Alistair Letcher
@aletcher.bsky.social
PhD student in Oxford (@flair-ox.bsky.social), working on RL & AI Safety 🤖
Website: aletcher.github.io
Website: aletcher.github.io
We made evolution scale to billion-parameter models. 🤯
Super proud of our team on this wild project!!
Super proud of our team on this wild project!!
Introducing 🥚EGGROLL 🥚(Evolution Guided General Optimization via Low-rank Learning)! 🚀 Scaling backprop-free Evolution Strategies (ES) for billion-parameter models at large population sizes
⚡100x Training Throughput
🎯Fast Convergence
🔢Pure Int8 Pretraining of RNN LLMs
⚡100x Training Throughput
🎯Fast Convergence
🔢Pure Int8 Pretraining of RNN LLMs
November 21, 2025 at 9:05 PM
We made evolution scale to billion-parameter models. 🤯
Super proud of our team on this wild project!!
Super proud of our team on this wild project!!
1/ Excited to share my recent work with IBM Research, "Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits"! We prove stronger, more realistic, and classically computable gradient bounds for variational quantum algorithms (VQAs). Link: quantum-journal.org/papers/q-202...
March 24, 2025 at 4:39 PM
1/ Excited to share my recent work with IBM Research, "Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits"! We prove stronger, more realistic, and classically computable gradient bounds for variational quantum algorithms (VQAs). Link: quantum-journal.org/papers/q-202...
Reposted by Alistair Letcher
Alistair Letcher, Stefan Woerner, Christa Zoufal
Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits
https://arxiv.org/abs/2309.12681
Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits
https://arxiv.org/abs/2309.12681
September 20, 2024 at 7:31 AM
Alistair Letcher, Stefan Woerner, Christa Zoufal
Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits
https://arxiv.org/abs/2309.12681
Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits
https://arxiv.org/abs/2309.12681