talk about challenges in the space I’m happy to, HN usually gives really great conversation partners.

Sorry, but this is untrue; action potentials in neurons have extremely complex interplay with each other, including residual “soft” periods and chemically-induced changes in how they fire. Neurons don’t just “fire” or “not fire”, they adaptively change the strength of their firing constantly, unpredictably and continuously.

Hey, I’m a big fan of what you’ve been doing since I stumbled upon it in 2021. Do you have an estimated timeline on when you guys will have that web-app API available, even as a beta? Incorporating a web app with the same ease textualize can be implemented with (or even getting a web app with cross-compatible TUI as a fallback) would be super attractive for the product I’m currently working on.

I guess I’ll take the opportunity to throw in my hat… I’m currently running a very early-stage startup trying to address some of the brain drain and complexity in industrial maintenance. If you’d like to talk/rant about your job and the pain points you have, I’d be all ears! Wouldn’t be a sales call, I’m just trying to talk to people at this point. Feel free to DM me if interested.

I'll take this opportunity to plug my own question to the folks on HN - does anybody know how much protection an LLC generally provides you w.r.t. lawsuits and such? I'm currently looking at doing software consulting for a startup, but indemnification clauses have been touchy for the people I've talked to (and I'm paranoid about losing more than I gain in an unfortunate situation). My lawyer has told me that "piercing the corporate veil" is difficult and an LLC should protect me relatively well, but a good friend told me that I should basically always limit my liability to the amount I've been paid as in his opinion the LLC would be of questionable utility. I know HN isn't the place for legal advice, just wondering if anyone has friendly opinions.

I tried googling this, but the SEO spam is so bad I always converge to the same damn sites. Maybe google search for legal layperson questions is the next big thing?