TL;DR:
- UC, Case Western Reserve University, and Ohio State University collaborate on a five-year, $5.1 million AI initiative.
- They aim to capitalize on AI and machine learning by deploying experts to assist researchers across Ohio.
- UC’s $1.1 million portion focuses on advancing high-tech industries, particularly in the biosciences.
- Transparent AI systems are being developed at UC to ensure trustworthiness and ethical AI outcomes.
- The NSF initiative seeks to democratize AI and machine learning across academic institutions nationwide.
- The Case Western Reserve-led team will recruit four AI experts to provide tailored mentoring and training to users from diverse backgrounds.
- The financial support emphasizes the need for a reliable infrastructure and a skilled AI workforce.
Main AI News:
In a groundbreaking collaboration, the University of Cincinnati (UC) has joined forces with Case Western Reserve University and Ohio State University to harness the power of artificial intelligence (AI) and machine learning in Ohio. The ambitious five-year plan, backed by a generous $5.1 million grant from the National Science Foundation, aims to propel the state’s researchers to the forefront of cutting-edge technology.
The primary goal of this collaboration is to deploy a team of expert professionals who will assist researchers across Ohio in leveraging the potential of AI in their respective fields. With the Ohio Supercomputer Center at Ohio State University playing a central role, these experts will work closely with researchers to explore AI’s transformative capabilities.
Jane Combs, the Director of Research Technologies at UC, highlighted their commitment to supporting various departments, especially in the burgeoning field of biosciences. She emphasized the importance of scaling up research efforts and solving grand challenges with the aid of AI, stating, “That’s the fun stuff — to think big and solve bigger problems.“
One key aspect of UC’s efforts is the development of transparent AI systems. By unraveling the decision-making processes of AI, scientists can build trust and credibility in these cutting-edge technologies. Combs remarked on the increasing ubiquity of AI across various disciplines, and she stressed the need for ethical considerations and ensuring diverse perspectives are represented in AI outcomes.
The team at UC is based in the Digital Futures building, the university’s latest research center, which fosters seamless interdisciplinary collaboration among its researchers. Recently, Professor Kelly Cohen from the Aerospace Engineering department addressed the challenges of AI decision-making at an international conference hosted by UC. He advocated for an AI approach based on fuzzy logic, which allows for degrees of truth instead of a binary true-false dichotomy. This “fuzzy logic” system is both explainable and transparent, making it a responsible and trustworthy choice for AI applications.
Cohen expressed concerns about the mainstream AI’s lack of transparency, citing its “black box” nature, brittleness, and potential dangers to human lives. This prompted the team at UC to explore alternative, more accountable AI solutions that prioritize safety and reliability.
The broader aim of the NSF’s initiative is to democratize AI and machine learning, making them accessible to researchers across academic institutions nationwide. Acknowledging that not everyone possesses expertise in AI, the project leader, Vipin Chaudhary, emphasized the significance of providing expert guidance and training. Chaudhary, the Kevin J. Kranzusch Professor and Chair of the Department of Computer and Data Sciences at Case School of Engineering, dubbed the expert team “evangelists” and “trainers” for AI technology.
The Case Western Reserve-led team plans to hire four AI experts, stationing two at each partnering institution, to deliver personalized mentorship and training to AI users. This inclusive approach will involve researchers from smaller community colleges and historically Black colleges and universities, fostering diversity and promoting AI adoption across various disciplines.
With generous financial support from the NSF, this initiative underlines the pressing need for a robust infrastructure and a well-trained AI workforce. Karen Tomko, Director of Research Software Applications at the Ohio Supercomputer Center, emphasized the demand for AI and machine learning tools in a wide range of fields, from computational chemistry to the fine arts. The addition of AI experts to partner institutions will undoubtedly empower the broader research community to effectively harness the transformative potential of these technologies.
Conclusion:
The collaborative efforts between UC and other Ohio universities signify a significant advancement in the AI market. By deploying experts and developing transparent AI systems, this initiative fosters trust and credibility in AI applications. Moreover, the broader NSF initiative demonstrates a growing demand for accessible AI solutions across various industries and academic institutions. Businesses in the AI market should take note of these developments as they indicate a shifting landscape with a heightened emphasis on accountability, transparency, and inclusivity in AI adoption. Staying abreast of such advancements will be crucial for businesses seeking to remain competitive and responsive to evolving industry trends.
