> Just today, I spent an hour documenting a function that performs a set of complex scientific simulations. Defined the function input structure, the outputs, and put a bunch of references in the body to function calls it would use.
So that's... math. A very well defined problem, defined very well. Any decent programmer should be able to produce working software from that, and it's great that ChatGPT was able to help you get it done much faster than you could have done it yourself. That's also the kind of project that's very well suited for unit testing, because again: math. Functions with well defined inputs, outputs, and no side-effects.
Only a tiny subset of software development projects are like that though.
> Only a tiny subset of software development projects are like that though.
Right: the majority of software development is things like "build a REST API for these three database tables" or "build a contact form with these four fields" or "write unit tests for this new function" or "update my YAML CI configuration to run this extra command".
I have a much more close relation with other niches than with web programming, even if web programming is part of my core skill set. I mostly interact with a few sites daily, even though I spend some time there. But I spend a lot of time with software like xterm, emacs, calibre, cmus,... and more with tooling like make, bash. While I'm not working on those, I had to become quite familiar with their working to troubleshoot some bug. Emacs is more important to me than AWS and GitHub.
Niche as in for every one systems programmer there are dozens of people writing API Glue.
By hours of work spent and lines of code produced the latter is in a whole different scale than systems programmers (which is a very badly designed term anyway).
I've never been worried about LLMs. I've always been worried about how people will use LLMs and how they will interpret the output of LLMs. Especially people who don't understand what LLMs are doing.
Why is this concern more important the what people interpret from the media, social media and the dissemination of information in general where lies and fabrications are also commonplace? Like surely people will always fall for nonsense, lies or fabrications and there is nothing that can be done about that.
As with all these discussions: accountability and consequence.
We can point at a media company, call out its vested interests, scream about its bias, protest in front of its office, sue it for slander and misrepresentation. We can call out individual personalities the same way. We can strive to drive the companies out of business and the personalities out of work, if we deem it necessary, and we can accumulate a paper trail that holds each one to account.
As neither individuals nor corporate entities, algorithms do not yet carry this kind of legal or public accountability even as we some start to hold them up as oracles. In most cases, failures of an algorithm are treated simply as bugs or user mistakes. Nobody is responsible for anything bad and the so the algorithm can persist and its vendor can shrug off their own responsibility by gesturing towards an perpetual development process instead of accepting consequence: "we work to make the algorithm better every day, try again tomorrow!"
>We can point at a media company, call out its vested interests, scream about its bias, protest in front of its office, sue it for slander and misrepresentation.
Right but the previous election had Russian servers spinning up fake news websites that displayed straight up generated news. Again how do you hold them accountable? You can't the only defence against bullshit is independent thinking.
Because LLMs strip away all the context surrounding the information it spits out that let you evaluate its trustworthiness. They're incredibly useful tools, I use them constantly when coding but I can do that because I know enough to validate the information and it happens that the cost of validating the output with the docs is shorter than reading them to find the relevant functions.
I wouldn't dare try to use an LLM for a chemistry question because I wouldn't be able to tell if it makes any sense or not. But if you're not a "tech person" and all you see is some company advertising their AIs as magical knowledge engines with disclaimer text that wouldn't pass accessibility tests, why wouldn't you assume they know their stuff? The Perplexity ads are bordering on negligent.
The difference is that web/social media is branded as an intelligent being you can ask any question of. We all agree the web is _also_ not reliable, but many people will think GPT / Gemini are verifiably accurate when they aren’t.
I've found that people in general seem to trust computers more than humans, which made sort of sense for a while.
What they don't fully realize is that this is a completely different game; now the computer is just guessing, as opposed to following a deterministic algorithm to the answer.
And this misunderstanding carries the potential for pretty serious consequences, good luck getting that loan once a computer finds some arbitrary pattern and says no.
If only it would tell you "You've criticized the war effort that day in 2004", in stead it will do parallel construction. The end game will be a kind of SEO for human profiles and we will live happily ever after by the best practice guide lines.
I've always been worried about how people will use LLMs and how they will interpret the output of LLMs. Especially people who don't understand what LLMs are doing.
The problem isn't the people. It's the tech companies.
The tech companies are telling people that it's intelligent, and the tech companies are using it to answer people's questions as if they're presenting facts.
People are using it the way they're told.
If you advertise something as a solution, don't be surprised when people use it to solve things.
I understands what you're trying to replicate, but I believe this would distract from the charm since users could then just visit YouTube [directly] and search for things scheduled.
The randomness and uninterrupted playback is why this is so cool =D
I really like how there are only 12 channels, and you don't get to choose what's on. The only way to make it even more like tv from a few decades ago would be if half of the channels were static.
For real accuracy of tv of a few decades ago they could add a 13th channel that takes content from Pornhub, but then adds a bunch of filters so you can barely see anything.
Integrate a Kinect / Realsense camera that estimates your body pose, so you have to stand in front of the computer and hold your arms in a specific way to direct a weak signal into the rabbit-ears...
if we're talking about stuff to make it more authentic, how about looking up my local weather if there's a strong storm the quality drops + more static, and a small
(rng) chance of it completely breaking if the antenna upstairs got completely broken by the strong wind.
Given how full of crap content and intrusive ads YouTube is these days, I actually kinda miss tv from back then. About the only benefits at this point are time shifting and pause/rewind.
I've long since concluded that YouTube's ads are merely a way of persuading me to upgrade to Premium. Given that they actually seem to be pretty good at recommending content to me I am mystified by why the ad selection is so awful.
1. If the ad selection is too good, people will fall into the uncanny valley. They have to make it terrible enough to maintain user confidence.
2, They may not have anything better to select from. Quickly start/stop the ads a few times and it will usually (but not always) give up on showing any ad at all, which suggests to me that the available ad pool at that point in time is being exhausted.
