Dominick Wirzba

Chronuid

1 4

·

dominick-wirzba-a46898115

AI & ML interests

None yet

Recent Activity

reacted to iliya-radulov's post with 🔥 3 days ago

Field Notes from a Low-Cost Robot Learning Lab: Hardware Churn, Software Whiplash, and What Actually Went Wrong An informal companion piece documenting the hardware incidents, framework churn, and debugging dead-ends from roughly seven weeks of work. It is written for people building similar setups on a hobbyist budget and is candid about the time lost to causes like loose power cables and swapped ports. Zenodo: https://zenodo.org/records/23259698 About me: I am an independent researcher. These works are part of a single-operator project on low-cost robot learning. My ORCID is 0000-0001-8943-5083. For questions or collaboration, feel free to reach out via the HF community.

reacted to Saccadic-AI's post with 🔥 3 days ago

One neural network. Five mathematical operations. Different learning times. We trained a small mixture-of-experts transformer on addition, subtraction, multiplication, division, and exponentiation modulo 113. The operations didn’t generalize together. Multiplication and division reached 90% held-out accuracy first, followed by exponentiation, subtraction, and finally addition. Multiplication before addition—the reverse of what we expect from a schoolchild. The accuracy chart in the linked article shows why a single overall accuracy number can hide an interesting learning story. Measured with IRIS from Saccadic LLC. More figures and analysis: https://huggingface.co/blog/Saccadic-AI/accuracy-plateaued-the-model-kept-changing Have you observed a similar ordering in multi-task grokking experiments?

reacted to Quazim0t0's post with 🔥 20 days ago

It feels like a sugar rush… this golden ratio they found. Stepping through a maze of processes, landing on what aims to be a generalist, raised from the cemetery of echoes of our thoughts, statements, findings, and conclusions. I never really thought beyond this point. I always assumed that the world would look as elegant as the innovations we create. I thought it would look different, have a defining design that really embodied the point we have now arrived at. I can't tell the difference. Everything looks the same. I think that's why it's even harder sometimes for us to swallow what is actually happening, because every representation that we've had from science fiction doesn't really fit the theme. I don't really see any worry with text and language. These models can generalize them well, and we have all seen how profound it can be. What I do worry about more is when we leave the tiny world of language and replace it with the big world of experiences. What would it be like to generalize hundreds of lifetimes? Would it see the nuances better than I? Could it predict what comes next if it had enough data from observing and experiencing the world?... Read more: https://huggingface.co/blog/Quazim0t0/little-world-big-world

View all activity

Organizations

models 0

None public yet

datasets 0

None public yet