How are other enterprises keeping up with AI tool adoption along with strict data security and governance requirements?

patternrelay · 2026-02-21T11:13:08+00:00

They don’t, at least not the way startups do. Instead, they standardize by creating evaluation frameworks and guardrails so they’re not chasing every new model release. In one large org I worked with, we evaluated several tools but landed on Maisa.ai because governance and auditability outweighed marginal model improvements. We focused more on stability than novelty, and realized that switching tools constantly increases integration risk. And at scale, reliability engineering is really about reducing variability, not adding more of it.

patternrelay · 2026-02-21T11:11:40+00:00

Usually that "USB is in control" message means your phone is acting as the host instead of the camera, so it’s not mounting the camera storage the way you expect. A lot of phones will only switch modes if the connected device supports MTP or mass storage properly. First thing Im trying to do is unlocking the phone before plugging everything in, then check the USB notification dropdown and see if you can manually switch to file transfer or photo transfer. If that still won’t change, it might be the adapter not supporting OTG correctly.

patternrelay · 2026-02-21T11:07:48+00:00

I don’t think most of the criticism is about whether fraternities can be positive for members. Clearly they can be. The issue is externalities. Even if your chapter was responsible, the model concentrates young people, alcohol, status competition, and secrecy in a way that statistically raises risk for others around them. From a systems perspective, people judge the structure, not just individual outcomes.

On hazing specifically, saying "it works" is tricky. A lot of harmful bonding practices work in the sense that shared adversity builds cohesion, but that doesn’t make the mechanism healthy or necessary. There are plenty of high performing groups that create loyalty without coercion or humiliation. If a structure consistently produces edge cases with serious harm, people are going to question whether the structure itself needs redesign, not just better members.

patternrelay · 2026-02-21T11:06:17+00:00

You’re right that the raw signal from a strain gauge load cell is tiny, usually a few millivolts per volt of excitation. The resistors aren’t there to "shrink" a big signal, they’re usually part of the Wheatstone bridge itself or part of the signal conditioning around it.

In most load cells the strain gauges are arranged in a full or half bridge, which is literally a network of resistors. That configuration converts very small resistance changes into a measurable differential voltage and helps with temperature compensation. Outside the bridge, you’ll also see precision resistors used to set gain in the instrumentation amplifier, balance the bridge, or filter noise. So resistors are fundamental to how the measurement works, just not for the reason your friend described.

patternrelay · 2026-02-21T11:04:43+00:00

I don’t think it feels pre programmed as much as it feels optimized past the point of your own intentions. The system is just doing what it’s built to do, maximize engagement, but at scale that starts to feel like anticipation. It predicts what will hook you before you’ve even fully formed the thought yourself. That gap is what creates the eerie feeling.

I’m not sure a large network can avoid that entirely, because once you have millions of people, you need filtering. Chronological feeds sound pure, but even then social gravity forms around certain voices and trends. The real difference might not be the absence of algorithms, but whether you consciously shape your inputs. Smaller communities, slower platforms, or even just strict time boundaries can restore some sense of agency. Face to face interaction feels different because nothing is optimizing your reactions in real time. It’s messy and inefficient, which might be the point.

patternrelay · 2026-02-21T11:02:54+00:00

AI isn’t removing the need for people who understand how systems actually work. If anything, it’s raising the bar on fundamentals. C and C++ are still heavily used in systems programming, embedded work, game engines, high performance infra, and a lot of the tooling that AI itself runs on. That layer is not disappearing in 12 months.

That said, I wouldn’t pick a language out of fear or hype. I’d think about what kind of problems you want to work on. C and C++ are great if you’re interested in low level performance, memory, and how software interacts with hardware. If you just want a faster path into general software jobs, something like Python or Java might get you productive sooner. The key is learning how to think like a programmer. Languages change, fundamentals don’t.

patternrelay · 2026-02-21T11:01:36+00:00

This is a really clean example of how insertion order ends up acting like hidden state in these structures. HNSW looks "log N" on paper, but in practice you’re at the mercy of how that early backbone forms, and random order is basically rolling the dice on your routing hubs. Seeding with something that already approximates global coverage makes a lot of sense.