But doesn't it make sense to pay for targeted political ads towards people opposed to you? The algorithm allows advertisers to do targeted advertising, and you were targeted, the subtle implication that targeted advertising would only show you "what you want to see" was intentional and misleading to get people on board with their attention being sold to the highest bidder.
With real TV and a DVR you haven't had to see a single commercial in the last 25 years if you didn't want to.
We don't talk enough about how streaming has forced us into a much worse experience with ads that are unskippable, privacy-invading, and now I hear they're being dynamically inserted into programming mid-scene.
We talked about it plenty back when the legacy media companies were refusing to move online. "The ad spend isn't nearly a high online." they would say, with "Yeah, but people actually watch the ads online. Give it a few minutes." in response.
It's still trivial to block these though with a combination of uBlock Origin and Sponsorblock. Despite Google's ongoing efforts to make this impossible.
have you forgotten how bad commercials were back then, and still are?
I haven't watched TV in years and years and years, because of the ads. I have a YouTube premium subscription and I am not ever going to watch broadcast or cable tv again. ever.
By “bad” I mean “commercials exist and are shown on TV”.
I don’t ever want to see a commercial. I have never been influenced by one. I never will be unless they change dramatically. There is no sales pitch that does not immediately make me dislike the salesperson.
“You don’t deserve your money as much as I do.” That’s all a commercial is. “We want your money so here is some quick audio and maybe video designed to convince you to give your money to us, in exchange for something less valuable than the amount you paid.”
T1 and T2 are completely different diseases. T2 should not be called diabetes. It should be called insulin resistance or chronic carbohydrate overdose.
I was diagnosed as pre-diabetic/T2. I started wearing a cgm and watching how various foods affected my blood sugar. I eliminated foods that caused spikes, and started cooking my own meals so I could control what went into them. I wound up with a very low carb diet of meat and vegetables, and a very stable blood sugar with NO spikes ever. According to my blood work and checkups I cured my NAFLD, cured my hypertension (including getting off drugs for that), and "cured" my pre-diabetes. I lost a lot of weight, but still have a lot more to lose.
I put cured in quotes because I don't think this diet can cure you once you're bad enough to need treatment. I think it can only put your disease into remission so that you don't suffer any health effects from it. Some of us just can't overeat carbs or we develop this disease, and the only effective treatment is to stop eating the carbs.
Optimizing the electron transport chain via supplements like CoQ10 (Ubiquinol more bioavailable), Benfotiamine (b1 form), Nicotinamide Riboside (b3 form) are extremely helpful.
That's the reason why metformin works so well for diabetes, and has longevity extension effects, because of how it stimulates the AMPK pathway, which is also anti-inflammatory (thus lowering oxidative stress).
We can reframe a TON of chronic conditions under the umbrella of mitochondrial dysfunction, whether it's ME/CFS, T2 diabetes, anxiety, depression, and addressing the mitochondrial dysfunction tends to be extremely helpful, if not able to bring the conditions into remission.
The problem though is that addressing mitochondrial dysfunction requires a multi-pronged approach with a lot of disruptive lifestyle interventions, which makes the activation cost for such things a hump that the average person will not be able to get over unless they have enough privilege to do so.
Please share more. This is the first time I heard of mitochondrial dysfunction. The more I read and research, the more I see this type of pattern: A host of similar diseases claimed to be caused by a very fundamental process in the body, which is only malfunctioning due to the modern lifestyle. Many of those stuff are backed by research.
Your body doesn't prefer glucose over fat. Too much glucose is toxic, so your body will focus on reducing it first. Too little is also dangerous so your body will make some from protein if necessary. But only as much as it needs.
Fat adaptation is about shifting your hormonal balance and response to retrain your body to maintain a lower level of glucose, and to retrain your cravings and hunger.
I'm not talking at the higher organism level, I'm talking at the very low-level chemistry in mitochondria. Glucose is "easier" to produce energy out of and so that happens preferentially from a chemistry perspective. Your body also needs a minimum level of glucose to survive.
When there isn't enough glycogen, the chemical balances in the mitochondria change and the liver mitochondria will produce glucose from whatever they have. This isn't a "decision" just the relative amounts of the chemicals change leading to one chemical pathway becoming more likely compared to another. This is all mediated by the random collisions of molecules in your cells. If you have a lot less of one molecule compared to another, the frequency that molecules find each other to do one thing v/s the other will change leading to different chemical pathways becoming more or less active.
There are many routes for your body to produce glucose. It is "easier" for your body to produce it from gluconegenic amino acids (not all amino acids can be used to produce glucose) than it is from fatty acids. It's the process of converting fatty acids into glucose that generates ketones. So when you have excess amino acids that can be turned into glucose, the chemistry will prefer this pathway over breaking down fat into glucose and this will lead to lower ketone production overall and kick you out of ketosis.
(I think I've gotten the gist of this right but any biochem experts feel free to correct me)
Gmail was invite-only to join and get an @gmail.com account, but once you had it you could interact with any email account user, and they could interact with you. GMail isn't a walled garden. Facebook, Wave, G+, etc are. That's why they depend on rapid user growth very early on when the hype is fresh.
I think the problem is economics. Electric charging stations already have less ability to service as many customers per hour as gas stations. Requiring that they also provide a heated building for the cars to charge in would make it even more expensive. The upcharge for such costs would make the power more expensive and the business less competitive.
So that's... math. A very well defined problem, defined very well. Any decent programmer should be able to produce working software from that, and it's great that ChatGPT was able to help you get it done much faster than you could have done it yourself. That's also the kind of project that's very well suited for unit testing, because again: math. Functions with well defined inputs, outputs, and no side-effects.
Only a tiny subset of software development projects are like that though.