svachalek

Often it's taken out of context by pop sci channels to propose the universe "could be" or even "is" in a black hole. But from my understanding, as a non-physicist, it's not surprising or interesting to most physicists that the math works out like this, and there's nothing else to suggest that we're in a black hole.

It's kind of crazy to think about. But silk is probably even crazier.

Same. Usually found next to the wax soda bottles. Even as a kid I thought they were objectively terrible as candy went (like a pretzel stick coated in sugar) but there was something cool and grown up about puffing a fake cigarette at age six.

Maybe you shouldn't take the "you" of this article personally, but as a reference to your 100 mouth breathing neighbors. Do you think the average person who spends their evening reposting troll memes and watching Tiktok videos is now using AI to enhance their understanding of the world?

To be fair we've already had decades of advancements that allow society to more than ever avoid expending any effort on actual thought, but I can only see AI continuing and expanding the trend, not reversing it.

Yeah there's even an "Agent SDK" from Anthropic that manages Claude CLI sessions for you, and a separate token budget for apps that use it, on top of the subscription tokens.

Thinking about a scary moment can make your pulse race, your eyes dilate, and cause you to sweat. Thinking about a lover can do all that and other things. So clearly the imagination can affect the body. Not saying this study will hold up necessarily, but it's not that far fetched.

I've been thinking recently, there's hardly any reason not to use a native language like Rust anymore. The classic reasoning for languages like Python is that it prioritizes developer time and resources over compute resources, but now developer time is rapidly trending to zero and everything is compute dominated.

It's not really all that fast, for most things it's full seconds or at least a significant portion of a second. As computing goes that's quite slow and there are many things that require much faster speeds than this. However compared to the typical LLM it's quite speedy and opens some new doors for real-time-ish scenarios.

Oh /loop was the crowning achievement. Basically guarantees you'll run a prompt at max context without caching over and over.

My problem isn't that it can identify such conditions, the record on cybersecurity lately shows these things are quite good at finding real faults. But the annoyance is that they always want to fix it by adding more things that open cracks. It's possible, sort of, to drive it to fix by removing things instead but it's a battle.

The sad thing is I think it's like Elara, it's just a favorite LLM name for things and there's likely not a human behind it.

I think these are cheap and easy toy models to toss out for the big labs, to see what they can do with limited inference resources. I'm not sure what the plan is for a company like LFM that seems to be doing this as an entire business plan.

I see it as a niche now but it will hopefully grow in the future. The amount of information these servers are collecting about you for potential use against you is staggering and makes adware spy tech look like the good old days of privacy.

Strongest and easiest use case now would be just to hook one of these up to a search engine tool and ask your random questions to it rather than adding to OpenAI or Gemini's database about you.

I think the use case for this sort of model would be building something like Google or Apple's agents on device. Find an email for me, write a message for me, add an appointment to my calendar etc. Simple agentic stuff, not writing apps.

And when you do find people out, they're wearing headphones and/or their nose is in a screen, and if you try to talk to them they look startled and annoyed like how dare you speak to me in a public place. The culture is just gone.

I agree. The latest models are getting quite good at validation, as long as they are clear on what the requirements are. Recently I got frustrated that while we have a huge test suite I noticed the LLM was hardly ever breaking a test with its changes (PRs only added tests, never changed old ones) which seemed suspicious.

I had it do a full audit. There were about 100k lines of tests, of which it determined about 60k were near useless. Many were overly mocked, some mocked to the point that they really weren't testing anything at all. It deleted those and wrote more expansive scenario tests to replace them, caught a lot of bugs on the way and fixed those too. Total time was about 2 hours.

I think humans need to review requirements, specifications, and test scenarios. And for some industries and uses they're still going to have to review every detail. But for a typical CRUD app, I think we're at a point where we can already set the process and quality bar higher than ever, in addition to moving faster.