Purely AI News: For AI professionals in a hurry
July 25, 2020
Google's tensorflow-lite framework for deep learning is now more than 2x faster on average, using operator fusion and optimizations for additional CPU instruction sets
TensorFlow Lite, Google's open-source deep learning framework, is a lightweight solution for mobile and embedded devices. It enables low-latency inference of on-device machine learning models with a small binary size and fast performance supporting hardware acceleration.
In the latest version of the TensorFlow Lite framework, Google Research has introduced several community-requested optimizations to make inference on edge IoT devices and smartphones faster and more efficient. TensorFlow Lite already had support for inference using mobile GPUs, Android’s Neural Network API, Hexagon DSPs, Edge TPUs, and the Apple Neural Engine. Integration with the production-tested XNNPACK library further improves inference performance by a factor of 2x on average.

Leveraging the XNNPACK library, Google has made several optimizations for the CPU instruction sets SSE2, SSE4, AVX, AVX2, and AVX512. Additionally, rather than executing TensorFlow Lite operators one-by-one, XNNPACK looks at the whole computational graph and optimizes it through operator fusion. For example, convolution with explicit padding is represented in TensorFlow Lite via a combination of PAD operator and a CONV_2D operator with VALID padding mode. XNNPACK detects this combination of operators and fuses the two operators into a single convolution operator with explicitly specified padding. The XNNPACK backend boosted background segmentation in Pixel 3a Playground by 5X and delivered 2X speedup on neural network models in Augmented Faces API in ARCore. We found that TensorFlow Lite benefits the most from the XNNPACK backend on small neural network models and low-end mobile phones.

The new TensorFlow Lite version 2.3 includes these optimizations based on the XNNPACK backend. Pre-built TensorFlow Lite binaries for Android and iOS can enable these performance improvements with a one-line code change. XNNPACK backend is also supported in the Windows, macOS, and Linux builds of TensorFlow Lite, where it is enabled via a build-time opt-in mechanism. After extensive testing and feedback from the community, Google plans to enable it by default on all platforms in a future release.

Aug. 2, 2020

Sample Factory, a new training framework for Reinforcement Learning slashes the level of compute required for state-of-the-art results

July 31, 2020

Intel joins hands with researchers from MIT and Georgia Tech to work on a code improvement recommendation system, develops "An End-to-End Neural Code Similarity System"

July 23, 2020

Fawkes: An AI system that puts an 'invisibility cloak' on images so that facial recognition algorithms are not able to reveal identities of people without permission

July 22, 2020

Researchers from Austria propose an AI system that reads sheet music from raw images and aligns that to a given audio accurately

July 21, 2020

WordCraft: A Reinforcement Learning environment for enabling common-sense based agents

July 20, 2020

A designer who worked on over 20 commercial projects for a year turns out to be an AI built by the Russian design firm Art. Lebedev Studio

July 19, 2020

Microsoft is developing AI to improve camera-in-display technology for natural perspectives and clearer visuals in video calls

July 18, 2020

Microsoft and Zhajiang Univ. researchers create AI Model that can sing in several languages including both Chinese and English

July 18, 2020

New event-based learning algorithm 'E-Prop' inspired by the Human brain is more efficient than conventional Deep Learning

July 17, 2020

Scientists from the University of California address the false-negative problem of MRI Reconstruction Networks using adversarial techniques

July 16, 2020

A new technique of exposing DeepFakes uses the classical signal processing technique of frequency analysis

July 16, 2020

New AI model By Facebook researchers can recognize five different voices speaking simultaneously, pushes state-of-the-art forward

July 15, 2020

Researchers from Columbia Univ. and DeepMind propose a new framework for Taylor Expansion Policy Optimization (TayPO)

July 14, 2020

Federated Learning is finally here; Presagen's new algorithm creates higher performing AI than traditional centralized learning

July 14, 2020

Fujitsu designed a new Deep Learning based method for dimensionality reduction inspired by compression technology

July 12, 2020

Databricks donates its immensely popular MLflow framework to the Linux Foundation

July 12, 2020

Microsoft Research restores old photos that suffer from severe degradation with a new deep learning based approach

July 12, 2020

Amazon launches a new AI based automatic code review service named CodeGuru

July 12, 2020

IBM launches new Deep Learning project: Verifiably Safe Reinforcement Learning (VSRL) framework

July 12, 2020

DevOps for ML get an upgrade with new open-source CI/CD library, "Continuous Machine Learning (CML)"

July 12, 2020

DeepMind's new open-sourced Reinforcement-Learning library, dm_control, packs a simple interface to common RL utilities

July 12, 2020

Learning to learn: Google's AutoML-Zero learns to evolve new ML algorithms from scratch