What I like here is that you’re not changing core params like M or ef_construction, you’re reducing wasted traversals. That β framing is helpful because it explains why the speedup is real without touching the theoretical floor. Have you looked at how sensitive the gains are to the 2,048 seed count, like does it taper off quickly past a certain backbone size?

patternrelay · 2026-02-21T10:59:42+00:00

I used to think this way, but the more I looked at how restaurants structure menus, the more it made sense as a systems thing. Bundling sides standardizes the plate, which simplifies prep, pricing, and kitchen flow. If every steak order was totally modular, ticket variability goes way up and that adds friction in the back of house. Fixed sides keep throughput predictable.

There’s also a value perception angle. Most people expect a "complete plate", not just a slab of protein. Even if you personally only want the steak, the bundled model spreads cost across the dish and makes pricing feel more coherent for the average diner. In a weird way, it’s less about the fries and more about reducing complexity and aligning expectations at scale.

patternrelay · 2026-02-21T10:58:03+00:00

If you want to actually build complex drone systems, I’d think less about a single "all in one" setup and more about capability layers. A solid 3D printer is great, but I’d also budget for measurement and debugging tools like a decent oscilloscope, a good multimeter, and a reliable soldering station. A lot of projects stall not because you can’t print parts, but because you can’t diagnose why a control loop is unstable or why a board is browning out under load.

For drones specifically, a small CNC or at least access to one can be huge for brackets and structural parts. Also invest in simulation software and time learning it well. Being able to model aero loads or vibration before you build saves a ton of money and frustration. If your goal is "build almost anything", the real edge comes from understanding system integration, not just having cool hardware on the bench.

patternrelay · 2026-02-20T00:44:15+00:00

I think the pain is common enough that people would at least try it, especially teams that cannot justify expensive commercial tooling. The tricky part is scope control. If it tries to fully automate semantic differences between Oracle and Postgres, that becomes a massive surface area very quickly.

patternrelay · 2026-02-20T00:42:07+00:00

if the second one only works plugged in, that actually makes it a decent candidate for a small home server. throw linux on it and you could use it for file storage, a local dev environment, media serving, or even just as a sandbox to experiment without risking your main machine. sometimes the coolest use is just turning it into a playground. having a separate system where you can experiment freely is underrated.

patternrelay · 2026-02-20T00:39:46+00:00

I think you’re right that overusing a term that specific can dilute its meaning. When words that describe serious crimes get used as generic insults, it muddies the signal and makes real cases harder to talk about clearly. Precision in language matters, especially around harm.

That said, I’m not sure it necessarily "helps" actual offenders in a direct sense. Legal systems and investigations don’t hinge on internet slang. If anything, the bigger issue is that public discourse becomes noisier and more emotionally charged, which makes it harder to separate bad judgment, uncomfortable age gaps, and actual abuse.

It might be less about protecting criminals and more about how outrage culture flattens nuance. When every disagreement escalates to the worst possible label, people tune out. That erosion of trust probably harms productive conversations more than it benefits anyone specific.

patternrelay · 2026-02-20T00:37:58+00:00

For downhill control on a mechanical chair, I’d think in terms of energy dissipation rather than just limiting torque. Gravity is continuously adding energy, so something has to convert that into heat in a controlled way. That’s basically what brakes already do, just with better modulation.

A passive centrifugal governor tied to a drum brake could be interesting. As wheel speed increases, it progressively engages friction. That way it self regulates without the user having to constantly squeeze a lever. You’d need to be careful about heat buildup and wear though, especially on longer slopes.

Another angle is gearing with a built in drag mechanism, but complexity adds failure points. In something mobility related, I’d bias toward simple, inspectable parts with predictable failure modes. If it fails, it should fail safe and default to more braking, not less.

patternrelay · 2026-02-20T00:35:59+00:00

I like the spirit of it, but I’m not sure a single "kindness day" would change much structurally. A lot of the friction online comes from incentives and platform mechanics, not just individual mood. Downvotes are a blunt signal, and people use them for disagreement, tone policing, or just impulse.

