In 1913, Henry Ford revolutionized car-making with the first moving assembly line, an innovation that made piecing together new vehicles faster and more efficient. Some hundred years later, Ford is now using artificial intelligence to eke more speed out of today's manufacturing lines. At a Ford Transmission Plant in Livonia, Michigan, the station where robots help assemble torque converters now includes a system that uses AI to learn from previous attempts how to wiggle the pieces into place most efficiently. Ford uses technology from a startup called Symbio Robotics that looks at the past few hundred attempts to determine which approaches and motions appeared to work best. A computer sitting just outside the cage shows Symbio's technology sensing and controlling the arms.
Roorkee: Indian Institute of Technology (IIT) Roorkee has launched two online certificate programs in high-demand topics -- Data Science and Machine Learning and Advanced Machine Learning and AI -- on Coursera, one of the world's leading online learning platform. "We are happy to announce two certificate courses in data science, machine learning, and AI in partnership with Coursera. This will enable a large number of aspirants to acquire these relevant areas for their professional growth," said Prof. Ajit K. Chaturvedi, Director, IIT Roorkee IIT Roorkee is among 150 top universities, including Yale, University of Michigan, University of Pennsylvania, and Imperial College of London -- that offer programs on Coursera. "For over 170 years, IIT Roorkee has been a leading Indian institution, known for its rigorous technical programs," said Betty Vandenbosch, Chief Content Officer at Coursera. "Through our partnership, we are expanding access and allowing more students to learn from IIT Roorkee's renowned faculty. Learners will gain the cutting-edge skills they need to advance their careers while creating powerful networks with their peers."
Williams's wrongful arrest, which was first reported by the New York Times in August 2020, was based on a bad match from the Detroit Police Department's facial recognition system. Two more instances of false arrests have since been made public. Both are also Black men, and both have taken legal action to try rectifying the situation. Now Williams is following in their path and going further--not only by suing the Detroit Police for his wrongful arrest, but by trying to get the technology banned. On Tuesday, the ACLU and the University of Michigan Law School's Civil Rights Litigation Initiative filed a lawsuit on behalf of Williams, alleging that his arrest violated Williams's Fourth Amendment rights and was in defiance of Michigan's civil rights law.
The rise of precision medicine is being augmented by greater use of deep learning technologies that provide predictive analytics for earlier diagnosis of a range of debilitating diseases. The latest example comes from researchers at Michigan-based Beaumont Health who used deep learning to analyze genomic DNA. The resulting simple blood test could be used to detect earlier onset of Alzheimer's disease. In a study published this week in the peer-reviewed scientific journal PLOS ONE, the researchers said their analysis discovered 152 "significant" genetic differences among Alzheimer's and healthy patients. Those biomarkers could be used to provide diagnoses before Alzheimer's symptoms develop and a patient's brain is irreversibly damaged.
Would you like to build predictive models using machine learning? That s precisely what you will learn in this course "Decision Trees, Random Forests and Gradient Boosting in R." My name is Carlos Martínez, I have a Ph.D. in Management from the University of St. Gallen in Switzerland. I have presented my research at some of the most prestigious academic conferences and doctoral colloquiums at the University of Tel Aviv, Politecnico di Milano, University of Halmstad, and MIT. Furthermore, I have co-authored more than 25 teaching cases, some of them included in the case bases of Harvard and Michigan. This is a very comprehensive course that includes presentations, tutorials, and assignments. The course has a practical approach based on the learning-by-doing method in which you will learn decision trees and ensemble methods based on decision trees using a real dataset.
How can you tell if an AI technology that's actually part of the AI revolution? What went wrong with artificial intelligence? This transformative technology was supposed to change everything. I've seen first-hand the incredible potential it has--both as a professor of computer science at the University of Michigan and as the founder of Clinc, ZeroShotBot, Myca.ai, a non-profit called ImpactfulAI, and several other AI-focused companies. So, why has it devolved into overhyped solutions, marketing noise, and an endless spin of the same, tired ideas?
Researchers from University of Minnesota, New York University, University of Pennsylvania, BI Norwegian Business School, University of Michigan, National Bureau of Economic Research, and University of North Carolina published a new paper in the Journal of Marketing that examines how advances in machine learning (ML) and blockchain can address inherent frictions in omnichannel marketing and raises many questions for practice and research. The study, forthcoming in the Journal of Marketing, is titled "Informational Challenges in Omnichannel Marketing Remedies and Future Research" and is authored by Koen Pauwels, Haitao (Tony) Cui, Catherine Tucker, Raghu Iyengar, S. Sriram, Anindya Ghose, Sriraman Venkataraman, and Hanna Halaburda. In this new study in the Journal of Marketing, researchers define omnichannel marketing as the "synergistic management of all customer touch points and channels both internal and external to the firm that ensures that the customer experience across channels and firm-side marketing activity, including marketing-mix and marketing communication (owned, paid, and earned), is optimized." Often viewed as the panacea for one-to-one marketing, omnichannel experiences data, marketing attribution, and consumer privacy frictions. The research team demonstrates that advances in machine learning (ML) and blockchain can address these frictions.
"What is fair?" feels like a rhetorical question. But for Michigan State University's Pang-Ning Tan, it's a question that demands an answer as artificial intelligence systems play a growing role in deciding who gets proper health care, a bank loan or a job. With funding from Amazon and the National Science Foundation, Tan has been working for the last year to teach artificial intelligence algorithms how to be more fair and recognize when they're being unfair. "We're trying to design AI systems that aren't just for computer science, but also bring value and benefits to society. So I started thinking about what are the areas that are really challenging to society right now," said Tan, a professor in MSU's Department of Computer Science and Engineering.
If you have a robot in close proximity to a person, and anything that goes wrong, that's a risk to that person," Raibert said. Things have gone wrong, at least on the job. In 2015, a 22-year-old man was killed while helping to set up a stationary robot at a Volkswagen plant in Germany. The robot pushed him against a metal plate and crushed him. In another case that year, a robot's arm malfunctioned, hit and crushed a woman's head in a Michigan auto plant.
A Tesla Model Y traveling on Autopilot crashed into a parked police car in Michigan while officers were investigating an accident involving a deer and another vehicle. The crash took place around 1:12 a.m. Lt. Brian Oleksyk of the Michigan State Police confirmed the Tesla was operating on its driver's assistance system when it crashed into a squad car that was parked partially in the right lane. The name of the driver has not been released. The 22-year-old who was operating the vehicle received citations for having a suspended license and failing to move over.