Tag: machine learning

AI Technology

Federated Learning: The Future of Distributed Machine Learning

In 2017 Google introduced Federated Learning (FL), “a specific category of distributed machine learning approaches which trains machine learning models using decentralized data residing on end devices such as mobile phones.” A new Google paper has now proposed a scalable production system for federated learning to enable increasing workload and output through the addition of resources such as compute, storage, bandwidth, etc.

AI Technology United States

OpenAI Guards Its ML Model Code & Data to Thwart Malicious Usage

The San Francisco-based AI non-profit however has raised eyebrows in the research community with its unusual decision to not release the language model’s code and training dataset. In a statement sent to Synced, OpenAI explained the choice was made to prevent malicious use: “it’s clear that the ability to generate synthetic text that is conditioned on specific subjects has the potential for significant abuse.”

AI Study Guide

Papers With Code Adds State-of-the-Art Features

Papers With Code is a unique and useful resource that presents trending ML research along with the code to implement it. The site was created by Atlas ML CEO Robert Stojnic, aka “rstoj” on Reddit’s machine learning board. The latest version of Papers With Code has added 950+ unique machine learning tasks, 500+ State-of-the-Art result leaderboards and 8500+ papers with code.

AI

To Hire or Not to Hire Online AI Grads: That Is the Question

It all started with a tweet from Google Japan Data Project Manager Suzana Ilić: “Yesterday someone (ML, CS PhD, Stanford) said he would not hire a person who is online educated in Machine Learning. Who here agrees and who thinks differently?” The question triggered a long and occasionally heated discussion that spread from Ilić’s twitter across the machine learning community.

AI China

Tencent AI Lab Director Leaves

It did not take long to see the first major AI talent reshuffling of 2019. Multiple sources are now confirming that reputed AI researcher Dr. Tong Zhang left his position as Executive Director of Tencent AI Lab effective December 31. Rumours suggest Zhang might return to teaching.

AI

2018 In Review: 10 Open-Sourced AI Datasets

In the conclusion to our year-end series, Synced spotlights ten datasets that were open sourced in 2018 and takes a peek into the papers behind them. We hope this list can provide the AI community with insight into what 2019 might hold in store for big data.

AI

Can AI Judge a Paper on Appearance Alone?

The number of AI-related research papers has skyrocketed in recent years, outpacing papers from all other academic topics since 2000. This has, not unsurprisingly, resulted in a shortage of qualified peer reviewers in the machine learning community, particularly when it comes to conference paper submissions.

AI

Ex-Google AI Chief Joins Apple’s Executive Team

Apple is ramping up its ambitious AI strategy, announcing today that John Giannandrea — the former Google AI Chief that Apple poached this April — has joined the company’s executive team as Senior Vice President of Machine Learning and Artificial Intelligence Strategy.

AI

AI Chip Duel: Apple A12 Bionic vs Huawei Kirin 980

Apple has unveiled the latest iteration of its smartphone chip: the A12 Bionic SoC (system-on-a-chip). The company made the announcement yesterday at its annual product showcase event in Cupertino, California, hailing the A12 as the industry’s first ever 7nm chip (the smallest current transistor scale). It will be embedded in Apple’s new XR, XS, and XS Max iPhones.

AI Technology

Jeff Dean’s 1990 Senior Thesis Is Better Than Yours

Google AI lead Jeff Dean recently posted a link to his 1990 senior thesis on Twitter, which set off a wave of nostalgia for the early days of machine learning in the AI community. Parallel Implementation of Neural Network Training: Two Back-Propagation Approaches may be almost 30 years old and only eight pages long, but the paper does a remarkable job of explaining the methods behind neural network training and the modern development of artificial intelligence.