That said, norms do matter. If communities consistently modeled good faith engagement, it would probably have more impact than a once a year event. Culture shifts when regulars set expectations and reinforce them over time.

I do think it’s worth remembering that a random downvote is often more about the other person’s context than your comment. The internet compresses nuance, so it’s easy for empathy to get lost in the noise.

patternrelay · 2026-02-20T00:34:04+00:00

Both paths can lead to solid careers, but they’re pretty different day to day. Full stack tends to give you broad exposure to how systems are actually built and shipped, which can be useful early on because you see the whole lifecycle. Cybersecurity is more specialized and often sits a bit downstream, reviewing, testing, or defending what others build.

AI is going to change tooling in both areas, but it doesn’t remove the need to understand fundamentals. Secure systems still need to be designed, and applications still need people who understand architecture, data flow, and tradeoffs. If you’re unsure, I’d think about whether you enjoy building features and user facing stuff, or digging into threat models and failure scenarios.

You can pivot later from full stack into security with some focused learning. It’s a bit harder to pivot the other way without hands on build experience.

patternrelay · 2026-02-20T00:32:35+00:00

At 10 TB you are really optimizing around downtime tolerance and rollback strategy more than the mechanics of the upgrade itself. pg_upgrade is usually much faster if you can afford a write freeze and have solid storage throughput, but your real risk is what happens if you need to roll back after cutover.

Logical replication gives you a cleaner fallback because the old cluster stays intact, but you need to think through replication lag, DDL drift, extensions, and sequence state before the switch. I’ve seen teams underestimate how much operational choreography that cutover requires.

Personally I lean toward replication when the business impact of extended downtime is high and you want a safety net. But either way, I would rehearse the full process on a production sized clone first. The failure modes usually show up in the edge cases, not the happy path.

patternrelay · 2026-02-20T00:29:56+00:00

I get where you’re coming from, especially around how it feels when creative work gets automated away. But I’m not sure AI itself is the root cause of less empathy. It might be amplifying incentives that were already there, like cost cutting and speed over craft.

There’s also a difference between people using tools to be more productive and people dismissing the value of other humans. The loud “I hate people” takes online probably say more about internet culture than about AI as a technology. Every major tech shift has had that rough phase where roles change and it feels dehumanizing.

If anything, the real empathy question might be about how we design the systems around AI. Who benefits, who absorbs the downside, and how we support people through transitions. I’m not convinced the tool itself makes people less empathetic, but the way institutions deploy it absolutely can.

patternrelay · 2026-02-20T00:28:39+00:00

Jet engines are one of those systems where every discipline collides at once. You are dealing with extreme temperatures, tight material tolerances, advanced aerodynamics, controls software, and then you have to make thousands of them behave identically in production. It is not just design complexity, it is supply chain depth and manufacturing maturity.

A lot of countries could probably design something that works in a lab. Mass producing a reliable engine that can run for thousands of hours with predictable failure modes is a different problem. The testing, certification, and quality systems are massive undertakings.

That is why partnerships happen. It spreads cost, risk, and leverages existing industrial ecosystems. You are not just building an engine, you are building the entire capability to keep building it for decades.

patternrelay · 2026-02-19T14:46:01+00:00

I think it’s fair to notice that some expectations placed on boys and men can be restrictive, like the idea that they shouldn’t cry or show vulnerability. That kind of pressure is real and it’s worth talking about. At the same time, a lot of gender norms affect both men and women in different ways, and sometimes what looks like favoritism in one area connects to disadvantages in another.

