14 PUBLISHED IDEAS
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Navigating through the Covid-19 pandemic in March 2020 caused organisations to work remotely and find ways to cut spending. However, companies significantly increased their spending on digital technologies for employees.
Over 50% of midsized companies increased their spending in this area, and 69% plan to increase their digital tools in 2022. Yet, many of these investments will not generate substantial business impact because they lack a sustained and successful focus on improving digital dexterity.
There’s an ingrained mythology around startups that not only celebrates burn-out efforts, but actually requires it. It’s the logical outcome of trying to compress a lifetime’s worth of work into the abbreviated timeline of a venture fund.
It’s not hard to understand why such mythology serves the interest of money men who spread their bets wide and only succeed when unicorns emerge.
The computing industry progresses in two mostly independent cycles: financial and product cycles.
Financial markets get a lot of attention. They tend to fluctuate unpredictably and sometimes wildly. The product cycle by comparison gets relatively little attention, even though it is what actually drives the computing industry forward.
Coined in 1956 by Dartmouth Assistant Professor John McCarthy, ‘Artificial Intelligence (AI) is a general term that refers to hardware or software that exhibits behavior that appears intelligent.
Basic ‘AI’ has existed for decades, via rules-based programs that deliver rudimentary displays of ‘intelligence’ in specific contexts. Progress, however, has been limited — because algorithms to tackle many real-world problems are too complex for people to program by hand.
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