Ashby's law of requisite variety states that a controller must have at least as much variety (complexity) as the controlled. Maturana and Varela proposed autopoiesis (self-production) to define living systems. Living systems also require to fulfill the law of requisite variety. A measure of autopoiesis has been proposed as the ratio between the complexity of a system and the complexity of its environment. Self-organization can be used as a concept to guide the design of systems towards higher values of autopoiesis, with the potential of making technology more "living", i.e. adaptive and robust.
Requisite Variety, Autopoiesis, and Self-organization Carlos Gershenson
...Small companies can bolster their business significantly by leveraging this technology properly. Owners who come up with a comprehensive IoT strategy will be well equipped to manage a business in the ever-changing 21stcentury.
According to CMSWire.com, many companies will need to start by updating their IT assets. "Add new devices, connect them to the cloud and enable them to talk to each other."
Businesses must harness the power of technological connectivity in order to serve and understand their customers better.Small businesses should first consider using IoT to collect customer data. The technology allows companies to easily and cost-efficiently collect new data which will offer invaluable insights about ways to improve business or keep up with the competition....
Last week, Mary Meeker of Kleiner Perkins Caufield Byers presented her Internet Trends report for 2014 at the Code Conference in California. Since we're fans of tl;dr analyses & content curation, though, here are some of the most important points from the first half of the report.
The intelligence phenomenon continues to fascinate scientists and engineers, remaining an elusive moving target. Following numerous past observations (e.g., Hofstadter, 1985, p. 585), it can be pointed out that several attempts to construct “artificial intelligence” have turned to designing programs with discriminative power. These programs would allow computers to discern between meaningful and meaningless in similar ways to how humans perform this task. Interestingly, as noted by de Looze (2006) among others, such discrimination is based on etymology of “intellect” derived from Latin “intellego” (inter-lego): to choose between, or to perceive/read (a core message) between (alternatives). In terms of computational intelligence, the ability to read between the lines, extracting some new essence, corresponds to mechanisms capable of generating computational novelty and choice, coupled with active perception, learning, prediction, and post-diction. When a robot demonstrates a stable control in presence of a priori unknown environmental perturbations, it exhibits intelligence. When a software agent generates and learns new behaviors in a self-organizing rather than a predefined way, it seems to be curiosity-driven. When an algorithm rapidly solves a hard computational problem, by efficiently exploring its search-space, it appears intelligent.
Content is King: we've heard this sentence so much that for a lot of us it can become a factor of stress and frustration. Are you suffering content FOMO? Relax: content curation is here to the rescue. And here's how to make it practical and easy through hands-on best practices and tips as well as free or freemium tools to stop worrying about not doing enough with content.