Damn, I forgot about the teaching aspect of programming. Must be hard. I can’t blame students for taking shortcuts when they’re almost assuredly swamped with other classwork and sleep-deprived, but still. This is where my defeatist comment comes in, because I genuinely think LLMs are here to stay. Like autocomplete, but dumber. Just gotta have students recognize when ChatGPT hallucinates solutions, I guess.

Look, ultimately the problem is the same as it has always been: juniors doing junior shit. There’s just more of it going on. If you’re hiring one, you put a senior on them ready to extinguish fires. A good review process is a must.

Now that I think about it, there was this one time the same young’un I was talking about tried to commit this insane subroutine that was basically resizing a vector in the most roundabout way imaginable. Probably would have worked, but you can also just use the resize method, y’know? In retrospect, that was probably some Copilot bullshit, but because we have a review process in place, it was never an issue.

I’m a little defeatist about it. I saw with my own 3 eyes how a junior asked ChatGPT how to insert something into an std::unordered_map. I tell them about cppreference. The little shit tells me “Sorry unc, ChatGPT is objectively more efficient”. I almost blew a fucking gasket, mainly cuz I’m not that god damn old. I don’t care how much you try to convince me that LLMs are efficient, there is no shot they are more efficient than opening a static page with all the info you would ever need. Not even considering energy efficiency. Utility aside, the damage we have dealt to developing minds is irreversible. We have convinced them that thought is optional. This is gonna bite us in the ass. Hard.

I’m just gonna shove the list here, cuz archive.is doesn’t play well with the fancy frontend that MIT has cooked up:

• Vera C. Rubin Observatory

A powerful new telescope will come online this year in a remote region of Chile and begin a decade-long survey of the southern sky. Inside is the largest digital camera ever made for astronomy, which will snap photos continuously for years to help astronomers study dark matter, explore the Milky Way, and untangle other cosmic unknowns.

• Generative AI search

Generative search promises to make finding what you’re looking for simple and quick. When you type in a query, an AI model summarizes information from many online sources to return a unique answer. On your device, it can comb through documents, photos, and videos, recognizing objects and people to help you find them faster. This may signal the end of traditional search engines and the rise of personal AI assistants.

• Small language models

Large language models can do amazing things because they’re crammed with hundreds of billions—even trillions—of parameters (the values that determine their behavior) and were trained on most of the internet’s data. But cheaper and less power-hungry small language models can now stand with the heavyweights across a range of specific tasks. Move over dinosaurs. The future belongs to smaller, nimbler beasts.

• Cattle burping remedies

Cow burps are one of the largest sources of agricultural emissions—and one of the trickiest ones to solve. A food supplement that significantly reduces the amount of methane that cattle belch is now available in dozens of countries. Other products, which might prove even more effective, are likely on the way.

• Robotaxis

Robotaxis have completed years of beta testing, and they are now finally becoming available to the public. In more than a dozen cities worldwide, riders can summon one whenever they want. Now, the biggest players are ramping up for intense competition as they expand into new cities under regulators’ watchful eyes.

• Cleaner jet fuel

New fuels made from used cooking oil, industrial waste, or even gasses in the air could help power planes without fossil fuels. These alternative jet fuels have been in development for years, but now they’re becoming a big business, with factories springing up to produce them and new government mandates requiring their use. Why it matters

• Fast-learning robots

Thanks to today’s generative AI boom, robots are now learning new tasks faster than ever. Today’s automatons are not one-trick ponies—we’re getting closer to general-purpose robots that could be dropped into new environments and tackle a variety of tasks on our behalf, almost instantly.

• Long-acting HIV prevention meds

A trial of a new HIV prevention medicine found that 100% of treated women and girls were protected from acquiring HIV infections. And it only needs to be injected once every six months. The drug could help us end AIDS once and for all—if we can ensure access for those who need it.

• Green steel

Making steel is one of the largest industrial sources of carbon dioxide, emitting more carbon than all of India (the world’s third largest emitter) and far more than air travel. The first industrial green-steel plant, which uses hydrogen made with renewable power, is being built by Stegra, a $7 billion startup that is scheduled to begin operations next year in northern Sweden.

• Stem-cell therapies that work

Stem cells from human embryos will cure disease. That’s the big promise scientists made decades ago. And now it’s finally coming true. Experimental transplants of lab-made cells seem to be helping treat two very different conditions—epilepsy and type 1 diabetes. Why it matters

Ye ye fair enough. My point is that LLMs can double bluff if need be and in the end the only thing we’ll have to identify them by is trying to like stress-test their tokenization.

I see through your ruse BrundleFly, if that even is your god-given Christian name. You clearly wrote written by ChatGPT at the end so that I may think that you are, in fact, an organism. The ol’ double-bluff eh? Get the fuck outta here! Do you know who you’re talking to? Do you know how many captchas I’ve passed? I’m a real god damn human being and that’s final!

Wait…

Obviously I don’t know what Reddit is. Sounds like a Lemmy alternative. But if anyone here finds out what Reddit is, go check out any subreddit where you’re supposed to just write stuff. r/AITAH, r/stories, r/AmIOverreacting. More bots than a TF2 practice match. Every post follows the exact same narrative structure. Dumb shit like “My dad killed my chihuahua, cooked it and fed it to my other chihuahua, so I’m not going to the family get-together. AITAH?” It’s genuinely shocking to me how comments don’t realize it. Maybe they’re LLMs as well, hence why they don’t say anything. Some of the mods might be LLMs too, considering they don’t do anything about it. Am I the only one who’s not an LLM? Am I just talking to myself at this point? Wait, am I also an LLM? What’s happening? Why have we made robots whose only job is to dilute reality?

I’ll be honest, I’m just hoping this AI shit calms down. Every 5-6 new papers published in the Journal of Computer Science is some AI slop. Like we get it, it’s fun filling a big ass matrix with weights which then inadvertently solve a problem you have. Could I please have some novel research that probably won’t go anywhere anytime soon but is kind of fun to think about and tinker with?