Applied Research to Deploy AI for NIST Research This area focuses on advancing application of AI to NIST metrology problems and enabling NIST scientists to draw routinely on machine learning and AI tools to gain deeper insight into their research. We believe AI will transform the world in dramatic ways in the coming years – and we’re advancing the field through our portfolio of research focused on three areas: towards human-level intelligence, platform for business, and hardware and the physics of AI. Iris.ai uses a combination of keyword extraction, word embeddings, neural topic modeling, word importance based similarity of document metrics and hierarchical topic modeling. Get meaning from massive amounts of information, remove unconscious human bias and get early market signals. The approach is mainly unsupervised but we utilize an evaluated annotation set from our community of AI Trainers for benchmarking and improving our tools. Fourteen new AI research projects are underway to address the COVID-19 pandemic through CIFAR’s AI and COVID-19 Catalyst Grants initiative Learn more; Artificial Intelligence; Mar 24 / 20 Using AI to track cancer evolution Canada CIFAR AI Chair Quaid Morris uses machine learning to find patterns of mutations in tumours. This research is supported by the National Research Foundation, Singapore under its AI Singapore Programme (AISG-RP-2019-050).
They will also work with the ADF to apply any new artificial intelligence capabilities to the new Star Shots strategy where possible. AI is an opportunity, not a threat to market research. NIST’s AI research efforts can be broken down into two categories: Foundational and Applied Research. Get meaning from massive amounts of information, remove unconscious human bias and get early market signals. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore. The field of artificial intelligence (AI) experienced tremendous scientific advances in the last few years, from vast improvements in processing power and computational efficiency to new insights into object identification, language, and deep learning. The mission of AFR is to perform world-class research at the intersection of Artificial Intelligence, Data Analytics, and Software Analytics in the context of FinTech. AI for Fintech Research (AFR) is a collaboration between ING and Delft University of Technology. IBM Research AI plans to showcase more than a dozen papers at ICLR 2020 covering a diversity of topics including breakthroughs in ways of infusing common sense into AI, securing machine learning from adversarial attacks and maintaining precision of inferencing while reducing energy use. IBM Research has been exploring artificial intelligence and machine learning technologies and techniques for decades. IBM — a leader in AI research since its inception in the 1950s — helped inform many of these advances. UniSA and UOW to jointly research AI capabilities for Defence.
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