latchkey

That theoretically could be within reason!

I know, right!

zwift is excellent, but i don't want to pay for it and i prefer to watch youtube's, instead of myself riding around in a cartoon world.

They were public 2 years ago?

useful to whom? ai loves it.

I asked it to keep track of features as it implemented them. It isn't meant to be read by humans.

You go to the website, you connect your trainer, you ride your bike and you get healthy.

wtf do you care about a readme for? =)

In early May, I broke my leg. Doctor eventually said get on a bike trainer and recover. So, I bought a trainer, didn't like the software that came with it, "wrote" my own with AI. Since it is just written with AI, I made it open source and free for everyone. I'm now months ahead of scheduled recovery. I'd call that a success.

https://github.com/RideControlOrg/RideControl

> Maybe it's just me, but nothing has changed in my life so far.

Manifest whatever you want!

The problem with the pivot is that with only 44GB of memory, you can't run models unless you nerf them or you scale the hardware out horizontally, which takes up a lot of space, power and even more cost.

This is why their API has dumb limits on it. I'd estimate their $/tok cost around $4-5000/mtok based on hardware alone, which is insane. Sure, it is fast, but if it is heavily quanted, expensive, and can't scale, you're going to be in a world of pain.

just get a bc-250...

lemonade stands are staffed by 11 year olds and there can be one on every corner.

these stands do better than cerebras, which is an 11 year old deeply unprofitable company building a technology that no other company has bothered to try to even get close to replicating.

This is what I put into google: "cfo of cerebras bird"

It came back with Bob Komin.

> they have more options than non-wafer-scale solutions, the chips are going 3d and meanwhile they benefit from the same interconnect progress as the wholly memory-bound alternatives

I hear that CS-420 will be amazing.

...if you can get access.

Sell offs don't have to happen, and $25m isn't some small amount of money.

> how has cerebras not gotten their chip right?

It doesn't scale, and won't ever be profitable. They pivoted to inference, which has the unfortunate (for them) side effect of also requiring a boat load of memory. This is why they just partnered with AMD to offload onto their chips.

> I use cerebras.ai the token rate is amazing

Ah, investor. Explains your responses.

Cerebras is an 11 year old unprofitable company with a stock that is down 30% since the IPO, in the hottest market ever.

They've pivoted many times over the years trying to make "wafer scale" work in a variety of use cases, and they still haven't gotten it right.

By the way, the CTO is dumping stock left and right and the stock is down nearly 5% today alone...

https://www.marketbeat.com/instant-alerts/insider-cerebras-s...

In my eyes, success is a profitable company.

Thanks! Always amazing that people don't know this stuff. Oh and the current CFO of Cerebras was the CFO of Bird, another giant failure.

100% this. The CEO at my last company squandered hundreds of millions of investor funds, and now he's the CEO at another company taking on hundreds of millions in debt.

Another example: current CEO of Cerebras, is an SEC felon from a prior company (for cooking the books), and now he's CEO of a public company.

I could have used BTC to buy into the ethereum ICO and I made up every excuse under the sun that a young kid who wrote shit python code could never compete with the gold rock.

Since then I've heavily revised my thinking. Primarily that I don't dismiss things as easily anymore. I try to focus on coming up with a reason to like it instead of disliking it.

I never sold.

Thanks to the DOGE/Trump goverment cutbacks, the previous government listed data was pulled offline. I've got a full copy of the data (much of it is out of date), but I haven't had the time to build a site and put it online. Might get around to it at some point. I'll probably reach out to the guy running the site and see if he wants the data.

https://www.reddit.com/r/HotSpringsWest/comments/1jwc8ga/nce...

It is ok, other hosting companies are allowed to have their own implementations of good ideas.

Cute. That said, if my business does as well as I think it will it'll be worth a lot more than that (not monthly).

I pay $200/month and I generate 10000000x more value of it than that. As you're saying, the actual barrier isn't just the model, it is the set up. As long as the walls are too high, $200 is going to dominate.

The internet was great before AOL, but the simplification is what brought the masses to it.

They have not improved in the one way that I use them today, which is coding. It is like talking to a halfwit, and I always end back up with codex.

Asking a direct question is not hostile. I'm glad to hear you've found a use for a smaller model that generates value. It gives me hope for the future, that said, I think we are still a long ways away from needing HPC in DC's.

> Open models keep getting bigger, but smaller open models also keep getting smarter.

Not only bigger, but smarter and more capable. From what I can tell, smaller are only getting smarter in very specific areas. There is a subtle difference there, that is extremely important.

> What I can do with an 8b used to require a 32b.

What exactly do you do with an 8b? I usually ask this question and either get no response or it is something that doesn't generate anything of value. So, please surprise me.

> they currently don't have a constraint of demonstrating that their value exceeds their cost

There is no loyalty in AI. I can switch to another model at near zero cost. They absolutely do have to demonstrate value. The concept of "good enough" is a misnomer because we're talking about putting these products into the hands of people who need to generate value from them.

That's the usual response, along with "you can't compete with free". But, look at how much money the frontier models are printing, it is obvious that the bell curve of usefulness is still centered around them.

Let's also not forget that even the open models are not getting smaller, they are getting larger. Of course, you can distill them down into something that will fit on smaller compute, but at the end of the day, the data centers of compute, still play a huge role.

Home computers are still nowhere close to as powerful as a $500k+ 10kW server full of 1.5TB of HBM GPU compute.

Large amounts of clothing exports too.

I've driven motorbikes through Dak Lak a few times. Really beautiful area. Just south of there is Da Lat and close by, there is one tiny coffeeshop run by some kids that live there that was my favorite... https://maps.app.goo.gl/PPy3c3T1oreRrDDR6