I looked at the idea of charter cities and special economic zones as models for urbanization. I think it'll be easier, faster, and less error-prone if we were to strengthen the movement towards greater rural governance and build up the rural areas towards the new designs.
India, for example, has a political architecture with a strong center and states, and weak districts, cities, and villages. It also has existing political support to improve villages, and that movement can be amplified.
The "Cloud Countries" idea in https://1729.com/how-to-start-a-new-country/ is cool. It's also orthogonal to the physical footprints that are the focus for sustainability. A person can be a LARP in many cloud countries, and also physically resident in a mud-world country so these don't conflict.
Can a business that doesn’t use Artificial Intelligence (AI) survive the competition?
AI beat humans at chess years ago, then at the more complex games of Jeopardy and Go. How long before it beats business managers? The complexity of running a business stands in the way. On the side of AI are the forces of data accumulation and algorithms that convert human expertise into software. AI is already available in many parts of the business, optimizing inventory, scheduling work, etc., and now it is optimizing decisions across silos and business units.
The game is on, let’s call it Decision Intelligence…
Achieving sustainability is a grand challenge for the human civilization. This analysis is to show that we have the ability to achieve it.
Sustainability is the ability for generations of humans to continue indefinitely without running out of the resources they need to have a good quality of life. Sustainability has three elements:
MBA students face a world disrupted by the COVID-19 pandemic that has driven a digital transformation while impeding physical supply chains. Artificial Intelligence (AI) continues to gain traction, and will change industries as well as the work of managers. These are the questions posed by an MBA class in Bangalore.
AI is a branch of computer science intent on building machines to do the tasks that otherwise require a person. It fell into disrepute in the 1980s, caused by bursting the bubble of inflated expectations. It’s back again, with splashy news. …
The front-page news has a time-series graph of COVID-19 cases in India, from March 15th to June 27th, showing total cases increasing in an exponential way from 110 to 508,953. The headline reads: “400,000 to 500,000 in a week”. Frightening!
Has the number of people infected with COVID-19 increased from 400,000 to 500,000 in a week?
What they fail to mention is that tests have increased, and cases track increased testing. By not presenting the test data, it is removed from readers’ cognition. The misleading default assumption is that nothing else changed (that there was the same amount of testing…
AI-enabled analytics helps managers make decisions with greater efficiency and impact. It also increases the productivity of analysts and engineers because complex data processing and analyses can be executed by AI. These jobs will shrink. Conversely, jobs to assess and control data accuracy, model integrity, and decision errors will increase. The nature of analytics work will, therefore, transform as AI eats Analytics.
AI eats traditional analytics jobs
The traditional data engineering job is to build and babysit clunky data processing using extract-transform-load (ETL) and relational databases. Dumb dashboards and reports require expert analysts to create and maintain them. AI tools…
There is a lot of confusion about the definition of Artificial Intelligence (AI), Data Science, and Analytics, and it is particularly harmful for students and early-career people who are thinking about specializing in these areas. This article is to dispel that confusion.
Artificial Intelligence (AI) is characterized as “intelligent software agents” in the authoritative book on the subject, “Artificial Intelligence: A Modern Approach” (Russell, 2010). Advances in machine learning, computer vision, and natural language processing create a buzz for AI. This buzz sometimes overshadows other AI algorithms, such as search, stochastic games, etc.
Data Science is about organizing and analyzing…