Gartner: In 2021, artificial intelligence (AI) augmentation will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally… Gartner defines augmented intelligence as a human-centered partnership model of people and AI working together to enhance cognitive performance. This includes learning, decision making and new experiences.
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.
Read more here
When computers are confused, humans are too. Every year, more than 500 million passengers use train stations in Paris. In AI Station, a collaboration between our Lab, SNCF Gares & Connexions, and the Austrian Institute of Technology, we use artificial intelligence to investigate how passengers navigate such places. In particular, computer vision and convolutional neural networks (CNN) help us understand how people perceive space and when they might have difficulties in orienting themselves. First results are published in the journal Building and Environment.
–MIT Senseable Lab
“The power to predict the future is about to emerge. The amount of data will grow by a million times over the next 30 years”—Masayoshi Son, CEO, SoftBank Group @masason
“As a FedEx employee in 1996, I was in the room when our CIO challenged Teradata on why any company would ever need a terabyte of data”–Chad Meley @chad_meley
“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 @rao2z
“Like so many things Amazon does, I’m sure it doesn’t look at it as a convenience store, doesn’t look at it as a bookstore, but looks at it as a data experiment. The stores themselves are not the big idea”—Neil Stern, senior partner, McMillanDoolittle
“American tech giants have more information on everyone who uses the internet than any other organizations on the planet”—Kara Swisher @karaswisher
“The ability to apply algorithms in real time at finely granulated levels to find previously hidden patterns and insights all depends on having an excellent understanding of the question you are asking and the nature of data”—William Mayo, CIO, The Broad Institute of MIT and Harvard
“In the process of collecting data, although everyone thinks that these data are important assets, they have not thought out clearly where they can be used…(data’s) value is completely determined by the application scenario”–我是机器之能联合主编宇多田，长期关注自动驾驶、智能制造与AI+安防赛道
“There is a gap between the policy community and the technical community on what exactly it means to value data”—James Zou, Stanford
“If you are going to be using public data and especially for public purposes, then we shouldn’t have a black box sort of AI system”— Senator Martin Heinrich (D., N.M.) @MartinHeinrich
“The internet’s purpose is to ratify knowledge through the accumulation and manipulation of ever expanding data. Human cognition loses its personal character. Individuals turn into data, and data become regnant”—Henry Kissinger
“Building AI represents a fundamentally different paradigm than building traditional software. The performance of an AI system depends more on the data than the algorithm—in most cases, without labeled data, there is no model. Similarly, for a model to improve and adapt, it requires more data rather than simply more code”—Alexandr Wang @alexandr_wang
“Data is one of the key fuels of AI progress, so a dataset containing a couple of hundred thousand labelled pictures of faces will be like jetfuel for human surveillance”—Jack Clark @jackclarksf
26% of consumers think they interact with AI at least once a day; when they think of AI, 53% think primarily of robots and 40% think primarily of self-driving cars; 58% get their information on AI from movies and TV or social media
The Mazor X system consists of sophisticated 3D planning tools and an intra-op guidance system with a precision Surgical Arm indicated for implant and instrument positioning in spine surgery – the core of the Surgical Assurance Platform.
GRoW- Greenhouse Robotic Worker
MetoMotion is developing a multi-purpose robotic system for labor-intensive tasks in greenhouses.The Company’s first application will be a robotic harvester for greenhouse tomatoes.