icpmacdo

not that much because its getting better at all benchmarks

"It feels like these new models are no longer making order of magnitude jumps, but are instead into the long tail of incremental improvements. It seems like we might be close to maxing out what the current iteration of LLMs can accomplish and we're into the diminishing returns phase."

SWE bench from ~30-40% to ~70-80% this year

incredible results

Modern AI both shortens the useful lifespan of software and increases the importance of development speed. Waiting around doesn’t seem optimal right now.

He only criticizes ai capabilities, without creating anything himself. Credentials are effectively meaningless. With every new release, he clamors for attention to prove how right he was—and always will be. That’s precisely why he lacks credibility.

Gary Marcus is continuously lambasted and not taken seriously

This is literally just the scaling laws, "Scaling laws predict the loss of a target machine learning model by extrapolating from easier-to-train models with fewer parameters or smaller training sets. This provides an efficient way for practitioners and researchers alike to compare pretraining decisions involving optimizers, datasets, and model architectures"

https://arxiv.org/html/2410.11840v1#:~:text=Scaling%20laws%2....

can you share learning resources on this topic

ARC co-founder Mike Knoop

"Raising visibility on this note we added to address ARC "tuned" confusion:

OpenAI shared they trained the o3 we tested on 75% of the Public Training set.

This is the explicit purpose of the training set. It is designed to expose a system to the core knowledge priors needed to beat the much harder eval set.

The idea is each training task shows you an isolated single prior. And the eval set requires you to recombine and abstract from those priors on the fly. Broadly, the eval tasks require utilizing 3-5 priors.

The eval sets are extremely resistant to just "memorizing" the training set. This is why o3 is impressive." https://x.com/mikeknoop/status/1870583471892226343

Why don't they already carry payloads? Is there anything worth taking up with the current expected value of it exploding ect?

Can you link some of the best youtube channels for those?

Always cool to see innovative solutions like this

Scaling The Turk to OpenAI scale would be as impressive as agi

"The Turk was not a real machine, but a mechanical illusion. There was a person inside the machine working the controls. With a skilled chess player hidden inside the box, the Turk won most of the games. It played and won games against many people including Napoleon Bonaparte and Benjamin Franklin"

https://simple.wikipedia.org/wiki/The_Turk#:~:text=The%20Tur....

This is what an incredible level of product market fit look's like, people act like they are forced to pay for these services. Go use a local LLAMA!

because it is still the most interesting field of study

He's alive

its a native swift app

No there is not

More info with an interview with Ilya here https://www.bloomberg.com/news/articles/2024-06-19/openai-co...

Thanks for the work you put into the Svelte platform, competition helps keep ecosystems more honest

"This revenue is almost all direct from ChatGPT and other OpenAI sales"

https://x.com/amir/status/1800992276652630455

OpenAI taken when they were valued at <1Bn

Incorrect round

Ilya: "I’m confident that OpenAI will build AGI that is both safe and beneficial under the leadership of @sama, @gdb, @miramurati and now, under the excellent research leadership of @merettm"

https://x.com/ilyasut/status/1790517455628198322

you would imagine some technology would be able to detect this no?

I've been working on the same thing, there is an interesting quote from back in the day and its either make your program faster or wait 6 months for the computers to get faster. I look at it the same way now with Key Point Analysis and Pose Estimation libraries.

I think OSS is best for this category right now.

If you know about the author of this post Gary Marcus you can just as easily ascribe accusations of fear, The Denial of Uncertainties, Hype and self-promotion/grifting

Spending time trying out Google's new AI products you can see the astonishing amounts of enormous bloat around every single service it offers

Sergey shouldn't be pair programming right now he should be doing the hard work with Sundar of bringing some semblance of coherence to their offerings but it seems like the organizational dynamics are too challenging for them at this scale.

Among the various free backend hosting options currently available, does Cloudflare stand out as the best choice with its offerings such as Workers and D1? I would love to hear users experiences with these services or if there any informative resources that discuss the costs associated with scaling applications on the infra?

Not to conflate it with him not feeling fear though, here is a TV show episode with him talking about the subject, hard to timestamp but 14:10 for the busy https://www.youtube.com/watch?v=V4OGs1DehzA

never mind people who have to stand up clusters with B100s soon

Gwern(or anyone else) do you have any resources on this?