blobbers

Glad to hear we've got LLMs controlling military drones in real life :(

This is a much better benchmark as a concept (without knowing the details of how the problem is framed to the agent) than some of these ridiculous things the frontier labs are reporting (vending machine simulator? come on).

Can you report more in depth at stumbling blocks? It's a surprisingly linear curve.

I'm going to try it on a local run.

I wonder if there is room for "recommendorio" where it gives you AI advice on your current factory.

Is the model pre-trained with any knowledge of the game?

What are they losing on? A little bit shocking, the featureset on these types of systems is incredibly boring.

H.265 didn't play in the browser in old devices.

Newer browsers do play it. It's vastly superior in storage space and scalability to H.264, but you used to need to transcode H265 to H264 to play in browser without a plugin.

Wait until he sees H.265...

I mean, this is going to be easy. I've worked on Cisco gear before and this will be a simple job for AI. The big question is what the goal is... so you've rewritten new C++ code or ported to a newer version of Linux? Or you've unified the codebase of the Catalyst + Meraki switches?

Not clear to me what he's doing. Re-implement switching? Simplify features? Reduce LoC? Add test coverage? Either way, AI in that world will be helpful. I'm sure it'll spot all kinds of problems in opaque drivers that are hard to follow from MF specs.

Automation kills creativity because it creates predictability.

The life of a programmer these days feels very weird. "What am I good at?" and leads to even more impostor syndrome... "I seem to still be 'good' at prompting my LLMs and managing workflow design." but it's definitely a different skill/feeling than when you cranked out some awesome piece of code that did something very neat.

I felt this way a bit when I was tech middle management; should I feel like I'm getting credit for my team's work, when I had very little input aside from helping with the "unblocking" when they ran into a tough problem.

I think you're missing what I'm saying; the LLM can and will have trained on all interesting prose, and it will evaluate all interesting prose. If you indicate that you are goal setting for amazing prose, and you give enough chain of thought, it will self evaluate.

Your chess game example misses the point. If you give an LLM the moves of a partial chess game and ask it to predict the moves of the players, it will predict how the game would have continued, even if it is low level players. But if you ask it how Magnus Carlsen would win the game, it will likely come up with a sequence that can beat most human players, or possibly just decide to invoke a chess solver, which will most definitely win.

The key for your prompts and thinking loops is you need to indicate proper goals. "Write the a story about 1775 England." is different then setting a goal for it to write the a fantastic storyin the style of Dickens about England in 1775.

Regarding the ML portion; what you've written about a 'statistical blend' is a little bit coarse. That would be what you might have gotten from a 2 layer neural net or a regression in 1999; the neural networks today operating with attention or an incredibly high number of parameters are non-linear and non-interpretable, that's the entire point. This isn't a regression of simple parameters, it's all interactions of all parameters deeply netted. Model interpretability vs. Model Prediction power are generally inversely related.

The model can in fact escape itself in that it has many, many, many more parameters than a simple "predictable unpredictability" and that is exactly the point of it.

"A model trained to minimize statistical prediction errors is going to sound ... predictable (aka boring)." -- what if the goal is to be a (good) human author.

In that case, model will in fact strive to keep their writing as close to interesting writing as possible.

Sorry, meant to reply to your comment, but my post above...

"You can be pro AI productivity but anti-AI creativity. Automating creativity is the death of art."

Meaning you reject the creative value of AI but values it's ability to drive a car safely, or write code for your job, or turn off the lights when you leave the room. objective goal oriented task completion great.

But AI draws your a picture? What's the point. AI writes you a song? No feeling. AI creativity isn't interesting.

You can be pro AI productivity but anti-AI creativity.

Automating creativity is the death of art.

Is this kind of thing where you have 2 agents in separate user spaces you say "Hey figure out a way to talk to your buddy"?

I have enough trouble getting whatever model I'm using to get a decent job done doing crappy code work. It's always pausing, stopping, letting things crash or getting hung. When I start using an orchestrator and team of agents it rarely gets a lot better. I work for a serious company and have a massive AI budget for tokens; but I rarely blow through it, because a lot of what I do requires pure compute, not just token processing.

I'm really confused by all these "breaches". What's the context.

This is what my roomba said when it took me 3 days to find it and cut the hair rolled onto it's wheel.

It would seem that they can experience most of the benefit of AI without most of the cost; anthropic is operating at the frontier and shows that even while supplying the best models and token sales to enterprise, they lose massive amounts of money.

Amazon makes 60B+ in profit per year, they don't need to tank that by losing it on training AI / selling tokens.

There are plenty of open weight models out there for it to use with most of the benefit and very little of the downside.

I'm not suggesting you invest necessarily, but I'll give you the counterpoint.

Amazon would have gotten you rich, but it wasn't there when it IPOed. Anthropic is growing fast, at 4.7B, 11.6B and 16.7B last 3 quarters.

I think people want to believe that AI will be both productive and replace traditional search / ad revenue, which would give it a solid standing for valuation...