starlust2

One could theoretically use a prompt injection attack to exploit a privilege escalation vulnerability on the kernel.

Fixing the hole is easy. Few more steps than you described, but still easy. Texturing less so.

The joke about someone using chatGPT to write a lengthy email that the recipient will summarize with ChatGPT is the perfect example of how pretend much work is.

We also need that for brightness. The brightness on Amazon Prime TV ads is painful. I literally hide under a blanket until they are done.

Even if you're married, you might not be married forever, could be in an open relationship, or a partner may cheat. None of which is the pharmacist's business.

Maybe not immediately but gathering the data on those areas will eventually lead to their ability to drive there.

Sounds like it's a person actively monitoring but not driving. The point is minimizing risk until safety can be proven.

It's not that they can't build a mental model, it's that they don't attempt to build one. LLMs jump straight from text to code with little to no time spent trying to architect the system.

> through brute force

The same is true of humanity in aggregate. We attribute discoveries to an individual or group of researchers but to claim humans are efficient at novel research is a form of survivorship bias. We ignore the numerous researchers who failed to achieve the same discoveries.

A thing people miss is that there are many different right ways to solve a problem. A legacy system might need the compatibility or it might be a greenfield. If you leave a technical requirement out of the prompt you are letting the LLM decide. Maybe that will agree with your nuanced view of things, but maybe not.

We're not yet at a point where LLM coders will learn all your idiosyncrasies automatically, but those feedback loops are well within our technical ability. LLM's are roughly a knowledgeable but naïve junior dev; you must train them!

Hint: add that requirement to your system/app prompt and be done with it.

Well I'm certainly not saying that AI should generate more corporate spam. That's part of them problem! And also a strawman argument!

A big challenge is that programmers all have unique ever changing personal style and vision that they've never had to communicate before. As well they generally "bikeshed" and add undefined unrequested requirements, because you know someday we might need to support 10000x more users than we have. This is all well and good when the programmer implements something themselves but falls apart when it must be communicated to an LLM. Most projects/systems/orgs don't have the necessary level of detail in their documentation, documentation is fragmented across git/jira/confluence/etc/etc/etc., and it's a hodge podge of technologies without a semblance of consistency.

I think we'll find that over the next few years the first really big win will be AI tearing down the mountain of tech & documentation debt. Bringing efficiency to corporate knowledge is likely a key element to AI working within them.

Wouldn't the fact that another group researched ABCA1 validate that the assistant did find a reasonable topic to research?

Ultimately we want effective treatments but the goal of the assistant isn't to perfectly predict solutions. Rather it's to reduce the overall cost and time to a solution through automation.

The thing with vague requirements is that the real problem is that making decisions is hard. There are always tradeoffs and consequences. Rarely is there a truly clear and objective decision. In the end either you or the LLM are guessing what the best option is.

I'm not sure about that but in that scenario polar regions would be 75-85F and life would be very harsh just about everywhere else. The one period in time where temperatures were that high, the Paleocene–Eocene Thermal Maximum, diversity plummeted, mammals were smaller and migrated to higher latitudes.

If climate change reaches the tipping point where clouds cannot form then we probably won't be seeing much rain anywhere.

> Maybe in the not-too-distant future we will have AI grokking large code bases and cranking out accurate, useful, UML diagrams out of it.

> All those diagrams, when they are complete, correct and up-to-date, do convey what they are supposed to convey.

I spent a bit of time prototyping this recently. It's definitely possible. Rational Rose also had the capability to generate diagrams from code though. I don't remember how good it was at the task though. Was Rational Rose just a very bad implementation?

I find the hate in this chat strange because diagrams are incredibly useful when working through complex problems* and then conveying that information to other engineers. My experience over 20+ years is that a huge portion of engineers can't grok complex problems from code alone.

*Most of my projects are optimizing billion+ row databases, micro-service architectures, and various other scaling challenges.

If you get to use a tool, then so does the LLM.

You're focusing too much on what the LLM can handle internally. No LLMs aren't good at math, but they understand mathematic concepts and can use a program or tool to perform calculations.

Your argument is the equivalent of saying humans can't do math because they rely on calculators.

In the end what matters is whether the problem is solved, not how it is solved.

(assuming that the how has reasonable costs)

I've noticed a big trend by commercial entities claiming to be "Open Source" but actually charging for licenses. Just because your code is in a public repo on github doesn't mean it's open source. If it's not an open source license it's not open.

This is especially true of AI projects.

Usually when a company is moving from PTO to DTO they are just trying to get the liability off the books. Management knows that most employees, especially new hires, don't take all of their days. It does nothing to help employees but that is how it is pitched.

If employees were actually utilizing unlimited DTO the company would switch back to accrued PTO. I've seen this happen with an explicit claim that employees were "abusing" the generosity of the company. Said company later switched back to DTO to force employees a few years later to burn down their accrued PTO balances.

> As a manager in a company, I've both had friends in HR and also had HR been my friend. Need to fire that horrible employee who is demoralizing the team and not being productive? HR is your friend. Need to hire the next best engineer? HR is my friend.

That's not a friend, that's a co-worker doing their job. There's a big difference between a friend and someone you get a long with well in a professional setting.

EV production volume is mostly limited by battery production. Manufacturers have been ramping that up so EV production should follow.

They are on a pole on your roof or you moved them to the ground?

> Lots of home appliances generate lots of heat (clothes driers, ovens, refrigerators, ...) that is currently vented to the atmosphere. it'd love to capture that and use it to "charge" the hot battery.

I've seen systems that use waste heat from central A/C to heat a swimming pool. In addition to the condenser they have a heat exchanger connected to the coolant line. Pool water is pumped through the heat exchanger and back out to the pool.

What you do is have your sister to re-write your posts and you re-write hers. No one will suspect you two are plotting to bring about the first Hegemon.

The point of reducing moderation is to allow the bad actors back in. Musk has been very vocal about supporting all speech regardless of impact.

I've wondered whether you could pump heat from a solar panel into a swimming pool.

I've seen systems where heat from A/C is used to heat swimming pools. Mostly just needs an extra exchanger on the A/C coolant line that transfers the heat to the pool water. You generally run both system at the same time when it's hot out. (assuming you are fortunate enough to have a pool)

Invisiline are actually 3D printed. Formlabs markets a printer for dental usecases. As long as your models and movement calculations are correct they'll work the same, but probably not an easy task.

https://dental.formlabs.com/materials/

An algorithmic question is a coding problem that focuses on problem solving, and may include questions/constraints related to time & space optimization.

The test should never rely on rote learning (e.g. implement Dijkstra's algorithm from memory) or require a "magic" solution (e.g. Project Euler)