Artificial Intelligence (AI) Stats News: AI Augmentation To Create $2.9 Trillion Of Business Value

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The recent surveys, studies, forecasts and other quantitative assessments of the health and progress of AI estimated the impact on productivity of human-machine collaboration, the number of jobs that could be automated in major U.S. cities, and the size of the future AI in retail and healthcare markets; and found AI optimism among the general population, algorithms outperforming (again) pathologists, and that our very limited understanding of how our brains learn may improve machine learning.

In 2021, AI augmentation (“a human-centered partnership model of people and AI working together to enhance cognitive performance”) will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally [Gartner]

In July 2019, there were more than $10.1 billion in robotics investments worldwide, up from $1.1 billion in June 2019 and $1.6 billion in June 2018; technology for self-driving cars and robots and intelligent systems in healthcare were the big winners, followed by supply chain automation, software and artificial intelligence, and service and consumer robots [The Robot Report]

69% expect their respective cities and residents will benefit in some way within the next 20 years from new technologies like AI; 45% expect their own jobs will be automated within the next decade; one-third of respondents in North America and Europe felt unsure about their city government’s vision for how to cope with technological change [Oliver Wyman survey of 9,000 people in 21 major global cities]

By training AI on more than 40,000 reports to develop sentiment scores for analyst notes, Morgan Stanley has developed what it calls Machine-Read Analyst Sentiment or MRAS; for trades where the MRAS strategy was bullish and the initial market move was negative, the strategy beat the S&P 500 by an average of 1.9% over a 60-day period; the strategy saw similar success when those positions were flipped [CNBC]

Applying the Frey/Osborne framework to 24 major U.S. cities, it is estimated that between 33% and 44% of people work in jobs with a greater than 70% probability of being automated, including retail salespeople, cashiers, office workers, and other service-related jobs [Sloan Management Review]

Only 50% of hospital executives are familiar with the concept of AI/RPA; more than half are unable to name an AI/RPA vendor or solution; 23% are looking to invest in AI/RPA today, while half plan to do so by 2021 [Olive AI survey of 115 U.S. hospital executives]

A machine learning algorithm outperformed pathologists (89% accuracy vs. 70% accuracy) in distinguishing between two types of breast cancer while matching the pathologists in differentiating cancer from non-cancer tissues [JAMA Network Open]

71% of respondents are in favor of using technology to replace manual and laborious tasks, and 69% believe that technology will enhance not replace their jobs; 64% believe automation technology will help to reduce their workload and stress. [Verint online survey of 34,068 consumers in Australia, Brazil, Canada, France, Germany, Hong Kong, India, Japan, Mexico, Netherlands, Singapore, Saudi Arabia, South Africa, Spain, Sweden, the United Arab Emirates, United Kingdom and the United States]

Do you believe that organizations have taken GDPR regulations seriously, and are now compliant?

  • Yes – 32%
  • No – 68%

[2,020 respondents to a Twitter poll conducted during Infosecurity Europe, June 2019

Do you think securing your devices and personal data will become more or less complicated over the next 12 months?

  • More – 66%
  • Less – 34%

[2,900 respondents to a Twitter poll conducted during Infosecurity Europe, June 2019]

DeepMind has developed a machine learning model that can label most animals at Tanzania’s Serengeti National Park at least as well as humans while shortening the process by up to 9 months (it normally takes up to a year for volunteers to return labeled photos) [Engadget]

In a simulation, biological learning algorithms outperformed state-of-the-art optimal learning curves in supervised learning of feedforward networks, indicating “the potency of neurobiological mechanisms” and opening “opportunities for developing a superior class of deep learning algorithms” [Scientific Reports]

The AI in retail market is estimated to reach $4.3 billion by 2024 [P&S Intelligence] [e.g., Nike acquires Celect, August 6, 2019]

The AI in healthcare market is estimated to reach $12.2 billion by 2023 [Market Research Future] [e.g., BlueDot has raised $7 million in Series A funding, August 7, 2019]

AI companies funded in the last 3 months: 417 for total funding of $8.7 billion

AI acquisitions in the last month (July 12-August 11): 20

AI leads all other sectors in Israel in the number of seed to A round financing deals in 2019: 1,509

AI leads all other sectors in Israel in the number of seed to A round financing deals 2013-2018: 6,111

Data is eating the world quote of the week: “Although it is fashionable to say that we are producing more data than ever, the reality is that we always produced data, we just didn’t know how to capture it in useful ways”—Subbarao Kambhampati, Arizona State University

AI is eating the world quote of the week: “We advocate for a new perspective for designing benchmarks for measuring progress in AI. Unlike past decades where the community constructed a static benchmark dataset to work on for the next decade or two, we propose that future benchmarks should dynamically evolve together with the evolving state-of-the-art”—Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi, Allen Institute for Artificial Intelligence and the University of Washington

[“source=forbes”]

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