Technology has the power to improve lives and tackle the great challenges of our time. At the University of Exeter, for example, Tim Dodwell is about to start a five-year project looking into how technology can make the aviation industry more sustainable and safer. He is one of the first five recipients of a new government fund for research fellowships into artificial intelligence (AI). His work will focus on how we can use machine learning and data processing to understand complex mathematical problems and build lighter and faster aircraft. The UK is the birthplace of AI, and it is fitting that these new fellowships are named after the man credited with inventing machine learning: Alan Turing.

You are a member of the Malta National AI Taskforce and were involved in drafting the government's national strategy for AI. What is your background in this regard - which are your areas of expertise? In terms of my undergraduate education, my background is in creative computing – combining computing technology with art and culture, which is what my job at MUŻA involves. I subsequently studied for a post-graduate degree in Artificial Intelligence, an area I always found interesting, especially when it comes to creative intersections with AI. I am very interested in computer interaction and computer vision, which are also my areas of expertise.

The growing application of deep neural networks in safety-critical domains makes the analysis of faults that occur in such systems of enormous importance. In this paper we introduce a large taxonomy of faults in deep learning (DL) systems. We have manually analysed 1059 artefacts gathered from GitHub commits and issues of projects that use the most popular DL frameworks (TensorFlow, Keras and PyTorch) and from related Stack Overflow posts. Structured interviews with 20 researchers and practitioners describing the problems they have encountered in their experience have enriched our taxonomy with a variety of additional faults that did not emerge from the other two sources. Our final taxonomy was validated with a survey involving an additional set of 21 developers, confirming that almost all fault categories (13/15) were experienced by at least 50% of the survey participants.

Suchi Saria is a Professor of Machine Learning and Healthcare at Johns Hopkins University, where she uses big data to improve patient outcomes.[2][3][4][5] She is a World Economic Forum (WEF) Young Global Leader. She earned her Bachelor's degree at Mount Holyoke College.[7] She was awarded a full scholarship from Microsoft. In 2004 she joined Stanford University as a Rambus Corporation Fellow.[7]

Killer autonomous robots that use algorithms and sensors to determine when to kill people should be banned, the UN has been told. The Campaign To Stop Killer Robots has called on the international community to create a treaty to regulate drones, vehicles and boats that operate on their own. Organisers say artificial intelligence technology is advancing so rapidly that legislation is urgently needed. The treaty would prohibit weapons systems that do not allow human control and those that make kill decisions without human consultation. The group includes Jody Williams, who won the Nobel Peace Prize in 1997 for her work on the International Campaign to Ban Land Mines.

Prof. Zhang is the JG Jackson and CJ Wood professor of physics at Stanford University. He is a member of the US National Academy of Science, the American Academy of Arts and Sciences and a foreign member of the Chinese Academy of Sciences. He discovered a new state of matter called topological insulator in which electrons can conduct along the edge without dissipation, enabling a new generation of electronic devices with much lower power consumption. For this ground breaking work he received numerous international awards, including the Buckley Prize, the Dirac Medal and Prize, the Europhysics Prize, the Physics Frontiers Prize and the Benjamin Franklin Medal. He is also the founding chairman of DHVC venture capital fund, which invests in AI, blockchain, mobile internet, big data, AR/VR, genomics and precision medicine, sharing economy and robotics.

There are multiple ways to learn data science, machine learning and deep learning concepts. You can watch videos, read articles, enroll in courses, attend meetups, among other things. I have personally learned a LOT from interacting with data science experts and industry thought leaders. Their experience in managing end-to-end machine learning and deep learning projects, their thinking when building a data science team from scratch, how they managed tough projects and overcame hurdles, etc. – we simply cannot learn all of these in any course. So, I am thrilled to present an exclusive interview with one such data science expert and industry thought leader – Dr. Sunil Kumar Vuppala!

In this work, we study how the large-scale pretrain-finetune framework changes the behavior of a neural language generator. We focus on the transformer encoder-decoder model for the open-domain dialogue response generation task. We find that after standard fine-tuning, the model forgets important language generation skills acquired during large-scale pre-training. We demonstrate the forgetting phenomenon through a detailed behavior analysis from the perspectives of context sensitivity and knowledge transfer. Adopting the concept of data mixing, we propose an intuitive fine-tuning strategy named "mix-review". We find that mix-review effectively regularize the fine-tuning process, and the forgetting problem is largely alleviated. Finally, we discuss interesting behavior of the resulting dialogue model and its implications.

A Nobel Peace prize winner has warned against robots making life-and-death decision on the battlefield, as it is'unethical and immoral' and can never be undone. Jody Williams made the statement at the United Nations in New York City after the US military announced its project the uses AI to make decisions on what human soldiers should target and destroy. Williams also pointed out the difficulty of holding those involved accountable for certain war crimes, as there will be a programmer, manufacturer, commander and the machine itself involved in the act. Jody Williams (right) has warned against robots making life-and-death decision on the battlefield, as it is'unethical and immoral' and'can never be undone'. She was accompanied with fellow activists Liz O'Sullivan (left) and Mary Wareham (center) Williams won the prestigious accolade in 1997 after leading efforts to ban landmines and is now an advocate with the'Campaign To Stop Killer Robots'.

The Digital DNA series explores the role of large-scale genetic testing in science, industry and society. We aim to understand both the benefits and risks of this emerging technology and see what the future may hold. In the finale of our Digital DNA series we talked to Dr Ian Roberts, the Chief Technology Officer of Healx. He describes how Healx uses artificial intelligence (AI) to repurpose already-approved drugs as treatments for rare diseases. IR: Healx are an AI-powered biotech, and we accelerate the discovery and development of treatments for rare diseases.