DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanism such as multiprocessing and SCOOP. The following documentation presents the key concepts and many features to build your own evolutions.
A vital component of trust and transparency in intelligent systems built on machine learning and artificial intelligence is the development of clear, understandable documentation. However, such systems are notorious for their complexity and opaqueness making quality documentation a non-trivial task. Furthermore, little is known about what makes such documentation "good." In this paper, we propose and evaluate a set of quality dimensions to identify in what ways this type of documentation falls short. Then, using those dimensions, we evaluate three different approaches for eliciting intelligent system documentation. We show how the dimensions identify shortcomings in such documentation and posit how such dimensions can be use to further enable users to provide documentation that is suitable to a given persona or use case.
Nearly half of NHS trusts (43%; obtained from a Freedom of Information (FoI) request) are investing in artificial intelligence (AI) enabling patients to'self-help' when accessing services. The trusts are harnessing technology such as virtual assistants, speech recognition technology and chat bots to ease the pressure on healthcare workers across their organisations. These vital investments are geared up to primarily provide access to information and services all-day, every-day, but they also play a key role in reducing the numbers of patients queuing to see their GP for information they can now access through a virtual assistant. Research commissioned by Nuance in 2015 into the impact of clinical documentation in NHS acute care trusts revealed that clinicians spend over half of their work day on clinical documentation. In a more recent Nuance study of UK GP practices, over nine in 10 reported that patient documentation was a considerable burden for their practice and that in 49 per cent of the practices, over half their patient documentation is paper versus electronic format.
Japan and other major fishing countries will likely introduce an international documentation system to better keep track of Pacific bluefin tuna catches as a step against overfishing, sources said Tuesday. The documentation plan is designed to certify fishing ports and methods to prevent illegal fishing and trade, and provide information such as catch volumes and their shipping destinations. The launch of the catch documentation system, which is expected to be discussed at an international conference in September in Fukuoka Prefecture, is intended to help restore depleted stocks of the Pacific tuna. Since 2015, fishing of the tuna has been regulated. In Japan, local fisheries associations gather data on bluefin tuna catches and report them to the Fisheries Agency, but there have been cases of unauthorized fishing that go unreported.