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Data & Artificial Intelligence

The field of data and artificial intelligence (AI) encompasses all the technologies, methods and processes for collecting, storing, analyzing and using data to solve complex problems and make decisions. Data science is a key discipline in this field, involving the collection and analysis of massive data, or big data, to extract useful information, such as patterns, trends or forecasts.
AI is another important discipline in this field, involving the development of machine learning algorithms and models capable of processing and analyzing data autonomously, in order to solve complex problems, make decisions or perform intelligent tasks.
In short, the field of data and AI aims to improve the way businesses, governments and individuals use data to enhance their performance, efficiency and decision-making.


Data science and AI are ubiquitous in multidisciplinary innovation in the Boston area. At the Massachusetts Institute of Technology (MIT), the Computer Science & Artificial Intelligence Laboratory (CSAIL) and the MIT Institute for Data, Systems and Society (IDSS) are having a significant impact on the development and application of analytical and algorithmic methods to address complex societal challenges in diverse fields such as finance, energy systems, urbanization, social networks and healthcare. At Harvard University, the Laboratory for Innovation Science at Harvard (LISH) supports innovative projects in data science and AI.

The multidisciplinary nature of applications is illustrated by the large companies based in the Boston area, such as Nuance, Dynatrace and Motional, as well as by the support and investment structures: the Hyperplane venture capital fund invests in early stage startups that use AI to solve diverse industrial problems; MIT’s The Engine fund places data and AI at the heart of innovative technologies likely to provide solutions to major societal challenges; The Founder Institute accelerator network has launched the AI & Robotics Acceleratorin Boston in 2021; at Boston Universitythe Hariri Institute for Computing and Computational Science & Engineering incubates and accelerates data and AI startups from academia..
Entrepreneurial successes confirm the strength of Boston’s data and AI ecosystem, with examples including Datarobot ($1B), a machine learning platform for building predictive models, Cybereason ($751M), which uses AI to detect potential cyber threats, and Tomorrow.Io ($185M), which offers an AI-based weather forecasting platform.

The local professional network in the field is strengthened by associations, such as Boston New Technology, and events like the AI accelerator summit.

San Francisco

The San Francisco Bay Area is a natural world leader in the fields of data and AI, being the headquarters of major tech companies such as Intel, AMD, IBM, Apple, Oracle, Alphabet (Google), Meta and more recently Twitter, Netflixandt Uber.

Stanford University plays a leading role in this ecosystem, through the Stanford Data Sciencedepartment, which aims to create synergies with the university’s other departments, as well as the Stanford Artificial Intelligence Laboratory (SAIL) and the Center for Artificial Intelligence in Medicine & Imaging (AIMI) which develop the use and application of AI systems. Finally, the Stanford Cyber Policy Center is particularly involved in the regulation and governance of digital technologies such as AI. The University of California Berkeley (UC Berkeley) also has research laboratories in these fields, including Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Expert Systems Technology Lab (BEST) and International Computer Science Institute (ICSI).

Generalist innovation support structures, such as Y combinator and Plug and Play Tech Centerhave a particular interest in data science and AI, while venture capital funds, such as The Hive focus on startups in these fields..

Several associations and events, such as the Silicon Valley Science Technology Association (SVSTA), Association for the Advancement of Artificial Intelligence (AAAI) and the AI Accelerator Summit, bring together the main players in this technology sector, and enable new successes to emerge, Following on from the record-breaking fund-raising efforts of OpenAI ($11B), whose aim is to develop machine learning applications based on research, and which is notably behind ChatGPT, Nuro ($2.3B), which is developing autonomous delivery vehicles using AI, Freenome ($1.1B), which uses AI to detect certain biological markers specific to cancer.

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