Viewing profile — mirker

One thing to point out is that the threshold of predictor complexity is dependent on the execution pipeline. A very speculative and deep architecture has a bigger need for better p…

Does anyone have experience using these open source models in production?

There is a ton of value. OpenAI having proprietary LLMs single handedly pivoted the entire field to LLMs. A random GitHub repository doesn’t come close to impact.

Because the authors don’t get a large reward for open sourcing the work and they stand to lose future value by lowering the gate to competition. You may want the code, but Google w…

They asked Watson of course.

Agreed. Here’s the thing: the authors of that paper got early access to GPT-4 and ran a bunch of tests on it. The important bit is that MSR does not see into OpenAI’s sausage makin…

The APIs were messed up early on, which is a reason TF2 happened. Every team started making their own random implementations of stuff. You had the TF Slim API, you had Keras, etc. …

Nah, TF has had dynamic execution since TF2 and it’s still losing users, it seems. The execution model and API is simply more complicated. What’s a session, placeholder, constant, …

PyTorch examples were also cleaner. torchvision had ResNet training batteries included while TF had role your own or clone some weird Keras repository.

I don’t understand what you mean. Here’s how many applied ML papers work: create a new dataset for a novel problem, download a PyTorch model, point model at dataset directory. Is i…

The story I’ve heard is the economics undergrads can’t get into economics grad school. This is just a rumor but the sentiment is that undergrads get taught a watered down version o…

I agree with you but does anyone even recognize the last category outside blue-sky research? People have a tendency to bin other people into buckets. Being a master at 2 things mea…

But it’s more thoughtful. The purchaser thought long and hard about what place the purchasee can use it in.

When people say you need the third hardware revision to get functional performance, and it still doesn’t work, you should conclude it’s poorly designed. The fact that these chips w…

Yeah the issue is you can generate data, but it won’t be good data. Training over random strings won’t make you learn language, but it’s technically data.

The OPs point is that it’s likely impossible to do what is claimed here in general. Imagine the LLM says something like Fermat’s Last Theorem. To verify it, you’d have to either 1)…

Many of those people left though.

There’s actually a few papers already on constrained decoding. I won’t link them but if you go on arxiv and really look you will find a couple in the past year.

Sure, I agree they are useful. My objection is it’s more in the tool category than science, while Alphafold is both. There isn’t convincing evidence that GPTs are pushing what we k…

Alphafold is open and seems fundamentally transformative in the science space. GPT is nice but it’s a smart meme-generator at the moment. I don’t disagree with the impact on G’s bo…

OS needs less than 100GB, though, so mixed drives seems more cost effective.

The image is nearly unreadable for me on mobile.

DOTA, Rocket League, CSGO, etc. are e-sports friendly but don’t have this population problem. It’s not about being “hardcore”; it’s about having broad appeal to hit a wide market s…

Hardcore “competitive” RTS (StarCraft/Age of Empires) can’t since it’s not competitive enough if you can’t hit a meaningful 300+ actions per minute, which is impossible without hot…

It looks interesting, honestly. Shame the RTS market is relatively small.