The 2023 AI and Machine Learning Research Report

whitePaper | April 16, 2020

The Iron Triangle or, as it is more commonly known, the project management triangle has influenced project teams for years. Summed up as “fast, good, or cheap.pick two,” the concept asserts that there are firm boundaries on what is possible to produce. The triangle metaphor implies there is no way to provide goods or services that are simultaneously on budget, on time, and of high quality because of the competing nature of these priorities.

whitePaper | May 25, 2022

Modernization of data and applications on the mainframe is a necessary priority for modern organizations. Building a MongoDB Operational Data Layer (ODL) is a pattern widely used to make critical mainframe data available for modern mobile and web applications.

whitePaper | June 29, 2022

The Responsible AI Institute (RAII) is developing one of the world’s first responsible AI certification programs. The RAII Certification Program is aligned with emerging global AI laws and regulations, internationally agreed-upon AI principles, research, emerging best practices, and human rights frameworks.

whitePaper | March 30, 2022

The Stanford Institute for Human-Centered Artificial Intelligence (HAI) offers the following submission for consideration in response to the Request for Information(RFI) by the White House Office of Science and Technology to the Update of the National Artificial Intelligence Research and Development Strategic Plan.

whitePaper | July 15, 2022

Today, the use cases for AI (artificial intelligence) and machine learning are developing at a remarkable pace. We are beginning to see cases where AI is contributing to society through its implementation in systems and services that are in production and consumer-facing. These include the automation of nuanced decisions that until now could only be made by humans, thereby increasing the profitability of corporations, and increasing customer satisfaction through the personalization of services making them tailored for each user. In addition, important discussions have begun on the adverse effects such AI systems have on humans and the resulting ethical issues they can create.

whitePaper | February 17, 2022

Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.