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Artificial Intelligence

Why does MBSI use AI for research?

With advanced computing capabilities AI is needed to understand and solve complex problems. AI can encompass developing technologies that are inherently interdisciplinary and provide key capabilities in virtually every field of science and technology. For the Institute, this research area will support the needs of our key focus areas like:

Climate Science

Health Innovation

We consider computational sciences to incorporate the academic and research disciplines of computer science, information science, artificial intelligence, machine learning, data science, and modeling and simulation. Our research requires state-of-the-art computing resources and human talent. The capabilities of the institute to conduct applied research in the computational sciences will be built up gradually as other areas of research grow at MBSI and in response to their identified requirements

Why is AI essential in today’s world?

The growing field of artificial intelligence (AI) is an important element of the computational sciences department. AI continues to evolve through domains such as machine learning, neural networks, and data science. In a nearly human-like way, modern AI is developing to take on tasks that humans perform, but in a more efficient manner. Once computer algorithms and models capture a human capability, AI can perform it faster and possibly more consistently. As large data sets accumulate, there is a need to learn from and analyze this data. AI offers this capability through machine learning (ML). When provided with large data sets, a machine in the form of computer programs and models can be trained to find solutions or identify trends using data analysis and various algorithms. Data science is another element in processing the massive amount of data, especially concerning climate change. To increase our understanding of the dynamics around climate change issues like sea-level rise and ice sheets, where computers, using data science techniques, can process large amounts of unstructured data. 

Statistics on weather and the environment can be analyzed for trends to base projections of future events. Energy companies could leverage the vast amounts of data they accumulate to create more efficiencies in energy use. ML can take this data and forecast energy generation, helping suppliers better fill gaps with renewable resources while simultaneously reducing waste. AI should improve power efficiency by 15% in the next three to five years according to the Capgemini Research Institute. This efficiency can begin at the industrial level and progress to the household level.

How can AI benefit MBSI?

AI can predict wind patterns up to 36 hours in advance to optimize wind farm operations and output, according to Google’s DeepMind. As we transition to alternative energy technologies to reduce and eliminate our carbon footprint, AI data analysis and modeling will be key to helping us determine when and how we can reach this goal. Similarly, the convergence of computational sciences disciplines can help us improve healthcare. There is a plethora of data available to our healthcare researchers on most widespread disease and health issues, but humans are not necessarily adept at identifying long-term conclusions from the review of short-term data. By applying AI and ML:

By applying ML analysis to data sets will help generate policy and recommendations that are consistent and in the best public interest over the long term.

Data science techniques can review and process data on overall health, that aid decision-makers on public policy choices and health advice.

AI will provide innovative options in health care through the study of massive health data sets and longevity analysis.

AI algorithms will be able to extract patterns from the data to help solve health problems and cure diseases.

Research MBSI

Work in computational sciences at the Institute will not necessarily focus on basic research. We seek solutions that can be applied to improve the capabilities of researchers in climate science and health innovation initially, and others as the MBSI research teams grow. The focus will be applied computational research to identify products, techniques, or approaches that will aid other research disciplines as well. Once identified, the solutions will be vetted across the institute with relevant colleagues, then implemented and tested in collaboration with our partners. Applying computational science techniques in areas where there are large data sets or extensive information repositories will be at the core of this department. Climatology, health innovation, and agricultural research will all utilize these computing services. 

Long Term Research Agenda

Aligned Artificial Intelligence:

Build ethical frameworks and safeguards to ensure AI aligns with human values. 

 Develop explainable AI systems that are transparent and trustworthy. 

Research human-machine collaboration models that leverage AI's strengths while respecting human decision-making.

 Explore the potential of AI for consciousness and sentience, ensuring ethical treatment.

Employ AI to accelerate research in all other fields, creating a virtuous cycle of discovery.

Conclusion

The use of predictive analysis, data collection, and advanced data analytics will help in accessing information and reducing manual efforts. AI can also speed up simulations and model-based experiments, allowing researchers to test hypotheses more efficiently. AI can simplify the tasks for researchers and optimize them accordingly.