Last Week in AI

The latest developments in AI research and technology.

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Every week, Invector Labs publishes a newsletter that covers the most recent developments in AI research and technology. You can find this week’s issue below. You can sign up for it below. Please do so, our guys worked really hard on this:

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From the Editor: Architectures for Building AI at Scale

Building artificial intelligence(AI) systems at scale seems like a problem that only a few companies have and, as a result, there are not many available guidance about what works and what doesn’t. If you are a machine learning architect looking to implement an infrastructure to run machine learning programs at scale, where do you start? As a new industry, we are all learning and trying to figure best practices as we go along.

In our experience, the best reference architectures for implementing machine learning at scale are coming from big technology players like Microsoft, Google, Facebook, Uber, Amazon, etc. After all, they are the companies dealing with these challenges. The great thing is that these companies have been open sourcing many of the frameworks and tools of their infrastructure. Just this week, Uber open sourced its Fiber framework for running parallel, highly scale computations. Following the new releases of those machine learning teams is a great way to spot new best practices and ideas that could be adapted to your machine learning architecture.

Now let’s take a look at the core developments in AI research and technology this week:

AI Research

Adversarial Neural Networks at Amazon

The Amazon Research team published some details about how the retail giant uses adversarial neural networks to improve product discovery.

>Read more in this blog post from Amazon Research

Training Robots to Navigate Using Simulations

Microsoft Research published a paper and a dataset about how to use photorealisitic simulated environments to teach robots how to see and navigate.

>Read more in this blog post from Microsoft Research

Translating and Summarizing Documents Without Fine-Tuning

Facebook AI Research published a paper introducing MARGE, a pretrained language model that learns to paraphrase, translate, and summarize text without any fine-tuning.

>Read more in the original research paper

Cool AI Tech Releases

AWS CodeGuru

Amazon Web Services(AWS) announced CodeGuru, a machine learning engine that can automate code reviews.

>Read more in the AWS press release

Uber Fiber

Uber open sourced Fiber, a framework for scaling computations, like the ones used in machine learning models, to hundreds of thousands of machines

>Read more in this blog post from the Uber engineering team

Connected Sheets

Google announced the general availability of Connected Sheets, which enables the analysis of petabytes of data using the familiar Google Sheets interface.

>Read more in this blog post from the G-Suite team

AI Startups and Relevant News

Amazon, Google Back Nation Research Cloud Bill

Tech giants Amazon and Google have joined over 20 organization supporting an US Congress bill to create a National AI Research Cloud that will give AI researchers access to compute resources and datasets.

>Read more in this coverage from VentureBeat

YouTube Gets a Smart Reply

Google has adapted its famous SmartReply feature to YouTube.

>Read more in this coverage from TechCrunch

MIT Takes Down Popular Dataset

MIT has taken offline its high cited Tiny Images dataset over allegations that it contains racist and biased label which can influence the outcome of machine learning models.

>Read more in this coverage from The Next Web

Written by

CEO of IntoTheBlock, Chief Scientist at Invector Labs, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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