If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Challenge yourself and reach for the highest bar. If you succeed, keep pushing the boundaries." This is what my friend Hassan Hajji advised when I started my career at IBM Research Tokyo in 2002, and these words have been a guiding force in my career ever since. At IBM, I was challenged to learn as much as possible about the research process in an industrial lab (prototyping ideas, patenting, publishing results), and it dovetailed nicely with my desire to work toward a Ph.D. in systems biology. After receiving my doctorate, which allowed me to enhance my skills in computational and mathematical analysis to understand complex biological systems, I was ready for a new challenge. I left Japan to work in the U.K. at a small startup, ecrebo,a which provides a coupon-issuing system for retailers who seek to attract customers based on their individual purchasing habits. I was responsible for developing a backend server for the coupon system. It had to be able to analyze the contents of the receipt, determine whether it met the conditions for issuing the coupon, and return it within three seconds, including communication time with the POS system.
Apprentice.io, a startup developing a conversational AI and augmented reality platform for pharmaceutical, biotech, and chemical companies, today announced it has raised $7.5 million. CEO and cofounder Angelo Stracquatanio says the capital will enable Apprentice to scale to accommodate customer growth attributable to the pandemic. A shortage of lab workers is hastening the adoption of automation-driven "augmentation" technologies. An American Society for Clinical Pathology study revealed that the increasing workload is compelling lab managers to hire recent graduates or candidates with bachelor's degrees but no laboratory training. Automation and digital guidance tools like Apprentice's can upskill young professionals while ensuring quality standards aren't compromised.
Artificial intelligence (AI) has now moved beyond its initial hype towards becoming a key part of the pharma industry – with many companies looking to partner with AI drug discovery start-ups. Pharma and healthcare are data-rich industries and AI helps by turning data into actionable insights, allowing us to solve complex, intricate problems. Using machine learning, AI algorithms can generate patterns that will enable us to predict toxicity, find potential combination treatments, identify and predict new drugs and expand usage of current drugs in other diseases. However, only a handful of companies from the swarm of AI start-ups have successfully gained traction within the pharma industry. Over the past month, I've had conversations with several growing AI drug discovery companies and have analysed some critical strategic shortcomings that can frustrate the upwards journey of these start-ups: AI cannot be built in isolation without understanding the nuances and the complexity of the business needs it will address.
New AI technologies are helping scientists to sort through the wealth of COVID-19 papers -- hopefully hastening the research process.Credit: Adapted from Getty The COVID-19 literature has grown in much the same way as the disease's transmission: exponentially. But a fast-growing set of artificial-intelligence (AI) tools might help researchers and clinicians to quickly sift through the literature. Driven by a combination of factors -- including the availability of a large collection of relevant papers, advances in natural-language processing (NLP) technology and the urgency of the pandemic itself -- these tools use AI to find the studies that are most relevant to the user, and in some cases to extract specific findings from the results. Beyond the current pandemic, such tools could help to bridge fields by making it easier to identify solutions from other disciplines, says Amalie Trewartha, one of the team leads for the literature-search tool COVIDScholar, at the Lawrence Berkeley National Laboratory in Berkeley, California. The tools are still in development, and their utility is largely unproven.
Small startups and big companies alike are recognizing that modern biotech R&D is as much a data ... [ ] problem as a science problem. Cloud technologies offer a way to bring together massive amounts of complex data to improve the way we feed, fuel, heal, and build our world with biology. These days, biotech R&D is as much a data problem as a science problem. Here's why: in the past decade, the exploding field of synthetic biology has done an incredible job solving the scientific challenges of making biology easier to engineer. I have written about how tools like gene editing, synthesis, sequencing, and automation are changing for the better the way we feed, fuel, heal, and build our world with biology.
As technologies like single-cell genomic sequencing, enhanced biomedical imaging, and medical "internet of things" devices proliferate, key discoveries about human health are increasingly found within vast troves of complex life science and health data. But drawing meaningful conclusions from that data is a difficult problem that can involve piecing together different data types and manipulating huge data sets in response to varying scientific inquiries. The problem is as much about computer science as it is about other areas of science. That's where Paradigm4 comes in. The company, founded by Marilyn Matz SM '80 and Turing Award winner and MIT Professor Michael Stonebraker, helps pharmaceutical companies, research institutes, and biotech companies turn data into insights.
Drone firm Zipline has been given the go-ahead to deliver medical supplies and personal protective equipment to hospitals in North Carolina. The firm will be allowed to use drones on two specified routes after the Federal Aviation Administration granted it an emergency waiver. It is the first time the FAA has allowed beyond-line-of-sight drone deliveries in the US. Experts say the pandemic could help ease some drone-flight regulations. Zipline, which has been negotiating with the FAA, wants to expand to other hospitals and eventually offer deliveries to people's homes.
Speech analytics technologies are used to extract information at customer contact points across various channels such as voice, chat, email, social channels, and surveys. Across the world, voice and phone interaction is the most common mode of communication used by consumers. Therefore, speech analytics is used in Voice User Interface (VUI) to derive insights at different contact points. In current times, organizations across various industry sectors are undertaking programs for transcripting and analyzing customer and organizational media. This is mainly to take logical decisions for customer and business management with the help of speech and text intelligence.
As countries around the world are gradually reopening following lockdowns, government authorities are using surveillance drones in an attempt to enforce social distancing rules. In India, police are using AI-equipped drones developed by US start-up Skylark Labs to monitor evening curfews and the distance between people who are outside during the day. The drones are being flown in six cities in the northern state of Punjab, and are also being trialled in the southern city of Bangalore, says Skylark Labs CEO Amarjot Singh. Each drone is fitted with a camera and an AI that can detect humans within a range of 150 metres to 1 kilometre. If it spots people it can send an alert to police in the district located nearest to the sighting.
NEW YORK (Reuters) - After a week or so sick in bed in their New York City apartment in March, members of the Johnson-Baruch family were convinced they had been stricken by the novel coronavirus. Subsequent test results left them with more questions than answers. Tests both for the virus itself and for the antibodies the immune system produces to fight the infection are becoming more widely available, but they are not perfect. For Maree Johnson-Baruch, her husband, Jason Baruch, and their two teenage daughters, their experience ran the gamut. They all became sick around the same time with the same symptoms.