There should be a new Hippocratic Oath to ensure patient safety in the modern age of medicine that includes people working in healthcare technology, according to a doctor and medical entrepreneur. Dr Jordan Shlain, Founder of Private Medical, made the comments at the CogX AI conference in King's Cross this week. The UK's medical tech sector is worth £7.6billion and employs 115,000 people across 3,700 companies. "Medicine is not just algorithms, there is a lot of humanity and emotions that goes into an interaction," he said. Highlighting the increased spending on healthcare in the UK, alongside a dip in lifespan and satisfaction scores, he said that while advances in AI have the potential to revolutionise healthcare, tech providers must distinguish consumers from patients and take responsibility for their actions.

Today, Microsoft is releasing The Future Computed: AI and Manufacturing. This new book provides an in-depth look at how artificial intelligence (AI) is transforming the manufacturing sector by optimizing digital operations and driving efficiencies, enabling new products and services, and allowing for safer work environments. The book also offers a timely look at how society can respond to some of the challenges AI creates, and the need to develop new laws and regulations to address workforce disruption and develop AI in an ethical and responsible manner. Written by Greg Shaw – co-author of Hit Refresh with Microsoft CEO Satya Nadella and The Ability Hacks about technology for people with disabilities – this book is the second in a series that began with the release last year of The Future Computed: Artificial Intelligence and its role in society. In an era when digital technology is changing almost every aspect about how people live, work, play, and learn, we believe it is important to think carefully about the complex questions that AI raises.

Special report ImageNet – a data set used to train AI systems around the world – contains photos of naked children, families on the beach, college parties, porn actresses, and more, scraped from the web to train computers without those individuals' explicit consent. The library consists of 14 million images, each placed into categories that describe what's pictured in each scene. This pairing of information – images and labels – is used to teach artificially intelligent applications to recognize things and people caught on camera. The database has been downloaded by boffins, engineers, and academics to train hundreds if not thousands of neural networks to identify stuff in photos – from assault rifles and aprons to magpies and minibuses to zebras and zucchinis, and everything in between. In 2012, the data set was used to build AlexNet, heralded as a breakthrough development in deep learning since it marked the first time a neural network outperformed traditional computational methods at object recognition in terms of accuracy.

Mumbai (Maharashtra) [India] October 12 (ANI/NewsVoir): Artificial Intelligence (AI) being perceived as a key for transformation of technology, even smaller companies are seen implementing machine learning within their products. ClinicSpots is one such Mumbai based mid-sized healthcare start-up to have introduced an innovative medical Q and A platform that makes use of NLP. The system tries to understand any patient query and displays the result in 3 forms: A direct answer, list of similar links related to the topic, other similar questions with answered. "For ClinicSpots it is crucial to maintain quality of content while expanding its user base. With hundreds of medical queries being posted each day on our portal, it become essential to automate this process. Hence we have introduced NLP to handle the patient queries better," said Pankaj Srivastava, Founder and CEO of ClinicSpots.

Underground penetration and exploration technologies have a long history and can be exploited in many sectors, such as agriculture, for example, to define soil water content1; geology, for example, for terrain seismic profiling2 and underground characterization3; and the oil and gas industry4 or construction, for example, for mapping and maintenance of underground utility service infrastructures5 and tunneling.6 Autonomous solutions, which can monitor the surrounding environment, make decisions, and adjust their behavior for improving penetration and exploration, could help make the process faster, more reliable, cheaper, and safer for humans and underground infrastructures.7 However, robotic solutions for such applications are still very limited,8–13 due to the strong constraints imposed on the movement of autonomous systems below ground by the physics of such a cluttered environment (i.e., high pressure and friction, stratifications with different soil impedance, and rocks). Ideally, a robotic system moving in soil should be able to adapt its actions to unpredictable constraints, avoiding or navigating around obstacles or sensitive objects, for example, to prevent damaging underground pipes or objects of the cultural heritage. However, they have a limited possibility of perception compared to aboveground robots, which for instance can take advantage of vision. Thus, within the soil, a possible strategy for movement and exploration is for the morphology of the body to adapt itself to the soil structure. Morphological adaptation in artificial solutions has been particularly exploited in the field of soft-bodied robotic systems,14,15 where soft materials are adopted for the deformation of soft artificial bodies, for moving through small gates16,17 or navigating cluttered environments, for example, by exploiting the passive buckling ability of soft inflatable structures in a robot, without the use of a sensory perception or bending control.18 Material properties or soft actuators are used for enhancing robot abilities.19 In fact, the adaptation provided by soft materials and actuators can effectively improve robot behaviors while decreasing the control complexity.20,21

A new flu vaccine designed by artificial intelligence has gone on trial in the United States in what researchers are claiming is a world first. Scientists at Flinders University in Australia have developed what they describe as a "turbo-charged" flu vaccine with an extra component that stimulates the human immune system to make more antibodies against the flu virus than a normal vaccine, thus making it more effective. Nikolai Petrovsky, professor of medicine at Flinders University in Australia and the lead researcher on the vaccine, said that as far as he knew this was the first time a flu vaccine had been developed using AI that had progressed to a trial in humans. He said that the use of AI had accelerated the vaccine discovery process, cut costs massively and had enabled the development of a more effective vaccine. He said using AI streamlined the vaccine development process.

The Institute of Physics (IOP) is convening a new type of forum – four days of discussion, debate and knowledge sharing at the IOP's flagship King's Cross building. Members of IOP special interest groups, including leading thinkers in the physics community in the UK and Ireland, will host discussions, talks, meetings and panels to foster debate and exploration of key topics such as oceans and the climate, optics in quantum technologies and machine learning. IOP member-led special interest groups are at the heart of the physics community and enable you to take part in activities in your particular areas of interest, share and receive expert advice on developments in your sector, grow your network across disciplines, attend topical and inter-disciplinary sessions. A drinks reception will be held at the end of each day, where you can meet speakers and the organising committees.

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For Google it was a historic announcement: a declaration that it had won the race to achieve "quantum supremacy" – the moment that a futuristic quantum computer performed a task that stumped even the most powerful standard computer in the world. But for all the fanfare, which saw Google's CEO Sundar Pichai compare the feat to building the first rocket to reach space, the claim has sparked a bunfight. The tech firm's rival, IBM, was swift to dismiss the excitement. Google has not, it asserts, achieved the highly prized goal of quantum supremacy. Google published its claim in the journal Nature on Wednesday after an earlier report on the work appeared briefly on a Nasa website last month. The paper describes how a team led by John Martinis, leader of the research team working on quantum supremacy, built a superconducting quantum processor named Sycamore that harnesses the weirdness of quantum physics to crunch through thorny problems.

The MLOps Conference took place earlier this week at Hudson Mercantile in New York City. Experts from the New York Times, Twitter, Netflix and Iguazio, the host company, spoke about best practices and machine learning implementation throughout a variety of different organizations. I learned of the technological void that exists when data scientists want to implement machine learning. With this new context in mind, I can approach conversations with our data team from a new perspective, and take the time to understand how we can implement new models on our team. Machine learning as a technology has been around for more than 50 years, beginning with Arthur Samuel's pioneering work at IBM where his program helped the computer improve with each game of checkers it played in 1952.