Mark Zuckerberg and his wife Priscilla Chan have announced they are going to heal the world and make it a better place. Except we all know those two dance like your dad. Looking like two humanoids from a snazzy Artificial Intelligence launch, Zuckerberg and Chan announced their plan to'cure, prevent or manage all human disease by the end of the century'. Looking like two humanoids from an AI launch, Mark Zuckerberg and his wife announced last Tuesday their 3billion plan to'cure, prevent or manage all human disease by the end of the century' They may need to cure my scepticism first. I wouldn't trust a guy with 365 identical grey t-shirts to cure a hangover.

The literature on judgment aggregation is moving from studying impossibility results regarding aggregation rules towards studying specific judgment aggregation rules. Here we give a structured list of most rules that have been proposed and studied recently in the literature, together with various properties of such rules. We first focus on the majority-preservation property, which generalizes Condorcet-consistency, and identify which of the rules satisfy it. We study the inclusion relationships that hold between the rules. Finally, we consider two forms of unanimity, monotonicity, homogeneity, and reinforcement, and we identify which of the rules satisfy these properties.

Motivated by the need to automate medical information extraction from free-text radiological reports, we present a bi-directional long short-term memory (BiLSTM) neural network architecture for modelling radiological language. The model has been used to address two NLP tasks: medical named-entity recognition (NER) and negation detection. We investigate whether learning several types of word embeddings improves BiLSTM's performance on those tasks. Using a large dataset of chest x-ray reports, we compare the proposed model to a baseline dictionary-based NER system and a negation detection system that leverages the hand-crafted rules of the NegEx algorithm and the grammatical relations obtained from the Stanford Dependency Parser. Compared to these more traditional rule-based systems, we argue that BiLSTM offers a strong alternative for both our tasks.

Causal inference concerns the identification of cause-effect relationships between variables, e.g. establishing whether a stimulus affects activity in a certain brain region. The observed variables themselves often do not constitute meaningful causal variables, however, and linear combinations need to be considered. In electroencephalographic studies, for example, one is not interested in establishing cause-effect relationships between electrode signals (the observed variables), but rather between cortical signals (the causal variables) which can be recovered as linear combinations of electrode signals. We introduce MERLiN (Mixture Effect Recovery in Linear Networks), a family of causal inference algorithms that implement a novel means of constructing causal variables from non-causal variables. We demonstrate through application to EEG data how the basic MERLiN algorithm can be extended for application to different (neuroimaging) data modalities. Given an observed linear mixture, the algorithms can recover a causal variable that is a linear effect of another given variable. That is, MERLiN allows us to recover a cortical signal that is affected by activity in a certain brain region, while not being a direct effect of the stimulus. The Python/Matlab implementation for all presented algorithms is available on https://github.com/sweichwald/MERLiN

DeepBench is an open source benchmarking tool that measures the performance of basic operations involved in training deep neural networks. These operations are executed on different hardware platforms using neural network libraries. Deepbench is available as a repository on github. The primary purpose of DeepBench is to benchmark operations that are important to deep learning on different hardware platforms. Although the fundamental computations behind deep learning are well understood, the way they are used in practice can be surprisingly diverse.

On 19 September the chief executive of the Law Society, Catherine Dixon, delivered a keynote address at the International Bar Association conference in Washington DC. The Law Society is the professional body that represents more than 170,000 solicitors in England and Wales. Our vision is to be valued and trusted as a vital partner to represent, promote and support solicitors while upholding the rule of law, legal independence, ethical values and the principle of justice for all. We also fulfil an important public interest function which aims to ensure access to justice, protect human rights and freedoms and uphold the rule of law. As part of our work to develop our strategy, we published a piece of research to identify what the future will bring for the legal profession.

All those cars on California's famously gridlocked highways could be doing more than using energy. They could be producing it. The California Energy Commission is investing 2 million to study whether piezoelectric crystals can be used to produce electricity from the mechanical energy created by vehicles driving on roads. The commission is choosing a company or university to take on small-scale field tests. It will study how the small crystals, which generate energy when compressed, could produce electricity for the grid if installed under asphalt.

They were dismissed as stupid and primitive by the archaeologists who first studied their fossilised bones, but it seems Neanderthals may have been just as chatty as our own species. Researchers have discovered evidence that suggests Neanderthals may have used vocal communication just like our own species Homo sapiens. They used 3D scans to analyse the delicate ear bones from both the fossilised remains of Neanderthals and modern humans. Scientists have found evidence that suggests Neanderthals (reconstruction pictured) may have communicated vocally in similar ways to modern humans. Using highly detailed'micro-CT' scans they were able to reconstruct how the ear bones, or ossicles, would have functioned when Neanderthals were alive.

Machine learning applications for NBA coaches and players might seem like an odd choice for me to write about. Let us get something out of the way: I don't know much about basketball. However, one of the perks of working in data science and machine learning is that I can still say somewhat insightful things about sports, as long as I have data. So with that expertise I'll weigh in to offer some machine learning applications for basketball. During a conversation with my good colleague Ray Wright, who does know quite a bit about basketball and had been looking at historical data from NBA games, we suddenly realized something about player shooting.

Healthtech, Fintech and AI dominated Techstars London Demo day today in London. At a packed venue (the famous Royal Institution, no less) the teams demo'd their products in short pitches. Here is a run-down of the teams, with some more details of those that stood out. You can watch a Facebook Live recording of the demos here. Didimo They say: "Didimo creates Virtual Avatars ready to be animated with one photo."