By Chansung Park and Sayak Paul (ML-GDEs) In this post, we’ll share the lessons and findings learned from conducting load tests for a Deep Learning model across numerous deployment configurations. These configurations involve REST-based deployments with FastAPI and TensorFlow Serving. …

In the previous post, Margaret introduced the project covering different scenarios where it could be useful along with other technical objectives. In this post, we will provide some more details about the models we used, some major bits from their conversion process in TensorFlow Lite (TFLite), and the benchmarking results…

Our interviewee today is Dan who is a third-year Ph.D. student in Computer Science at UC Berkeley. Dan is primarily interested in Machine Learning Safety. Some of his notable works include the GELU activation function, the activation function used in BERT and GPT. …

We have Vincent Sitzmann for today’s interview! Vincent is a Postdoctoral Researcher at MIT’s CSAIL and he just completed his Ph.D. at Stanford. Vincent’s research interests lie in the area of neural scene representations — the way neural networks learn to represent information on our world. One of Vincent’s works…

For today’s interview, we have Alexander M. Rush with us. Alexander is currently an Associate Professor at Cornell University where his research group studies several areas of NLP such as text generation, document-level understanding, and so on. They also work on open-source developments such as OpenNMT. Alexander’s research work has…

This article discusses pruning techniques in the context of deep learning. — This article is the successor to my previous article on Quantization. In this article, we’re going to go over the mechanics of model pruning in the context of deep learning. Model pruning is the art of discarding those weights that do not signify a model’s performance. …

I am pleased to have Niki Parmar for today’s interview. Niki is a Senior Research Scientist at Google Brain where she is involved in research related to self-attention and extending that to different applications in both language and vision. …

Highlights about the experiences I gathered throughout the GDE program in one year. — I first came across the term “Google Developers Expert” (GDE) back in 2018 during DevFest Kolkata where a GDE in Flutter Pawan Kumar gave a talk. After going through the details of the program I got immensely interested to join it. …

I am pleased to have Colin Raffel for today’s interview. Colin is currently working as a Research Scientist at Google. Colin’s research interests broadly lie in areas like learning with limited labeled data, transfer learning, especially from an NLP context. …