Machine learning (ML) models are a cornerstone of modern technology, allowing models to learn from and make predictions based on vast amounts of data. These models have become integral to various industries in an era of rapid technological innovation, driving unprecedented advancements in automation, decision-making, and predictive analysis. The reliance on large amounts of data
There is a great YouTube video that has been circulating the internet for half a decade that reimagines a heuristically programmed algorithmic computer “HAL-9000” as Amazon Alexa in an iconic scene from “2001: A Space Odyssey.” In the clip, “Dave” asks Alexa to “open the pod bay doors,” to which Alexa responds with a series
The construction sector is known for its perennial pursuit of efficiency, quality, and safety. In recent years, one of the tools the sector has started leveraging to achieve these goals is predictive maintenance (PM), specifically the implementation of artificial intelligence (AI) within this practice. This approach, combined with continuous advancements in AI, is revolutionizing the
On May 16, 2023, the U.S. Senate Judiciary Committee conducted a significant oversight hearing on the regulation of artificial intelligence (AI) technology, specifically focusing on newer models of generative AI that create new content from large datasets. The hearing was chaired by Sen. Richard Blumenthal for the Subcommittee on Privacy, Technology, and the Law. He
On January 26, 2023, the U.S. National Institute of Standards and Technology (NIST) released the Artificial Intelligence (AI) Risk Management Framework (AI Risk Management Framework 1.0), a voluntary guidance document for managing and mitigating the risks of designing, developing, deploying, and using AI products and services. NIST also released a companion playbook for