Search Results for author: Pete Warden

Found 13 papers, 8 papers with code

Few-Shot Keyword Spotting in Any Language

2 code implementations3 Apr 2021 Mark Mazumder, Colby Banbury, Josh Meyer, Pete Warden, Vijay Janapa Reddi

With just five training examples, we fine-tune the embedding model for keyword spotting and achieve an average F1 score of 0. 75 on keyword classification for 180 new keywords unseen by the embedding model in these nine languages.

Keyword Spotting Transfer Learning

Visual Wake Words Dataset

5 code implementations12 Jun 2019 Aakanksha Chowdhery, Pete Warden, Jonathon Shlens, Andrew Howard, Rocky Rhodes

To facilitate the development of microcontroller friendly models, we present a new dataset, Visual Wake Words, that represents a common microcontroller vision use-case of identifying whether a person is present in the image or not, and provides a realistic benchmark for tiny vision models.

Machine Learning Sensors

1 code implementation7 Jun 2022 Pete Warden, Matthew Stewart, Brian Plancher, Colby Banbury, Shvetank Prakash, Emma Chen, Zain Asgar, Sachin Katti, Vijay Janapa Reddi

Machine learning sensors represent a paradigm shift for the future of embedded machine learning applications.

BIG-bench Machine Learning

Data Engineering for Everyone

no code implementations23 Feb 2021 Vijay Janapa Reddi, Greg Diamos, Pete Warden, Peter Mattson, David Kanter

This article shows that open-source data sets are the rocket fuel for research and innovation at even some of the largest AI organizations.

BIG-bench Machine Learning

ML-EXray: Visibility into ML Deployment on the Edge

no code implementations8 Nov 2021 Hang Qiu, Ioanna Vavelidou, Jian Li, Evgenya Pergament, Pete Warden, Sandeep Chinchali, Zain Asgar, Sachin Katti

The key challenge is that there is not much visibility into ML inference execution on edge devices, and very little awareness of potential issues during the edge deployment process.

Quantization

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

no code implementations5 Jan 2022 Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi

In this paper, we present CFU Playground: a full-stack open-source framework that enables rapid and iterative design and evaluation of machine learning (ML) accelerators for embedded ML systems.

Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers

no code implementations27 Jan 2023 Shvetank Prakash, Matthew Stewart, Colby Banbury, Mark Mazumder, Pete Warden, Brian Plancher, Vijay Janapa Reddi

This article discusses both the potential of these TinyML applications to address critical sustainability challenges, as well as the environmental footprint of this emerging technology.

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