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Fable and the end of the free lunch

dbreunig.com

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Re: Fable and the end of the free lunch

#41

Post by geniium »

nchmy wrote: post #2

The real revolution is Deepseek v4 flash and similar models (GPT 5.6 Luna, muse spark 1.2, mimo, etc...) - Genuinely good performance for a tiny fraction of the cost of Fable and even GLM etc... I think a lot of people would be very content if they never got smarter, and just kept getting even cheaper/faster. Of course, both things continue to happen on a seemingly monthly basis

I was using ChatGPT voice during cooking to reflect on variations of a dishes i was preparing for years.

It was so amazing to get advices and reflect that it struck me : I could use this model forever - it’s clever enough to help me tons and do lot of work for me - even if ai would stop evolving I would love it

Re: Fable and the end of the free lunch

#42

Post by sscaryterry »

gpjanik wrote: post #40

"When Moore’s Law slowed in the mid-2000s" it did not, in fact, slow down in the mid 2000s, or at all. https://ourworldindata.org/data-insights/moores-law-has-accu...

It did in terms of the traditional more MHz (GHz) is better, but as you've correctly pointed out, not when it comes to actual compute.

Re: Fable and the end of the free lunch

#43

Post by kelnos »

hypfer wrote: post #26
dgellow wrote: post #23

Earlier quoted context omitted.

FWIW you’re not looking good in this engagement, feels very childish, looking for a gotcha that doesn’t mean much

I think that depends on the audience. Thank you for caring though :)

Audience member here: I agree with GP; you posts come off as petty and childish.

It seems natural to me to make comparisons only to open weight models where the weights have actually been released.

Re: Fable and the end of the free lunch

#44

Post by aabhay »

This concept of a free lunch was never true. In a competitive dynamic, speed and performance were always worth optimizing, comparing, and improving.

One of the primary reasons for this is that computers operate in a vast range of orders of magnitude. There’s several orders of magnitude between cache local cpu operation and dram, then several to disk, then several to network, then several to globally durable guarantees. When your code has literally thirteen orders of magnitude to optimize under, there’s never a free lunch. You always need to understand your stuff.

Re: Fable and the end of the free lunch

#45

Post by Zylokloto »

He started with thinking were to send what.

I throw everything at claude Opus.

While some people start thinking like OP, A LOT of people just start exploring ai.

And others which are already using it, only understand half of it and just use what they are allowed to use. Claude, GitHub Copilot, Curser, etc.

Re: Fable and the end of the free lunch

#46

Post by jbstack »

gpjanik wrote: post #40

"When Moore’s Law slowed in the mid-2000s" it did not, in fact, slow down in the mid 2000s, or at all. https://ourworldindata.org/data-insights/moores-law-has-accu...

You've selectively quoted the article. The full quote (emphasis added):

"When Moore’s Law slowed in the mid-2000s (specifically, single-threaded performance stagnated), we suddenly had to think about parallelization, architecture, memory locality, etc."

Your link is talking about transistor count. The article is talking about single-threaded performance. Today's CPUs are faster in large part because they have more and more cores.

Re: Fable and the end of the free lunch

#47

Post by nchmy »

lilbigdoot wrote: post #14
nchmy wrote: post #2

The real revolution is Deepseek v4 flash and similar models (GPT 5.6 Luna, muse spark 1.2, mimo, etc...) - Genuinely good performance for a tiny fraction of the cost of Fable and even GLM etc... I think a lot of people would be very content if they never got smarter, and just kept getting even cheaper/faster. Of course, both things continue to happen on a seemingly monthly basis

If they could be cheap+fast and not try to do too much, that's a good spot for me. I don't use the smarter models as much because of cost and because they're still not good enough to let loose on a lot of problems. For assistance I prefer something that can very quickly spit out a specific piece I can review on the spot and keep going. I let smarter models handle things that I treat as external dependencies and don't…

I have a similar process - its just a pair programmer most of the time. I dont understand how people can have a fleet of agents working a bunch of waterfall specs..

Re: Fable and the end of the free lunch

#48

Post by robomc »

enraged_camel wrote: post #5

>> GLM 5.2 is worth focusing on. It came out the same week as Fable and is roughly 1/9th the cost (and ~1/5th the cost of Opus 5). Is GLM 1/9th the quality of Fable? Perhaps, for certain classes of tasks. But for most rote coding it’s more than sufficient. Especially when provided with great context. I frequently chat with Fable to interrogate and shape a design, before handing off a brief to GLM. People say stuff li…

> It can result in a key insight that helps you strategize more effectively, a novel approach that saves a huge amount of time, a feature design that is lot more user-friendly

My brother, that's my job.

Re: Fable and the end of the free lunch

#49

Post by csullivannet »

blfr wrote: post #39
denverllc wrote: post #31

Earlier quoted context omitted.

Write a detailed plan using a more expensive model and implement it using the cheaper one.

How much are you saving once the more expensive model already has all the context loaded and ready to go?

API calls get more expensive, not less, as you've loaded more context. This is exactly when you want to switch to cheaper models.

Re: Fable and the end of the free lunch

#50

Post by hypfer »

kelnos wrote: post #43
hypfer wrote: post #26

Earlier quoted context omitted.

I think that depends on the audience. Thank you for caring though :)

Audience member here: I agree with GP; you posts come off as petty and childish. It seems natural to me to make comparisons only to open weight models where the weights have actually been released.

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