A new US State Department-funded study calls for a temporary ban on the creation of advanced AI passed a certain threshold of computational power. The tech, its authors claim, poses an'extinction-level threat to the human species.' The study, commissioned as part of a 250,000 federal contract, also calls for'defining emergency powers' for the American government's executive branch'to respond to dangerous and fast-moving AI-related incidents' -- like'swarm robotics.' Treating high-end computer chips as international contraband, and even monitoring how hardware is used, are just some of the drastic measures the new study calls for. The report joins of a chorus of industry, governmental and academic voices calling for aggressive regulatory attention on the hotly pursued and game-changing, but socially disruptive, potential of artificial intelligence.

Speaker comparison, the process of finding the speaker similarity between two speech signals, occupies a central role in a variety of applications---speaker verification, clustering, and identification. Speaker comparison can be placed in a geometric framework by casting the problem as a model comparison process. For a given speech signal, feature vectors are produced and used to adapt a Gaussian mixture model (GMM). Speaker comparison can then be viewed as the process of compensating and finding metrics on the space of adapted models. We propose a framework, inner product discriminant functions (IPDFs), which extends many common techniques for speaker comparison: support vector machines, joint factor analysis, and linear scoring.

Deep learning is great, but no, it won't be able to do everything. The only way to make progress in AI is to put together building blocks that are there already, but no current AI system combines. Adding knowledge to the mix, getting over prejudice against "good old AI", and scaling it up, are all necessary steps in the long and winding road to reboot AI. This is a summary of the thesis taken by scientist, best-selling author, and entrepreneur Gary Marcus towards rebooting AI. Marcus, a cognitive scientist by training, has been doing interdisciplinary work on the nature of intelligence -- artificial or otherwise -- more or less since his childhood.

High-level classification algorithms focus on the interactions between instances. These produce a new form to evaluate and classify data. In this process, the core is the complex network building methodology because it determines the metrics to be used for classification. The current methodologies use variations of kNN to produce these graphs. However, this technique ignores some hidden pattern between attributes and require normalization to be accurate. In this paper, we propose a new methodology for network building based on attribute-attribute interactions that do not require normalization and capture the hidden patterns of the attributes. The current results show us that could be used to improve some current high-level techniques.

Speaker comparison, the process of finding the speaker similarity between two speech signals, occupies a central role in a variety of applications---speaker verification, clustering, and identification. Speaker comparison can be placed in a geometric framework by casting the problem as a model comparison process. For a given speech signal, feature vectors are produced and used to adapt a Gaussian mixture model (GMM). Speaker comparison can then be viewed as the process of compensating and finding metrics on the space of adapted models. We propose a framework, inner product discriminant functions (IPDFs), which extends many common techniques for speaker comparison: support vector machines, joint factor analysis, and linear scoring.

We've today backed a challenge from the Prime Minister, Theresa May, to make the UK a world leader in the use of data and artificial intelligence to help transform the diagnosis and treatment of chronic diseases in the UK. Speaking in Macclesfield, the Prime Minister challenged the NHS, leading health charities and industry to accelerate progress in using Artificial Intelligence (AI) to quicken the diagnosis of conditions including heart and circulatory disease, cancer and dementia. The speech supports the Government's Industrial Strategy, which includes four Grand Challenges to put the UK at the forefront of future technologies and industries. This includes growing the artificial intelligence and data driven economy and managing an ageing society. Data science is the use of maths, statistics and computer science to get answers from large, complex data sets, while AI is the use of computer algorithms to draw conclusions from this type of data without direct human input.