Just what i find

Driving increased "data gravity" means customers are less likely to divert new data workloads to alternative platforms, and SalesForce's two recent acquisitions – MuleSoft (a data integration and transformation company) for $6.5 billion in March (https://www.fool.com/investing/2018/03/23/salesforcecom-makes-a-transformative-move-for-the.aspx) and Datorama (cloud AI for marketing) for $800 million (https://www.fool.com/investing/2018/07/27/salesforce-strengthens-its-ai-capabilities-with-an.aspx) further highlight their desire to make it as easy Continue reading →

Recent advances in AI mean that it would now be possible to develop autonomous weapons – systems which are capable of making automated decisions to take human life. Elon Musk, DeepMind and others have signed a pledge never to create AI weapons: "We the undersigned agree that the decision to take a human life should Continue reading →

A big step towards making devices like Alexa or Siri (or more likely Google Assistant, given that this research comes from DeepMind) better understand humans is the development of "theory of mind". By around 4 years old, human children can understand that their beliefs may diverge from those of others, and that understanding that divergence Continue reading →

Among many promising applications for AI in medicine, cardiology is one with the greatest potential. Current clinical practice calls for manual analysis of a wide range of complex diagnostic imagery, and this analysis is time consuming and error prone, even for the most experienced doctors. Advances in the technology are hampered by ethical concerns that Continue reading →

Following the controversy around (and expiration of) Google's $15 million contract with the US Department of Defense (https://mashable.com/2018/06/02/google-defense-department-project-maven-contract-not-renewed/?europe=true#ebCfKFgiPPqN), the US government has now signed an $885 million contract with Booz Allen – and i'm willing to bet that there will be far less public debate around the ethics of the applications of technology under this Continue reading →

Yet another example of the value of simulated training, researchers at OpenAI trained a robotic hand using hundreds of years of  object manipulation inside a computer simulation. The resulting hand movements are significantly more dexterous than anything developed so far. https://www.technologyreview.com/s/611724/artificial-intelligence-driven-robot-hand-spends-a-hundred-years-teaching-itself-to-rotate/ A reinforcement-learning algorithm allows Dactyl to learn physical tasks by practicing them in a virtual-reality Continue reading →

In an interesting piece of research intended to highlight the biases embedded in AI systems and training data, a team at the University of Melbourne produced a system capable of making assessments of physical attributes and the emotional state of people in a photo. Hidden in the assessments are a range of biases – gender Continue reading →

Two years after the unveiling of the original Tensor Processing Unit, Google's announced "Edge TPU" – tiny AI accelerator chips designed to be embedded in IoT devices. Models will be trained on large, server clusters like today, and then embedded in edge devices in factories or workshops – perhaps analysing samples for quality control, processing Continue reading →

In a major breakthrough, researchers from Deep Mind have improved the accuracy of AI lip reading, with half the error rate of previous methods, and over 50% accuracy. If embedded in to smart devices, it could make lip reading accessible to anyone with a smartphone – both helping the many people who struggle in noisy Continue reading →

One of the questions we often ask in interviews is for a candidate to talk about a piece of data they've seen recently which surprised or interested them – an interest in data journalism is (for my team) an indicator of a person interested in numbers, a prerequisite for a successful career in data and Continue reading →