I recently caught up for a morning coffee with Charles Sansbury, CEO of Cloudera. We spoke about how AI is changing how leaders view data infrastructure and the significance of organizations capable of operating at exascale. Charles shared how his conversations with Fortune 50 companies have shifted from theoretical AI applications to practical concerns about return on investment, data quality, and infrastructure. A key part of this transition is the emerging trend of ‘private AI’ - targeted models trained on proprietary company data.
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I recently caught up for a morning coffee with Charles Sansbury, CEO of Cloudera. We spoke about how AI is changing how leaders view data infrastructure and the significance of organizations capable of operating at exascale. Charles shared how his conversations with Fortune 50 companies have shifted from theoretical AI applications to practical concerns about return on investment, data quality, and infrastructure. A key part of this transition is the emerging trend of ‘private AI’ - targeted models trained on proprietary company data.
This new age of smart machines will still need humans - but arguably, they will need to be ones who can think, create and make decisions in very different ways than the workforce of today. As with the first Industrial Revolution, reinventing education will be a priority going forward, especially if we are to survive the automation-led shakeup to jobs. To find out what it might take to transform schools and learning, I spoke with Dr. Shawn K. Smith , an education futurist and chief executive officer of Modern Teacher. Shawn also sits on the board of The Futures Institute, an organization dedicated to providing global insights on complex local problems.
Between Worlds
I recently caught up for a morning coffee with Charles Sansbury, CEO of Cloudera. We spoke about how AI is changing how leaders view data infrastructure and the significance of organizations capable of operating at exascale. Charles shared how his conversations with Fortune 50 companies have shifted from theoretical AI applications to practical concerns about return on investment, data quality, and infrastructure. A key part of this transition is the emerging trend of ‘private AI’ - targeted models trained on proprietary company data.
