1. Baidu has a new trick for teaching AI the meaning of language

Google in an ongoing competition in AI. The company was Baidu, China’s closest equivalent to Google, and the competition was the General Language Understanding Evaluation, otherwise known as GLUE.

Author: Karen Hao

Read More On: MIT Technology Review

2. China’S Baidu Dethrones Google To Take AI Language Crown

Chinese technology giant Baidu has overtaken Google and Microsoft in an artificial intelligence competition designed to test how well a machine can understand human language. Baidu, which is often referred to as China‘s Google, achieved the highest ever score in the General Language Understanding Evaluation (Glue) – widely considered to be the benchmark for AI language understanding.

Author: Anthony Cuthbertson

Read More On: Independent

3. AI creativity will bloom in 2020, all thanks to true web machine learning

Machine learning has been trotted out as a trend to watch for many years now. But there’s good reason to talk about it in the context of 2020. And that’s thanks to developments like TensorFlow.js: an end-to-end open source machine learning library that is capable of, among other features, running pre-trained AI directly in a web browser.

Author: Maciej Zasada

Read More On: The Next Web

4. Japan Loves Robots, but Getting Them to Do Human Work Isn’t Easy

ASAHIKAWA, Japan — Removing the tiny eyes that pockmark potatoes is dull, repetitive and time-consuming work — perfect, it would seem, for robots in a country where the population is declining and workers are increasingly in short supply.

Author:

Read More On: The New York Times

5. How AI Is Really Going To Change Real Estate In 2020 And Beyond

By 2030, AI is predicted to add +$15 trillion to the global GDP thanks largely to solving data issues according to PwC. Lending money used to be a tricky business but time consumers and technology is changing. Banks and other industries are struggling to cope with the changing consumer demand, but a few are getting it right.

Author: Paul Armstrong

Read More On: Forbes

6. Lack of guidance leaves public services in limbo on AI, says watchdog

Police forces, hospitals and councils struggle to understand how to use artificial intelligence because of a lack of clear ethical guidance from the government, according to the country’s only surveillance regulator.

Author: Dan Sabbagh

Read More On: The Guardian

7. 10 Ways AI Is Going To Improve Fintech In 2020

Bottom Line: AI & machine learning will improve Fintech in 2020 by increasing the accuracy and personalization of payment, lending, and insurance services while also helping to discover new borrower pools.

Author: LouisColumbus

Read More On: Forbes

8. Generative adversarial networks: What GANs are and how they’ve evolved

Perhaps you’ve read about AI capable of producing humanlike speech or generating images of people that are difficult to distinguish from real-life photographs. More often than not, these systems build upon generative adversarial networks (GANs), which are two-part AI models consisting of a generator that creates samples and a discriminator that attempts to differentiate between the generated samples and real-world samples.

Author: Kyle Wiggers

Read More On: VentureBeat

9. There’s a robot cat you can back on Kickstarter

You may have heard of Aibo, Sony’s robot dog, but if a robot cat is what you’ve always wanted, you’re now able to back one on Kickstarter. In fact, it actually looks kind of cute. MarsCat, made by Elephant Robotics, looks a lot like a cat, but it’s not realistic enough that you’ll be fooled into thinking it’s a replacement for a furry feline that might already wander around your house.

Author:  

Read More On: The Verge

10. In 2020, let’s stop AI ethics-washing and actually do something

Last year, just as I was beginning to cover artificial intelligence, the AI world was getting a major wake-up call. There were some incredible advancements in AI research in 2018—from reinforcement learning to generative adversarial networks (GANs) to better natural-language understanding.

Author: Karen Hao

Read More On: MIT Technology Review