How Computer Graphics and Big Data Gave Birth to Today’s Artificial Intelligence (AI)

The explosion of breakthroughs, investments, and entrepreneurial activity around artificial intelligence over the last decade has been driven exclusively by deep learning, a sophisticated statistical analysis technique for finding hidden patterns in large quantities of data. A term coined in 1955—artificial intelligence—was applied (or mis-applied) to deep learning, a more advanced version of an approach to training computers to perform certain tasks—machine learning—a term coined in 1959.

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Startup Nation and COVID-19

As the coronavirus came suddenly out of stealth mode, displaying a record-breaking adherence to Silicon Valley’s mantra of “scaling up,” shocked startup investors—watching the Bloomberg US Startups Barometer plunging more than 50% in 3 months—ask “what’s to be done now”?

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AI by the Numbers: 87% of CEOs See Data as Strategic Asset

Recent surveys, studies, forecasts and other quantitative assessments of the progress and impact of AI highlight the growing respect for data and its uses by businesses everywhere and the increasingly positive—but still mixed—attitudes towards AI by US consumers.

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Digital Health, AI, and Israel

The global outbreak of the new Coronavirus brought to our attention an inconvenient truth about influenza: The seasonal flu kills between 291,000 to 645,000 people worldwide each year. Still, a December 2019 survey found that 37% of US adults did not intend to get a flu shot.

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AI by the Numbers: Data Privacy or AI Supremacy?

Recent surveys, studies, forecasts and other quantitative assessments of the progress and impact of AI highlight the confusion and contradictory attitudes of consumers about the privacy of their data, the impact of AI on jobs, and the race for AI supremacy.

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Ramon Llull and His ‘Thinking Machine’

In 1308, Catalan poet and theologian Ramon Llull completed Ars generalis ultima (The Ultimate General Art), further perfecting his method of using paper-based mechanical means to create new knowledge from combinations of concepts.

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Why It’s Difficult to Make Predictions, Especially About the Future

The year 2020 has been featured in many predictions and long-term visions in the past, implying not only the terminal point for the forecast or planning period but also a crystal-clear crystal ball. Now that the year 2020 is our present, we can clearly see where these prognostications went wrong and try to understand why they were so cloudy.

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