tinyML Talks by Zuzana Jelclcova (Demant) and Daniel Situnayake (Edge Impulse)

Announcing two tinyML Talks on July 7th, 2020

IMPORTANT: Please register here
https://us02web.zoom.us/webinar/register/7515928600399/WN_G1s01cZwRXGMdTpqy-I3Ag

Once registered, you will receive a link and dial in information to Zoom teleconference by email, that you can also add to your calendar.

8:00 AM - 8:30 AM Pacific Daylight Time (PDT)
Zuzana Jelclcova, Industrial Ph.D. student, Demant
"Benchmarking and Improving NN Execution on Digital Signal Processor vs. Custom Accelerator for Hearing Instruments"

Hearing instruments are supported by multicore processor platforms, that include several digital signal processors (DSPs). These resources can be used to implement neural networks (NNs); however, execution time and energy consumption are prohibitive to do so. In this presentation, we will talk about benchmarking neural network workloads relevant for hearing aids on Demant’s DSP-based platform. We will also introduce a custom NN processing engine (NNE) that was developed to achieve further power optimizations by exploiting a set of various techniques (reduced wordlength, several MACs in parallel, two-step scaling etc.).
A pretrained, fully connected feedforward NN (Hello Edge: Keyword Spotting on Microcontrollers) was used as a benchmark model to run a keyword spotting application using Google speech command dataset on both, the DSP and NNE. We will talk about the performance of the two implementations, where the NNE significantly outperforms the DSP solution.

Zuzana graduated from Technical University of Denmark (DTU) in 2019 as a MSc of Computer Science and Engineering. Since then she has been pursuing a Ph.D. degree in collaboration with DTU and Demant A/S - an international hearing healthcare group that offers solutions and services to help people with hearing loss. The topic of Zuzana's Ph.D. are neural networks in resource constraint hearing instruments with the focus on hardware and digital design.

8:30 AM - 9:00 AM Pacific Daylight Time (PDT)
Daniel Situnayake, Founding tinyML Engineer, Edge Impulse
"How to train and deploy tiny ML models for three common sensor types"

TinyML is incredibly exciting, but if you're hoping to train your own model it can be difficult to know where to start. In this talk, Dan walks through his workflow and best practices for training models for three very different types of data: time-series from sensors, audio, and vision. We'll be using Edge Impulse, a free online studio for training embedded machine learning models.

Daniel Situnayake is the Founding TinyML engineer at Edge Impulse. He's co-author of the O'Reilly book TinyML, alongside Pete Warden. He previously worked on the TensorFlow team at Google, and he co-founded Tiny Farms Inc., deploying machine learning on industrial scale insect farms.

We encourage you to register earlier since on-line broadcast capacity may be limited.

Note: tinyML Talks slides and videos will be available on the tinyML website and tinyML YouTube Channel afterwards, for those who missed the live session. Please take a moment and subscribe to the YouTube channel today: https://www.youtube.com/tinyML