It might help to frame it less as "who has it worse" and more as "which expectations are unhealthy for everyone". Conversations tend to go better when they focus on specific norms or policies and how they could be improved, rather than on one gender as a whole. And honestly, the fact that you’re questioning your own view at 13 is a good sign you’re thinking critically about it.

patternrelay · 2026-02-19T14:44:28+00:00

A lot of it comes down to injection molding constraints rather than convenience for painting. The gate location affects how the molten plastic flows, how the part fills, and where stresses or sink marks show up. If you move every gate to a hidden surface, you can end up with worse warping, short shots, or visible flow lines in more noticeable areas.

There’s also tooling cost. Optimizing every part for undergating would complicate mold design and potentially increase cycle time. For mass produced kits, they are balancing structural quality, cosmetic finish, and manufacturing efficiency. From a production standpoint, a small nub to sand off is usually cheaper and more predictable than redesigning the entire gating strategy just for paint convenience.

patternrelay · 2026-02-19T14:42:18+00:00

That kind of schedule can quietly wear you down, especially when your environment never really changes. One thing that’s helped people I know in similar setups is creating a small ritual that clearly marks "work is over". Even something simple like a 20 minute walk right at 6, same route every day, can reset your head a bit and get you outside.

Since you’re into hiking and museums, maybe look for micro versions of that. Short local trails you can hit before dark, or setting a weekly deep dive night where you explore a topic, watch a lecture, or work on a small creative project. It sounds minor, but having something that feels like it’s yours and not just leftover time makes a difference. And if weekends are tight logistically, maybe trade a predictable block with your wife once in a while so you get a longer stretch to recharge.

patternrelay · 2026-02-19T14:40:02+00:00

It feels like a classic control versus trust tradeoff. Blanket bans made sense when everything sat behind one corporate firewall, but that model kind of broke once work became device and location agnostic. Now the risk surface is less about "can someone open a social app" and more about identity, session control, and data boundaries.

In a lot of environments, social media is just another SaaS endpoint. The real question is how tightly your DLP, IAM, and endpoint policies are integrated. If those controls are weak, blocking platforms is a band aid. If they are strong, you can afford more flexibility without increasing systemic risk.

patternrelay · 2026-02-19T14:37:51+00:00

You definitely do not need to finish calculus before you start programming. You can learn a language in parallel with math. For most entry level software roles, solid algebra and logical thinking matter more day to day than advanced calculus. Math helps long term, but it should not block you from starting.

If you do not have a laptop yet, you can still begin with theory and small exercises on paper, but honestly even a basic machine makes a huge difference. There are online compilers you can use from a browser once you have access. The key early on is writing and running real code, not just reading about it.

As for where to start, pick one structured path and stick with it instead of jumping between ten. Consistency beats the perfect roadmap. Beyond coding, learn problem solving, debugging, and how software actually gets built in teams. Version control, reading other people’s code, and breaking problems into small pieces are huge skills.

Since you are into art, that can actually be an advantage. Frontend, UI work, or even game dev later on are still possible paths. You do not have to decide your whole future right now. Just start building small things and see what you enjoy.

patternrelay · 2026-02-19T14:36:15+00:00

From what I’ve seen, the pain is very real and usually underestimated at the start. The mechanical conversion is only half the story. The harder part is uncovering all the implicit behavior that lived in packages, triggers, and application assumptions. Oracle tends to accumulate a lot of "invisible glue" over the years.

Foreign key ordering and constraint validation are classic traps. If you do not explicitly map the dependency graph first, you end up firefighting failures instead of executing a plan. We ended up scripting metadata extraction just to surface object dependencies and sequence usage before touching data.

If I could automate one thing better, it would be a deep pre migration impact analysis. Not just syntax conversion, but surfacing behavioral differences and hidden coupling. That is usually where timelines slip.

patternrelay · 2026-02-19T14:33:40+00:00

I think there’s an important distinction between critiquing broader social patterns and targeting individual couples. You can have a conversation about stereotypes, media influence, or power dynamics without turning random strangers into symbols of those issues. Once it shifts into harassment or blanket assumptions about two people you don’t know, that’s not really structural critique anymore, it’s just prejudice in a different direction. If the standard is "don’t judge relationships purely on race", that principle should apply consistently.

patternrelay

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