reasonabl_human

Thank you for your work on DwarfStar! It is truly helping democratize access to frontier tech.

Do you have any recommended reading on the history of Christianity? I find it challenging to find unbiased / purely historical explanations of how we got to this point.

How do you feel about this in retrospect? Those observations sound heavily firm-dependent, but I would be interested in learning which non-tech functions offer higher compensation possibilities

can you link to the overall approach or references for your work?

Can you share the name of the company or more product details? Curious to know more about what solutions in this space look like

And that’s not quantized at all, correct?

If so, then the parent comment’s sentiment holds true…. Exciting stuff.

Solid use case for Saul Goodman LLM alignment

What forum are you referring to?

What’s a Notch?

Awesome! Did you document your teardown and guitar amp build anywhere? What a unique project. Would love to see it.

Classic. This was a common failure mode for the 360 as well. Used to fix friends 360s that had the red ring of death by tearing them down, tightening the braces underneath the heat sink, and adding an additional case fan.

Never actually had to escalate to reflowing the BGA mount underneath the GPU but recall tutorials of how to do that in a consumer oven.. thank goodness I never tried that one at home.

What a fascinating read, thanks for sharing that link.

That paper is incredible. It’s crazy that they found 41% of all DN connections receive recurrent feedback from a downstream neuron.

Some things that may be commonplace understanding in the neuroscience community but that I found interesting:

- speculation that deep recurrence in the learning center is a mechanism for working memory, and allows for multiple high-level cognitive processes to occur simultaneously

- the description of how a variety of neurons in the learning center categorize stimuli, a different group controls the learned value of inputs (valence?), and then another group integrates the valences of both the learned and innate neuron groups for the given stimulus category

Oh, and that most of the neurons were engaged in multi-modal activity

Look into Nix / NixOS

What tests are you running? Anything outside of the alpaca eval test suite?

Also interested. Would be really great to run this against a self hosted LLM agent.

Does this mean your queries are all one-shot instead of utilizing techniques like LangChain?

‘Big Tech’ will always be there in some form down the road. If you have the risk tolerance and early career flexibility, take the path less traveled.

Black bar?

ControlNet is the new development that will really allow us to guide diffusion model outputs more granularly - first I’m seeing it used against video generation

Thanks for your work in this space, it’s incredible!

I’ve been sidetracked with work but planning on tuning llama 65B to produce alpaca 65B, will distribute via huggingface or torrent..

FWIW running the 30B alpaca-lora model quantized to 4-bit via llama.cpp has given me great results, and while I don’t expect much of an improvement from 65B at FP16, 65B will probably perform better than 30B when quantized

The interesting next steps in my head are more focused around curating a better instruction-tuning dataset using GPT-4, then fine-tuning again, and integrating the LangChain project with the resulting agent

What is the closest approach we know of today that plays games, not plays? The dialogue above is compelling, and makes me wonder if the same critique can be levied against most prior art in machine learning applied against games. E.g. would you say the same things about AlphaZero?

Okay I’ll bite - please elaborate!

Interesting, where can I learn more about prompting, and tuning a raw model?

Thanks so much for sharing these insights! Especially the humanizing points around life still unfolding around you regardless of how much success you achieve.

Interesting- in that case these are some eye popping numbers.

However, I’m struggling to square that fact with the observation that the Wikipedia table shows a number of entries >100%. How could government spending ever exceed 100% of GDP given it is counting toward GDP?

Can someone explain the significance of this statistic in context? Seems there are many successfully economies with a government spend of higher % of GDP than the US. Not sure how this fits into a broader picture of a country’s financial health.

Also- based on my cursory reading here, it seems disingenuous to claim 46% of GDP is government spending- the stat is that government spending is comparable to 46% of the GDP of that year. Government spend doesn’t comprise 46% of the GDP, rather we are using GDP as a measuring stick to evaluate the sanity of government spending amounts.

Whoa! Do you have a build log posted somewhere? What platform did you build on?

I think I just discovered a dangerous new rabbit hole…

Do you have recommended resources for getting into #3, specifically around funding / assisting others in building businesses?

I am interested in doing so outside of the traditional VC models and tech sector, but the signal to noise ratio of information on building businesses is incredibly low on the web.