Boost My Business shines a spotlight on a tech start-up whose app maps accessibility via its users and AI. Fiona Alston chatted to Matthew McCann CEO of Access Earth about how his app helps users find businesses which have the accessibility requirements for their particular needs. McCann has cerebral palsy and uses a rollator to get around, and it's his personal experience of trying to access businesses like restaurants and hotels which proved the need for the software. "Growing up it was difficult for me to find accessibility information whether it was going out to eat somewhere or going to the shops and for me that's a really important thing to know ahead of time," says McCann. "I realised then going into college I wanted to be able to do something about that - figuring out the world isn't accessible at the moment and I wanted to make that change," he says.
An MIT and Intel research team has developed an algorithm capable of creating algorithms. And before we start fantasizing about Skynet and other apocalyptic dystopias, all this really means is the ability for a machine to automate programming so that in turn a programmer can automate a wide range of tedious or repetitive tasks or, pushing it to its limit, that anyone can program simply by describing the tasks they want to perform. The system, machine inferred code similarity (MISIM), learns what a piece of software intends to do by studying the structure of the code and analyzing syntactic differences of other codes with similar behavior. The idea of computers capable of programming themselves from instructions given in natural language has been around for some time and has already been put into practice via several initiatives of development platforms or NCDPs, under the umbrella of the so called No Code movement. More and more companies, particularly startups with the capacity to design their systems from scratch, are developing structures based on code written by third parties or taken from repositories and platforms, which is assembled into pieces.
By Sumit Pandey Taoyuan City (Taiwan), Sep 20 (UNI) Even as the world awaits a COVID vaccine, Artificial intelligence (AI) can be used for detecting pneumonia caused by the pandemic which has claimed nearly a million lives globally. The dataset commonly used for this work is open source chest X-ray images from Kaggle or other open-source websites. Some of these models have reported an accuracy even greater than 98 percent, experts have said. The experts while calling for integrating the AI systems into the medical practice, said it would build a mutually-beneficial relationship between AI and Medicine. In future AI would offer greater efficiency or cost-effectiveness and Doctors (or Medical Staff) would offer AI the essential medical exposure of complex cases.
The Cambridge Dictionary defines "bootstrap" as: "to improve your situation or become more successful, without help from others or without advantages that others have." While a machine learning algorithm's strength depends heavily on the quality of data it is fed, an algorithm that can do the work required to improve itself should become even stronger. A team of researchers from DeepMind and Imperial College recently set out to prove that in the arena of computer vision. In the updated paper Bootstrap Your Own Latent – A New Approach to Self-Supervised Learning, the researchers release the source code and checkpoint for their new "BYOL" approach to self-supervised image representation learning along with new theoretical and experimental insights. In computer vision, learning good image representations is critical as it allows for efficient training on downstream tasks. Image representation learning basically leverages neural networks that have been trained to produce good representations.
One study estimated that pharmaceutical companies spent US$2·6 billion in 2015, up from $802 million in 2003, for the development of a new chemical entity approved by the US Food and Drug Administration (FDA). N Engl J Med. 2015; 372: 1877-1879 The increasing cost of drug development is due to the large volume of compounds to be tested in preclinical stages and the high proportion of randomised controlled trials (RCTs) that do not find clinical benefits or with toxicity issues. Given the high attrition rates, substantial costs, and low pace of de-novo drug discovery, exploiting known drugs can help improve their efficacy while minimising side-effects in clinical trials. As Nobel Prize-winning pharmacologist Sir James Black said, "The most fruitful basis for the discovery of a new drug is to start with an old drug". New uses for old drugs.
Ahead of the U.S. presidential election on November 3, IBM today announced it's working with states to put information into the hands of potential voters. Using the AI and natural language processing capabilities of Watson Assistant, IBM says it's helping field voter queries online and via phone by advising people on polling place locations, voting hours, procedures for requesting mail-in ballots, and deadlines. Research from the Pew Center indicates that nearly half of all U.S. voters expect to have difficulties casting a ballot due to the coronavirus pandemic. In a recent NPR/PBS NewsHour/Marist Poll, 41% of those surveyed said they believed the U.S. is not very prepared or not at all prepared to keep November's election safe and secure. IBM's election-focused Watson Assistant offering taps Watson Discovery to surface information about voting logistics from federal, state, and county websites; local news reports; and government documents.
Stopping the spread of infectious disease has taken on a new urgency. But what's the best way to check large groups of people for signs of illness? One option is to set up a fever screening station. Thermal screening stations are not a new concept. Many of us have walked through them in airports or hospitals.
On September 18th The Lancet Digital Health released an article called " Artificial intelligence in COVID-19 drug repurposing" (written by Yadi Zhou, PhD, Prof Fei Wang, PhD, Prof Jian Tang, PhD, Prof Ruth Nussinov, PhD, Prof Feixiong Cheng, PhD) in the article it explained how artificial intelligence is being used for drug reproposing,which is where an already existing is drug used to fight novel diseases such as COVID-19. Artificial intelligence is being used to speed up this process, with the exponential growth in computing power, memory storage and a plethora of data its only right for the medical sector to use this to speed up a process that help fight against the worlds latest threat that is COVID-19. So how is artificial intelligence being used to speed up this process, well the article explains how artificial intelligence used for extracting hidden patterns and evidence from biomedical data, which otherwise would have been done manually saving a considerable amount of time. In connection to the medical sector, artificial intelligence in medicine may be racially biased. Just like explained above artificial intelligence has transformed the healthcare and has really cut the time on many aspects of medicine such as making a breast or lung cancer diagnosis based on imaging studies, or deciding when patients should be discharged in a matter of second which is just incredible, but like all good things it comes with its flaws.