My most played Steam game is Dishonored, at 127 hours. I have replayed it a lot. A rarity for me, but I really liked that game. Dishonored came out in 2012. It’s taken me 12 years to accumulate that many hours.

Balatro came out two months ago.

I have 93 hours in it.

I used to work summers as an apprentice electrician. The amount of crazy wiring I saw in old houses was (heh) shocking. Sometimes it was just that it was old. Real old houses sometimes just had bare wire wrapped in silk. … And a few decades later that silk was frayed and crumbling in the walls and needed replacing.

My current house was wired at a time when copper was more precious, so it was wired up and down through the house, with circuits arranged by proximity, not necessarily logic. When a certain circuit in my house blows the breaker, my TV, PC and one wall of the master bedroom all lose power. The TV and PC are not in the same room either.

Just saying.

… Saying what, exactly?

I said that we should

• design for change
• “within reason”
• because we can’t know what exact changes are needed.

And you argued… The same thing? Just in the reverse order?

Have you ever been in an old house? Not old, like, on the Historic Register, well-preserved, rich bastard “old house”. Just a house that has been around awhile. A place that has seen a lot of living.

You’ll find light switches that don’t connect to anything; artwork hiding holes in the walls; sometimes walls have been added or removed and the floors no longer match.

Any construction that gets used, must change as needs change. Be it a house or a city or a program, these evolutions of need inevitably introduce complexity and flaws that are large enough to annoy, but small enough to ignore. Over time those issues accumulate until they reach a crisis point. Houses get remodeled or torn down, cities build or remove highways, and programs get refactored or replaced.

You can and should design for change, within reason, because all successful programs will need to change in ways you cannot predict. But the fact that a system eventually becomes complex and flawed is not due to engineering failures - it is inherent in the nature of changing systems.

… And can you fix it?

That sounds amazing - OMW to check it out!

Oh, for sure. I focused on ML in college. My first job was actually coding self-driving vehicles for open-pit copper mining operations! (I taught gigantic earth tillers to execute 3-point turns.)

I’m not in that space anymore, but I do get how LLMs work. Philosophically, I’m inclined to believe that the statistical model encoded in an LLM does model a sort of intelligence. Certainly not consciousness - LLMs don’t have any mechanism I’d accept as agency or any sort of internal “mind” state. But I also think that the common description of “supercharged autocorrect” is overreductive. Useful as rhetorical counter to the hype cycle, but just as misleading in its own way.

I’ve been playing with chatbots of varying complexity since the 1990s. LLMs are frankly a quantum leap forward. Even GPT-2 was pretty much useless compared to modern models.

All that said… All these models are trained on the best - but mostly worst - data the world has to offer… And if you average a handful of textbooks with an internet-full of self-confident blowhards (like me) - it’s not too surprising that today’s LLMs are all… kinda mid compared to an actual human.

But if you compare the performance of an LLM to the state of the art in natural language comprehension and response… It’s not even close. Going from a suite of single-focus programs, each using keyword recognition and word stem-based parsing to guess what the user wants (Try asking Alexa to “Play ‘Records’ by Weezer” sometime - it can’t because of the keyword collision), to a single program that can respond intelligibly to pretty much any statement, with a limited - but nonzero - chance of getting things right…

This tech is raw and not really production ready, but I’m using a few LLMs in different contexts as assistants… And they work great.

Even though LLMs are not a good replacement for actual human skill - they’re fucking awesome. 😅

What I think is amazing about LLMs is that they are smart enough to be tricked. You can’t talk your way around a password prompt. You either know the password or you don’t.

But LLMs have enough of something intelligence-like that a moderately clever human can talk them into doing pretty much anything.

That’s a wild advancement in artificial intelligence. Something that a human can trick, with nothing more than natural language!

Now… Whether you ought to hand control of your platform over to a mathematical average of internet dialog… That’s another question.

In order to add their names to your dictionary. You don’t have to allow it. But given that there’s no internet access for the keyboard - it seems pretty safe

Kotlin is Java with all the suck taken out.

It’s a modern, ergonomic language that runs on the JVM and removes as much GD boilerplate as it can.

It’s fantastic.

Google: It’s a three-pronged attack: sub-liminal, liminal and super-liminal.

Lisa: Superliminal?

Google: I’ll show you. (leans out of window) Hey, you! Code in Golang!

Carl: Uh, yeah, all right. Lenny: I’m in.

Yeah. Some basic tables showing how a json object would be encoded in CBOR would go a long way.

RFCs make for dry reading.

Compilers are a specialized topic - and syntax design is fiddly - but it really is no harder than any other sort of program. A lot of the hard theoretical work was done back in the sixties and seventies. You don’t have to start from scratch. These days it’s “only” a matter of implementing the features you want and making sure your syntax doesn’t leave itself open to multiple interpretations. (just as arithmetic, e.g. ‘5 × 4 - 1’ requires some rules to make sure there’s only one correct interpretation, so do language syntaxes need to be unambiguous to parse. )

Don’t get me wrong - writing a language is a lot of work and it’s super cool that OP has done this! I just want to stress that language development is 100% doable with an undergrad degree. If you understand recursion and how to parse a string you already have all the theory you need to get started.