In a conversation with Analytics India Magazine, Co-founder and CTO Shishir explained the technology behind Cranberry Analytics’ management system Recon, breaking down how AI and ML can facilitate the management of natural resources and what the future for AI in water management looks like.
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The pros of artificial intelligence technology have always been followed up with the cons of leveraging these technologies. With the launch of every new system that requires users to share personal and biometric data, a school of thought has emerged voicing the ethical and privacy concerns of using the systems. A recent investigative report by Reuters sheds light on how the three US tech giants — Google, IBM and Microsoft — have been resisting and turning down projects on account of ethics concerns.
Read MoreIn 2017, Google, in a blog post, ‘Federated Learning: Collaborative Machine Learning without Centralized Training Data,’ explained in detail the nuances of this technique. Since then, a lot has changed. In this article, we will list some of the top research papers on federated learning.
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With an aim to bolster AI research across major American research institutes, the National Science Foundation (NSF) announced that it will establish 11 new National AI-Research Institutes. Each NSF institute has been awarded $20 million for the research that will go on for five years, to study the range of advances through AI-based technologies. The US Department of Agriculture National Institute of Food and Agriculture, and the US Department of Homeland Security will also work in collaboration with the NSF in the research.
NSF aims to empower America’s workforce with the knowledge of AI-tech, by deepening its research. Last year in August, NSF had announced the formation of seven national AI institutes. These institutes are aimed at AI research that would expand to a broader range of businesses across American economy. For such extensive AI research, NSF initially supported these institutes with an investment of $100 million. The establishment of these institutes represents America’s most significant federal investment in AI research and workforce development. Register for our Workshop > >
Objectives of 11 NSF AI-research institutes
NSF Director Sethuraman Panchanathan had last year said that NSF invests over $500 million in AI research annually. However, 2021 has been a year of more such establishments. This year, the combined investment of NSF in national AI-research institutes is $220 million, while the reach of all 11 AI-research institutes announced recently, will now expand to a total of 50 states in the US.
Panchanathan described NSF’s vision in AI research to be an inspiration for talents and ideas across the country, as he said, “The field of AI-research is an important area which will lead the US to new capabilities in terms of improving lives from medicine to entertainment, transportation to cybersecurity. Such research initiatives will position the US in the vanguard of competitiveness.”
The eleven national AI-research institutes will focus on seven key areas:
See Also
AI and advanced cyberinfrastructure,AI for advances in optimisation,AI in computer and network systems,AI augmented learning,AI driven innovation in agriculture, food system,AI in dynamic systems, andHuman-AI interaction and collaboration
These AI-research institutions are being established by NSF in partnership with the US Department of Homeland Security, the US Department of Food and Agriculture, Google, Amazon, Accenture, and Intel. Most of the tech companies involved in the investment are already part of the business transformation that industries have witnessed using AI, worldwide. The NSF institutes will serve as the platform for broader studies of the transformational advances that can be achieved in various sectors— specifically in the fields of science and engineering, followed by the economic sector, cybersecurity, and the agriculture sector with food-system security.
Here’s a list of the 11 institutes, and their areas of focus in AI-research:
The research program led by Georgia Institute of Technology, also known as AI-CARING, will focus on AI systems that learn individual models of human behaviour. How the AI behaviour changes with time and uses the knowledge to collaborate and communicate in any given caregiving setting. This is NSF’s ‘AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups‘ which will be partially funded by Google and Amazon.In order to support the underrepresented students and teachers to learn AI-tech, NSF’s ‘AI Institute for Advances in Optimisation‘ will be led by Georgia Tech, to revolutionise decision-making on a large scale, by fusing AI and maths, into the intelligent systems— to achieve breakthroughs. The research will benefit high school, graduate and postgraduate students and the institute will be partially funded by Intel.The University of California San Diego will collaborate with five other universities across America, to “make impossible optimisations possible” by solving the challenges of scale and complexity. To achieve this, NSF’s ‘AI Institute for Learning-Enabled Optimization at Scale‘ will apply learning-enabled optimisation. The institute will be partially funded by Intel.With focus on AI in cybersecurity, NSF’s ‘AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment‘ will create cyberinfrastructure to make AI easy for scientists, to promote its democratisation in the country. This institute will be led by Ohio State University and will be fully funded by NSF.NSF’s ‘AI Institute for Future Edge Networks and Distributed Intelligence‘ will develop new AI tools and techniques to ensure that future generations of wireless edge networks are self-healing and self-optimised. The institute will design such wireless edge networks by leveraging the synergies between networking and AI. It will be partially funded by DHS.NSF’s ‘AI Institute for Edge Computing Leveraging Next-generation Networks‘ will work in collaboration with scientists, engineers, statisticians, legal scholars and psychologists from seven varisities in the country— to develop edge computing with landmark AI functionality, while controlling the costs. This institute will be partially funded by DHS, and will be led by Duke University.With focus on fundamental AI and machine learning, NSF’s ‘AI Institute for Dynamic Systems‘ will perform innovative research— to integrate models based on physics with AI and machine learning approaches. Led by University of Washington, this institute will be partially funded by DHSNSF’s ‘AI Institute for Engaged Learning‘ will engage learners in AI-driven narrative-centered learning environments, through advanced natural language, machine learning and computer vision. The research is aimed at achieving transformational advances in STEM teaching also. It will be led by North Carolina State University and will be fully funded by NSF.Led by Georgia Research Alliance, NSF’s ‘AI Institute for Adult Learning and Online Education‘ will focus on adult online education by developing novel AI theories and techniques. This institute will be partially funded by Accenture.With focus on AI in agriculture, the ‘USDA-NIFA Institute for Agricultural AI for Transforming Workforce and Decision Support‘ will integrate AI methodologies into agriculture operations to better predictions and decision mechanisms, and robotics-enabled agriculture. It will be funded by USDA-NIFA.With an aim to transform the agriculture sector, the ‘AI Institute for Resilient Agriculture‘ will use innovative AI-driven digital twins that model plants at an unprecedented scale. This method is enabled by computational theory, tools for crop improvement and production for resiliency to climate change, along with AI algorithms. Led by Iowa State University, this institute will be funded by USDA-NIFA.
Recently, the national science foundation also issued a grant to the University of Florida, for a five-year study to find out ‘the public’s awareness of artificial intelligence’.
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