The federal government is proposing to establish an agency that will focus on robotics and Artificial Intelligence, the Minister of Science and Technology, Dr Ogbonnaya Onu has said. He disclosed this on Monday when he received a delegation of the Academy of Science in his office in Abuja. Dr Onu noted that when established, the agency will help to improve the quality of research in the nation's universities and industrial laboratories. He said the Academy of Science is well-placed to advise the federal government on issues bordering on Science, Technology and Innovation. The minister also said it was high time Nigeria takes its place among the leading nations of the world in terms of Science, Technology and Innovation.

TEACH a man how to fish, and you can feed him for a lifetime. Homegrown artificial intelligence (AI) company Xjera Labs aims to do just that, with the aid of neural networks and deep learning algorithms. Its AI engine Athena can train software to perform specific tasks, whether these pertain to recognising sushi, teaching drones to fly or spotting intruders. The company's co-founder and chief executive Ethan Chu compares Athena to a school for its "pupils" - in Xjera's case, these are its products named XIntelligence, XTransport and XHound. Taken together, the trio offers a bevy of functions, including facial recognition, emotional analysis and identifying vehicle types.

It is a classic win-win situation: In the town of Manno, located not far from Lugano in the canton of Ticino, researchers from the Dalle Molle Institute for Artificial Intelligence ( IDSIA) and experts from UBS have been working together since the end of 2018. The IDSIA benefits from concrete applications for its research, while the global banking giant aims to use data analysis to optimize its processes and expand its services. "What will genuinely change our lives in the coming years are machine learning and artificial intelligence," says Sabine Keller-Busse, UBS Group Chief Operating Officer. The collaboration was announced at the beginning of 2018 and was already launched by the end of the year, thanks in large part to the location. "The launch at our existing base in Manno was extremely favorable. We found precisely the right experts there for our needs," says Sabine Magri, UBS GCOO Chief Operating Manager.

Artificial intelligence programs are multiplying like rabbits across the federal government. The Defense Department has tested AI for predictive maintenance on vehicles and aircraft. Civilian agencies have experimented with robotic process automation. RPA pilots at the General Services Administration and the IRS helped employees save time on repetitive, low-skill tasks. In February, President Donald Trump signed an executive order expanding his administration's efforts to foster the research and development of artificial intelligence tools in government.

Decentralized artificial intelligence (AI) firm SingularityNET and tech conglomerate Cisco have partnered to develop applied artificial general intelligence (AGI) technologies. AGI is one aspect of AI technology that concentrates on learning the intellectual tasks of which humans are capable. Sometimes referred to as "Strong AI," AGI emphasizes a machine's ability to reason in uncertain situations, solve puzzles, plan and communicate in natural language. Goertzel also said that the scale of Cisco's AGI deployments will be a major driver for the firm's development, stating: "The work we've done with Cisco on smart traffic analytics using OpenCog's logical reasoning and deep neural networks just scratches the surface. Let's just say we have some much broader and deeper conversations going on."

The MIT Stephen A. Schwarzman College of Computing (SCC) will reorient the Institute to bring the power of computing and artificial intelligence to all fields at MIT, and to allow the future of computing and AI to be shaped by all MIT disciplines. To support ongoing planning for the new college, Dean Melissa Nobles invited faculty from all 14 of MIT's humanistic disciplines in the School of Humanities, Arts, and Social Sciences to respond to two questions: As Nobles says in her foreword to the series, "Together, the following responses to these two questions offer something of a guidebook to the myriad, productive ways that technical, humanistic, and scientific fields can join forces at MIT, and elsewhere, to further human and planetary well-being." The following excerpts highlight faculty responses, with links to full commentaries. The excerpts are sequenced by fields in the following order: the humanities, arts, and social sciences. "The advent of artificial intelligence presents our species with an historic opportunity -- disguised as an existential challenge: Can we stay human in the age of AI? In fact, can we grow in humanity, can we shape a more humane, more just, and sustainable world? With a sense of promise and urgency, we are embarked at MIT on an accelerated effort to more fully integrate the technical and humanistic forms of discovery in our curriculum and research, and in our habits of mind and action."

The AI Times is a weekly newsletter covering the biggest AI, machine learning, big data, and automation news from around the globe. If you want to read A I before anyone else, make sure to subscribe using the form at the bottom of this page. Toronto-based Daisy Intelligence, which has created an AI-powered platform for retail and insurance, has raised $10 million in Series A financing. "Microsoft and Eros are partnering to take Bollywood's $5B movie industry global by developing a new platform, creating new offerings, and delivering personalized content – all using Azure." You don't see a startup get a $50 million seed round all that often, but such was the case with Vianai, an early-stage startup launched by Vishal Sikka, former Infosys managing director and SAP executive.

The invasive and expensive diagnosis process of bladder cancer, which is one of the most common and aggressive cancers in the United States, may be soon helped by a novel non-invasive diagnostic method thanks to advances in machine learning research at the San Diego Supercomputer Center (SDSC), Moores Cancer Center, and CureMatch Incorporated. Research scientists Igor Tsigelny and Valentina Kouznetsova have been working on the development of a machine-learning (ML) model that looks at a patient's metabolites and their chemical descriptors. The model accurately classifies the stages of bladder cancer in a patient, according to the researchers. Tsigelny is the lead author on a recently published study in the Metabolomics journal called'Recognition of Early and Late Stages of Bladder Cancer using Metabolites and Machine Learning'. When a patient experiences early symptoms of bladder cancer (e.g., blood in urine, pain during urination, etc.), the current method of diagnosis is often a painful, invasive series of tests.

NEW DELHI: Artificial Intelligence (AI) is augmenting human lives like never before and is helping companies take the next big leap. As the AI ecosystem witnesses rapid expansion in India, Google's vice-president Jay Yagnik, who leads large parts of AI at the company, speaks to timesofindia.com We have seen that AI augments human potential as it grows in its capabilities. When it comes to the future of work, in the next 20-30 years, we see a huge potential of AI-enabled tools deeply augmenting people, everything from their search and information needs to unlocking their true potential. Plus, we actually think that by taking an approach where we partner with the ecosystem, we can tackle deep societal challenges in the field of education and healthcare.

An artificial intelligence (AI) neural network identified congestive heart failure with 100% accuracy, according to the findings of a study published in Biomedical Signal Processing and Control Journal. Just one raw electrocardiogram (ECG) heartbeat was what the AI needed to identify the condition, according to the paper. "Enabling clinical practitioners to access an accurate (congestive heart failure) detection tool can make a significant societal impact, with patients benefiting from early and more efficient diagnosis and easing pressures on (National Health Service) resources," said Leandro Pecchia, Ph.D., assistant professor of biomedical engineering at the University of Warwick in England. Typical congestive heart failure detection methods focus on heart variability and are time consuming and prone to errors, according to researchers. Instead, the research team developed a model which uses a combination of advanced signal processing and machine-learning tools on raw ECG signals.