The capability to learn and adapt to changes in the driving environment is crucial for developing autonomous driving systems that are scalable beyond geo-fenced operational design domains. Deep Reinforcement Learning (RL) provides a promising and scalable framework for developing adaptive learning based solutions. Deep RL methods usually model the problem as a (Partially Observable) Markov Decision Process in which an agent acts in a stationary environment to learn an optimal behavior policy. However, driving involves complex interaction between multiple, intelligent (artificial or human) agents in a highly non-stationary environment. In this paper, we propose the use of Partially Observable Markov Games(POSG) for formulating the connected autonomous driving problems with realistic assumptions. We provide a taxonomy of multi-agent learning environments based on the nature of tasks, nature of agents and the nature of the environment to help in categorizing various autonomous driving problems that can be addressed under the proposed formulation. As our main contributions, we provide MACAD-Gym, a Multi-Agent Connected, Autonomous Driving agent learning platform for furthering research in this direction. Our MACAD-Gym platform provides an extensible set of Connected Autonomous Driving (CAD) simulation environments that enable the research and development of Deep RL- based integrated sensing, perception, planning and control algorithms for CAD systems with unlimited operational design domain under realistic, multi-agent settings. We also share the MACAD-Agents that were trained successfully using the MACAD-Gym platform to learn control policies for multiple vehicle agents in a partially observable, stop-sign controlled, 3-way urban intersection environment with raw (camera) sensor observations.

We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment. The environment encapsulates a competitive machine reader based on BERT, providing candidate answers to questions, and possibly some context. To validate the realism of our formulation, we ask humans to play the role of a meta-answerer. With just a small snippet of text around an answer, humans can outperform the machine reader, improving recall. Similarly, a simple machine meta-answerer outperforms the environment, improving both precision and recall on the Natural Questions dataset. The system relies on joint training of answer scoring and the selection of conditioning information.

The bipedal robot, which stands nearly two feet tall, can do more than just sing and dance. It uses artificial intelligence to recognize patients' faces and engage in conversation – in various languages. Built by SoftBank Robotics of San Francisco, NAO has 25 degrees of freedom to move and adapt to its surroundings, seven touch sensors, four directional microphones and speakers and two 2D cameras. CHOP initially plans to use the robot as a welcoming tool, one that will regularly participate in entertainment programs, including the hospital's live television shows. Next week, it will participate in a Bingo program, calling out the numbers and announcing the names of children who win. "And that's just the tip of the iceberg," said Stephanie Brennan, strategic operations manager for CHOP's child life programs.

Customers expect and use multiple channels to access customer support. "Most customers will still prefer to use an automated or self-service option as long as it is convenient and easy to understand," says Jeff Toister, author of The Service Culture Handbook, "because when a customer does want to connect with a human, it's almost always because something is either urgent or complicated." During the recent California mass power outage everything powered by electricity – Internet Wifi, traffic lights, expresso machines – was brought to a halt. The sheer volume of over 700,000 residents looking for information also brought the PG&E website, chatbots and call centers to their knees. The 2019 CGS Customer Service Chatbot and Channel Survey found that AI technology implementations are happening faster than customers are able, or willing, to embrace them.

Eight artificial intelligence (AI) use-cases from six entities in Qatar were showcased during the Digital Transformation Workshop organised by the Qatar Digital Government Training Programme (QDGTP) in partnership with Microsoft. The event, an initiative by the Ministry of Transport and Communications (MoTC), was held on the sidelines of the recently concluded Qitcom 2019 at the Qatar National Convention Centre (QNCC) in Doha. The six entities included General Authority of Customs (GAC), Hamad Medical Corporation (HMC), Al Jazeera, the Ministry of Commerce and Industry (MoCI), Aspetar, and Aspire. Ali el-Sheshtawi from GAC presented a machine learning module developed by the authority to help in document processing by reducing risk of human error and time taken in handling documents, while HMC, represented by Ramez Raafat and Babu Ramesamy, presented the chatbot and auto coding use-cases respectively. Through the chatbot use-case, intelligent agent within the organisation will help shorten the path and time to get the needed information and understand the correct actions needed.

Eight artificial intelligence (AI) use-cases from six entities in Qatar were showcased during the Digital Transformation Workshop organised by the Qatar Digital Government Training Programme (QDGTP) in partnership with Microsoft. The event, an initiative by the Ministry of Transport and Communications (MoTC), was held on the sidelines of the recently concluded Qitcom 2019 at the Qatar National Convention Centre (QNCC) in Doha. The six entities included General Authority of Customs (GAC), Hamad Medical Corporation (HMC), Al Jazeera, the Ministry of Commerce and Industry (MoCI), Aspetar, and Aspire. Ali el-Sheshtawi from GAC presented a machine learning module developed by the authority to help in document processing by reducing risk of human error and time taken in handling documents, while HMC, represented by Ramez Raafat and Babu Ramesamy, presented the chatbot and auto coding use-cases respectively. Through the chatbot use-case, intelligent agent within the organisation will help shorten the path and time to get the needed information and understand the correct actions needed.

The US government funding in artificial intelligence has fallen short and the country needs to invest in research, train an AI-ready workforce and apply the technology to national security missions, a government-commissioned panel led by Google's former CEO said in an interim report on Monday. The National Security Commission on Artificial Intelligence (NSCAI), created by Congress last year, raised concerns about the progress China has made in this area. It also said the US government still faces enormous work before it can transition AI from "a promising technological novelty into a mature technology integrated into core national security missions." The commission thinks an allied effort on AI in the realm of national security is important, Robert Work, vice chairman of the NSCAI and a former deputy secretary of defense, told reporters. The NSCAI has spoken with Japan, Canada, the United Kingdom, Australia and the European Union, Work said. The challenge US officials face is that American industry and academic leaders have said that any such restrictions would harm the US economy.

A team of leading security researchers was recently crowned top hackers after finding vulnerabilities across multiple devices including an Alexa-powered Amazon Echo and a Samsung Galaxy S10. Amat Cama and Richard Zhu, who go by Team Fluoroacetate, compromised the devices at an international bug bounty event called Pwn2Own in Tokyo late last week. The event, hosted by Zero Day Initiative, is home to "white hat" hackers who are paid top dollar if they find previously unknown bugs in gadgets supplied by big tech companies. The vulnerability Cama and Zhu found in the Echo allowed them to "take control" of the gadget, according to Pwn2Own. And finding the bug earned them $60,000.

Birdsong is the world's finest music. Yet in New Zealand, where birds are regarded as taonga or precious things, a unique ecological conundrum exists. For an estimated 70 million years, New Zealand was isolated by water from the rest of the world, and its birds evolved free from predator mammals. As a result, many of New Zealand's birds, including the iconic kiwi, lost the ability to fly. Unfortunately, predators such as rats, possums, and stoats have gradually been introduced and are increasing.

The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can't) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.