635 citations · 1k across the 4 of their papers we have counts for
7 papers
Text and Code Embeddings by Contrastive Pre-Training
Arvind Neelakantan, Tao Xu, Raul Puri +22
Text embeddings are useful features in many applications such as semantic search and computing text similarity. Previous work typically trains models customized for different use c…
A quantum-classical cloud platform optimized for variational hybrid algorithms
Peter J. Karalekas, Nikolas A. Tezak, Eric C. Peterson +3
In order to support near-term applications of quantum computing, a new compute paradigm has emerged--the quantum-classical cloud--in which quantum computers (QPUs) work in tandem w…
Solving Rubik's Cube with a Robot Hand
OpenAI, Ilge Akkaya, Marcin Andrychowicz +16
We demonstrate that models trained only in simulation can be used to solve a manipulation problem of unprecedented complexity on a real robot. This is made possible by two key comp…
Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers
C. M. Wilson, J. S. Otterbach, N. Tezak +7
Noisy intermediate-scale quantum computing devices are an exciting platform for the exploration of the power of near-term quantum applications. Performing nontrivial tasks in such…
Unsupervised Machine Learning on a Hybrid Quantum Computer
J. S. Otterbach, R. Manenti, N. Alidoust +27
Machine learning techniques have led to broad adoption of a statistical model of computing. The statistical distributions natively available on quantum processors are a superset of…
All-mechanical quantum noise cancellation for accelerometry: broadband with momentum measurements, narrow band without
Kurt Jacobs, Nikolas Tezak, Hideo Mabuchi +1
We show that the ability to make direct measurements of momentum, in addition to the usual direct measurements of position, allows a simple configuration of two identical mechanica…