Google has completed a controversial take-over of the health division of its UK AI acquisition, DeepMind. The personnel move had been delayed as National Health Service (NHS) trusts considered whether to shift their existing DeepMind contracts -- some for a clinical task management app, others involving predictive health AI research -- to Google. In a blog post yesterday Dr Dominic King, formerly of DeepMind (and the NHS), now UK site lead at Google Health, confirmed the transfer, writing: "It's clear that a transition like this takes time. Health data is sensitive, and we gave proper time and care to make sure that we had the full consent and cooperation of our partners. This included giving them the time to ask questions and fully understand our plans and to choose whether to continue our partnerships. As has always been the case, our partners are in full control of all patient data and we will only use patient data to help improve care, under their oversight and instructions."

Decision Point has unlimited potential in all verticals and sectors and can deliver information in a useful format on which to base decisions. In response to growing concerns around the operation and accountabilities of AI algorithms and the potential for legislation or certification of AI's Decision Point has decided to adopt an Operational Passport approach. The AI Operational Passport is linked to the existing augmented intelligence platforms capacity to create regulatory point in time reporting. The functionality for the AI Operational Passport already exists as it is fundamental to defence and security to have traceability on decision making for oversight and legality of actions. With the levels of complexity and constant market movement experienced by organisations, enterprises, divisions defining the right question can often be a huge and expensive process.

Local authorities in Shanghai last week have issued licenses – the first in China – for operational tests of smart and connected cars with passengers in them, that would pave the way for commercial robotaxis in the future. The licenses were given to car-hailing ride service Didi Chuxing as well as to car manufacturer SAIC Motor and BMW that allow them to conduct autonomous driving projects in real urban scenarios in Shanghai's Jiading district, local government officials announced at last week's World Autonomous Vehicle Ecosystem Conference. Each of the three companies are permitted to run 50 vehicles for pilot programs including robotaxis, unmanned deliveries and other autonomous driving services. The license holders can increase the number of test vehicles after six months if there are no traffic violations. The city issued China's first licenses on autonomous vehicle (AV) tests to SAIC and EV maker Nio in March 2018, with only company employees allowed to ride in the vehicles during tests.

Almost two years ago, Dennis Degray sent an unusual text message to his friend. "You are holding in your hand the very first text message ever sent from the neurons of one mind to the mobile device of another," he recalls it read. Degray, 66, has been paralysed from the collarbones down since an unlucky fall over a decade ago. He was able to send the message because in 2016 he had two tiny squares of silicon with protruding metal electrodes surgically implanted in his motor cortex, the part of the brain that controls movement. By imagining moving a joystick with his hand, he is able to move a cursor to select letters on a screen.

Long an obsession of science fiction writers, "artificial intelligence" in the modern era of fast-paced technological innovation is a term that is as ubiquitous as it is nebulous. For the payments technology industry, however, the term describes advanced analytical technology that has an outsized potential to improve the payments ecosystem for banks, payments processors, merchants and consumers. In fact, financial services companies will spend US$11 billion on AI in 2020, according to an analysis by IDC -- more than any other industry cited. They'll stand to make a nice return on their investment as well, according to PwC estimates. In North America alone, AI is projected to increase the GDP of the financial and professional services industry as much as 10 percent by 2030, driven by increases in both productivity and consumption.

Researchers at the Queensland University of Technology (QUT) have applied artificial intelligence (AI) to develop a more accurate and detailed method for analysing images of the back of the eye to help clinicians better detect and track eye diseases. In the study, the group of researchers explored a range of deep learning techniques to analyse Optical Coherence Tomography (OCT) images, said David Alonso-Caneiro, QUT senior research fellow and study lead author. OCT, which takes cross-sectional images of the eye to show different tissue layers, is a common instrument used by optometrists and ophthalmologists. These images are around four microns in size and can help clinicians detect eye diseases such as glaucoma and age-related macular degeneration. The team collected OCT chorio-retinal eye scans from an 18-month longitudinal study of 101 children with good vision and healthy eyes, and used these images to train the AI program to detect patterns and define the choroid boundaries.

Researchers at the Queensland University of Technology (QUT) have applied artificial intelligence (AI) to develop a more accurate and detailed method for analysing images of the back of the eye to help clinicians better detect and track eye diseases. In the study, the group of researchers explored a range of deep learning techniques to analyse Optical Coherence Tomography (OCT) images, said David Alonso-Caneiro, QUT senior research fellow and study lead author. OCT, which takes cross-sectional images of the eye to show different tissue layers, is a common instrument used by optometrists and ophthalmologists. These images are around four microns in size and can help clinicians detect eye diseases such as glaucoma and age-related macular degeneration. The team collected OCT chorio-retinal eye scans from an 18-month longitudinal study of 101 children with good vision and healthy eyes, and used these images to train the AI program to detect patterns and define the choroid boundaries.

According to a report published at Fortune.com, Google has achieved "quantum supremacy" with a 53-qubit quantum computer. From reading the report, it is obvious that Fortune.com Here's what this means for cryptocurrency, military secrets and all secrets which are protected by cryptography. Notably, NASA published the scientific paper at this link, then promptly removed it as soon as the implications of this technology started to become apparent to a few observers. The cover-up begins…) However, the Financial Times reported on the paper before it was removed.

New Delhi, Sep 23: A team of IIT graduates has developed an artificial intelligence (AI) powered sensor sheet that can be put under the mattress to detect indicators such as heart health, respiration, sleep, and stress with medical grade accuracy. The device works on a technology known as Ballistocardiography (BCG), which involves measurement of the movement of heart. BCG can be extended to find movement, breathing and snoring. "Our advanced algorithms have been trained over billions of data points to achieve 98.4 per cent accuracy in measuring heartbeat and respiration. The device is a contact-free health monitor and personal health companion," Mudit Dandwate, an alumnus of Indian Institute of Technology (IIT) Bombay, told PTI. "It is a thin sensor sheet that goes below the mattress and tracks heart health, respiration, sleep, stress with medical grade accuracy. Basis tracking their health data, there are experts that provide personalised health improvement plan," said Mudit, co-founder of Dozee.

Brisbane startup FloodMapp has raised $1.3 million, as it looks to take its flood-prediction tech to the rest of Australia, and into hurricane-prone areas of the US. The funding comes from several VC firms, including Allectus Capital, Transition Level Investments, Jelix Ventures and Mercurian, as well as from a number of individual investors. Founded by Juliette Murphy and Ryan Prosser, FloodMapp combines big data analytics and machine learning techniques with traditional hydrology and hydraulic modelling approaches. The tech measures river height and rainfall data in real-time, and uses underlying elevation and topography to predict how and where water will flow over the land, Murphy tells StartupSmart. This allows the team to "predict a map of the inundated areas" and share that data with third parties.