LOL, I can relate to this. My partner is the "The recipe expects me to fry this for exactly 7 minutes" type and I am "Yeah 400g or maybe 500g, it'd be awesome if I add ingredient X too".

We don't cook together well. The only way we enjoy it is if one gets to be the head chef and the other just follows instructions.

No no, I fully agree they are necessary, I'm just making a different point. My point is about weight, not necessity.

I also believe that EVs are necessary, and they're much heavier than ICE cars, because batteries are heavy. This comes with clear problems - for example, pedestrian safety. What annoys me the most is that because all in all EVs are a good thing (or better than the alternative), we've accepted that weight and nobody bats an eyelid at the idea of a 2-ton car when it's in fact an abomination.

Bikes are not cars, thankfully, but 15 kg is not a light bike. It's a light e-bike, but for it's within 1960s standards for what a light "bike" should be. And if you're a petite middle aged woman who carries her bike across 2 flights of stairs in the train station, being told that a 15-kg mountain bike is "light" is a bit of a middle finger.

I feel e-bikes are like electric cars and SUVs, so bloated that they're redefining what "light" means.

My cheap gravel bike from 2020 is 10 kg, and this one is 15. Is this "reasonably light for an e-bike"? Sure. Is this "so light that I won't believe it's electric"? Well, it's 50% heavier than a budget gravel bike from 7 years ago, so no way I could believe that.

Interestingly what I've said here ☝️ ️comes with an interesting implication. There used to be a type of software "engineer" that couldn't actually think through a problem and implement a good software solution. They were valuable because they could refactor, write code, but not think through a problem. These are the people who have the most to lose at the moment, and also the ones that find the least value on AI, because AI only does really well the single thing they could do.

I appreciate the intent behind that sentence, and the problem is that is written (or said) by people who don't understand coding.

Syntax was never the hard part. Code syntax is a set of rules that you can teach a machine and it's "easy" enough for an LLM to grasp it. The problem here is that this phrase does a "code = syntax" but ignoring all the difficult things that actually are in the code. Architecture, design, tradeoffs, translation of vague requirements into concrete software components...

All of those things are terribly hard, and the reason why many LLM-first coding projects get abandoned at 70% and then companies need to hire a Software Development consultancy to mop up their mess.

I'm an engineer. I've studied aerodynamics. I know how helicopters work. I know the blade is a wing that generates lift. I can even explain it all in detail.

Yet if we came across some alien antigravity technology and we started making antigravity aircraft, I'm sure that would make more sense to me than helicopters because what the hell. My brain just refuses to believe they can fly.

Are these any good? I mean, within their size class, obviously - not expecting them to compare to Kimi K3!

Models the size of that 135M one open up some interesting use cases for edge devices.

What they forgot to add: in the same time, they've also managed to create more bugs than they've fixed, thanks to AI.

Well, MacBook Pro or also Mac Studio. Pre shortage, you could spec out the Mac Studio with 512 GB of RAM, if you had stupidly deep pockets.

I know this, you know that I know this, you know that the OP knows this, and we all know this is not what they were talking about.

Are you perhaps a certain type of sea mammal?

Oh come on, you know what they meant. People might have voted for Labour, but not to have Burnham as PM. Nor Sunak, or Lettuce Lady.

Unfortunately AI doesn't work like that. Any way to explain it would be an oversimplification but I can try.

The training data (songs) are used to create the weights. This is a bunch of numbers that are on their own meaningless - they don't map to specific songs, but to attributes such as "tone" "rhythm"... And like that but many (millions of) abstract attributes that don't make sense as people, but make sense to computers.

So if the thing makes a song that is very "rhythmic" but also "tonal", there's no specific training song that contributed to that - all did, and it's a mess to decypher how much each contributed to each attribute. Except the resulting song doesn't use two parameters, uses many millions, so it's essentially impossible to know.