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by   -   February 17, 2020

By Ruoxi Jia

People give massive amounts of their personal data to companies every day and these data are used to generate tremendous business values. Some economists and politicians argue that people should be paid for their contributions—but the million-dollar question is: by how much?

by   -   February 14, 2020

The AIhub coffee corner captures the musings of AI experts over a 30-minute conversation. This edition focusses on AI as an inventor. This discussion was prompted by news that an artificial intelligence system was named as the inventor of two ideas in patents filed in the UK, Europe and US last summer.

by   -   February 13, 2020

Monday to Wednesday at AAAI-20 saw a multitude of technical sessions, the exhibition and posters. In addition there were a number of interesting debates, invited talks and panels. Here are some tweets from the final three days of the conference.

by   -   February 12, 2020

If you weren’t able to attend the AAAI20 conference in New York you can catch some of the invited talks and panel sessions via the livestreamed videos. Featured events include Yolande Gil’s presidential address and the Turing Award winners’ session.

by   -   February 11, 2020

The AAAI-20 outstanding paper awards were presented on Tuesday 11th February at the AAAI conference in New York. Awards and honourable mentions were given for: outstanding paper, outstanding student paper and outstanding paper in the special track on AI for social impact. You can read about the award-winning work below.

by   -   February 10, 2020

It was a busy weekend at the 34th Conference on Artificial Intelligence (AAAI). Although the AAAI technical sessions didn’t start in earnest until the Sunday there were numerous workshops on Saturday as well as associated conferences AIES (AI, Ethics and Society) and EAAI (Educational Advances in AI). Here is a selection of tweets from the weekend.

by   -   February 8, 2020

The 34th AAAI Conference on Artificial Intelligence (AAAI-20), held in New York, started yesterday (Friday 7 February) and runs until Wednesday 12 February. Our Managing Editor, Lucy Smith, will be attending, covering the conference and meeting researchers.

by   -   February 5, 2020
Shutterstock

By Jean Frederic Isingizwe Nturambirwe, Stellenbosch University and Umezuruike Linus Opara, Stellenbosch University

Modern farming has evolved by adopting technical advances such as machines for ploughing and harvesting, controlled irrigation, fertilisers, pesticides, crop breeding and genetics research. These have helped farmers to produce large crops of a good quality in a fairly predictable way.

But there’s still progress to be made in getting the best possible yields from different kinds of soils. And big losses still occur – especially during and after harvest – where monitoring and handling of produce isn’t done well. The industry needs smart and precise solutions and these are becoming available through new technology.

by   -   February 4, 2020

What’s hot on arXiv? Here are the most tweeted papers that were uploaded onto arXiv during January 2020.

Results are powered by Arxiv Sanity Preserver.

by   -   February 3, 2020

By Laura Smith and Marvin Zhang

One of the most important markers of intelligence is the ability to learn by watching others. Humans are particularly good at this, often being able to learn tasks by observing other humans. This is possible because we are not simply copying the actions that other humans take. Rather, we first imagine ourselves performing the task, and this provides a starting point for further practicing the task in the real world.

by   -   January 31, 2020

Happy new year 2020! Below are the tweets about AI we have collected this month.

by and   -   January 30, 2020

By Larry Medsker

AI Policy Matters is a regular column in AI Matters featuring summaries and commentary based on postings that appear twice a month in the AI Matters blog.

by   -   January 29, 2020

The Machine Learning for Health workshop at NeurIPS 2019 brought together machine learning researchers, clinicians, and healthcare data experts. With the theme “what makes machine learning in medicine different?” the aim was to elucidate the obstacles that make the development of machine learning models for healthcare uniquely challenging.

by   -   January 28, 2020

By Michael Janner

Reinforcement learning systems can make decisions in one of two ways. In the model-based approach, a system uses a predictive model of the world to ask questions of the form “what will happen if I do x?” to choose the best x1. In the alternative model-free approach, the modeling step is bypassed altogether in favor of learning a control policy directly. Although in practice the line between these two techniques can become blurred, as a coarse guide it is useful for dividing up the space of algorithmic possibilities.

by   -   January 24, 2020

Is our autonomy affected by interacting with intelligent machines designed to persuade us? That’s what researchers at the University of Bristol attempted to find out through an analysis of the interaction between intelligent software agents and human users.


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