The social care crisis – as demonstrated with the Conservative Party's disastrous manifesto pledge – is one of the biggest issues facing the NHS. Spending squeezes have led to bed-blocking in hospitals; while low wages and poor working conditions are causing carers to leave the industry in droves. One social care startup thinks that a solution might lie in AI. Cera, founded by Ben Maruthappu, a former innovation adviser to NHS England, is a startup that wants to provide smarter social care using an Uber-style platform to match carers and patients. The startup has to date raised £2.7 million in early funding, and in March signed a partnership with Barts Health NHS Trust, as well as several clinical commissioning groups and hospitals in London to test its solution.

TECHNOLOGY FOR PEOPLE Digital disruption is taking a new direction with people now shaping technology to fit our need. By amplifying people and putting the power into their hands, banks can deepen their role in consumers' lives, and firmly establish their place as partners in the new digital economy. HELP WRITE THE NEW RULES OF ENGAGEMENT OR RISK BEING REGULATED OUT THE UNCHARTED BANKERS SAY: • Industry regulations have not kept pace with technology advancement (66% globally, 82% in US). THE UNCHARTED TAKE THE LEAD TO SHAPE THE NEW RULES 75% of bankers agree they have a duty to be proactive in writing the rules. Freedom to innovate THOSE THAT DO EXPECT MORE: Opportunity to develop standards that others follow Expanded opportunities for trusted partnerships 6. www.accenture.com/bankingtechvision

You enter your password incorrectly too many times and get locked out of your account; your colleague sets up access to her work email on a new device; someone in your company clicks on an emailed "Google Doc" that is actually a phishing link -- initially thought to be how the recent spread of the WannaCry computer worm began. Each of these events leaves a trace in the form of information flowing through a computer network. But which ones should the security systems protecting your business against cyber attacks pay attention to and which should they ignore? And how do analysts tell the difference in a world that is awash with digital information? The answer could lie in human researchers tapping into artificial intelligence and machine learning, harnessing both the cognitive power of the human mind and the tireless capacity of a machine.

Summary: What are the earliest seeds of artificial intelligence? To whom do we owe thanks for starting us down this path? Many modern researchers to be sure, but the earliest is Leonardo Torres of Spain, in about 1914. As data scientists it's very cool to be at the forefront in this age of techno-optimism. Since the awakening of the digital age calculated by economic researchers to have begun about 1994, a wave of increased productivity has been credited to computer-related innovations resulting in higher standards of living for many if not most.

A Discriminative Deep Forest (DisDF) as a metric learning algorithm is proposed in the paper. It is based on the Deep Forest or gcForest proposed by Zhou and Feng and can be viewed as a gcForest modification. The case of the fully supervised learning is studied when the class labels of individual training examples are known. The main idea underlying the algorithm is to assign weights to decision trees in random forest in order to reduce distances between objects from the same class and to increase them between objects from different classes. The weights are training parameters. A specific objective function which combines Euclidean and Manhattan distances and simplifies the optimization problem for training the DisDF is proposed. The numerical experiments illustrate the proposed distance metric algorithm.

Innovation diffusion has been studied extensively in a variety of disciplines, including sociology, economics, marketing, ecology, and computer science. Traditional literature on innovation diffusion has been dominated by models of aggregate behavior and trends. However, the agent-based modeling (ABM) paradigm is gaining popularity as it captures agent heterogeneity and enables fine-grained modeling of interactions mediated by social and geographic networks. While most ABM work on innovation diffusion is theoretical, empirically grounded models are increasingly important, particularly in guiding policy decisions. We present a critical review of empirically grounded agent-based models of innovation diffusion, developing a categorization of this research based on types of agent models as well as applications. By connecting the modeling methodologies in the fields of information and innovation diffusion, we suggest that the maximum likelihood estimation framework widely used in the former is a promising paradigm for calibration of agent-based models for innovation diffusion. Although many advances have been made to standardize ABM methodology, we identify four major issues in model calibration and validation, and suggest potential solutions.

New system for i-vector speaker recognition based on variational autoencoder (VAE) is investigated. VAE is a promising approach for developing accurate deep nonlinear generative models of complex data. Experiments show that VAE provides speaker embedding and can be effectively trained in an unsupervised manner. LLR estimate for VAE is developed. Experiments on NIST SRE 2010 data demonstrate its correctness. Additionally, we show that the performance of VAE-based system in the i-vectors space is close to that of the diagonal PLDA. Several interesting results are also observed in the experiments with $\beta$-VAE. In particular, we found that for $\beta\ll 1$, VAE can be trained to capture the features of complex input data distributions in an effective way, which is hard to obtain in the standard VAE ($\beta=1$).

Biomedical researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a new recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies. It also can be customized to fit the needs of different scenarios. Ontology Recommender 2.0 combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available.

The days of forgetting to stock up on household essentials because you've forgotten what is in the fridge at home could be at an end. A new gadget from tech firm Bosch will allow shoppers to see exactly what they've got in stock from their mobile phone. From today the firm will start selling mini-cameras which can be installed inside a fridge are connected to an app on someone's phone. Bosch has created a gadget that connects a camera installed inside the fridge to an app on a phone, allowing the user to see what they've got in stock This will allow that person to see exactly what is inside wherever they may be – whether at work, or browsing the aisles in their local supermarket. Shoppers can even zoom to check exactly how many eggs they have, for example, or if there are enough vegetables in the drawer. It is part of a range of gadgets which have been launched by Bosch, as part of its smart home range which will connect dozens of appliances to mobile phones.

Let's hear it for the written word. Learning to read can have profound effects on the wiring of the adult brain – even in regions that aren't usually associated with reading and writing. That's what Michael Skeide of the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, and his colleagues found when they taught a group of illiterate adults in rural India to read and write. Skeide and his colleagues wanted to study how culture changes the brain, so focused on reading and writing. These cultural inventions have appeared only recently in our evolutionary history, so we haven't had a chance to evolve specific genes for such skills.