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although the experience of insight is sudden and can seem disconnected from the immediately preceding thought, these studies show that insight is the culmination of a series of brain states and processes operating at different time scales."

This echoes the favored Fast Company definition of creativity, that it's finding the connections between seemingly unrelated things.

Here’s the problem with interactivity: There’s no evidence people actually want it in their stories. No one watches Mad Men or reads Gone Girl yearning for control of the story as it unfolds. Interaction is precisely what most of us don’t want during story time. The more we interact with a story, the more we have to maintain the alertness of the mind operating in the real world. We can’t achieve the dreamy trance that constitutes so much of the joy of story--and the power. And the more I think about it, the more convinced I am that Finnegan’s Wake, for all its splendor as a kind of impressionistic word painting, repels readers because of its interactivity. Most critics think that Joyce was trying to get away from what he called “wideawake language” to re-create the chaos of dreaming life. Paradoxically, however, the sheer difficulty of Finnegan’s Wake forces readers to maintain a “wideawake” frame of mind as they attempt to puzzle their way through. They can’t slip into the waking dream of story time.

Story resists reinvention. As the example of Finnegan’s Wake shows, storytelling is not something that can be endlessly rejiggered and reengineered. Story is like a circle. A circle is a circle. The minute you start fussing with the line you create a non-circle. Similarly, story only works inside narrow bounds of possibility. Imagine narrative transportation as this powerful brain capacity that is protected by a lock. The lock can only be opened with a specific combination. For as long as there have been humans, the ways of undoing the lock have been passed down through generations of storytellers. Going back to the earliest forms of oral folktales and moving forward through stage plays, to printed novels, and modern YouTube shorts, the fundamentals of successful storytelling have not changed at all.

When it comes to the fundamentals of story, there is not now--and never will be--anything new under the sun.

brands invest $44 billion in content every year.

The modern-day marketer balances left- and right-brain thinking. They use SEO and technology as an enabler and distributor, using content marketing creativity to build holistic content and SEO programs that result in measurable business outcomes.

SEO and content strategies need to be aligned for optimal marketing performance, yet the costs and time associated with training and development can negatively impact productivity, scale and revenue. This catch 22 makes it difficult to achieve such levels of collaboration, and divergence remains.

The bottom line: When you’re looking for information, everything that’s not what you need at this very minute is noise.

By such orchestrated interplay of all media, whole cultures could now be programed in order to improve and stabilize their emotional climate, just as we are beginning to learn how to maintain equilibrium among the world's competing economies

I'm not advocating anything; I'm merely probing and predicting trends. Even if I opposed them or thought them disastrous, I couldn't stop them, so why waste my time lamenting?

Resenting a new technology will not halt its progress.

Two years ago, the two greatest Jeopardy champions of all time got obliterated by a computer called Watson. It was a great victory for artificial intelligence--the system racked up more than three times the earnings of its next meat-brained competitor. For IBM’s Watson, the successor to Deep Blue, which famously defeated chess champion Gary Kasparov, becoming a Jeopardy champion was a modest proof of concept. The big challenge for Watson, and the goal for IBM, is to adapt the core question-answering technology to more significant domains, like health care. WatsonPaths, IBM’s medical-domain offshoot announced last month, is able to derive medical diagnoses from a description of symptoms. From this chain of evidence, it’s able to present an interactive visualization to doctors, who can interrogate the data, further question the evidence, and better understand the situation. It’s an essential feedback loop used by diagnosticians to help decide which information is extraneous and which is essential, thus making it possible to home in on a most-likely diagnosis. WatsonPaths scours millions of unstructured texts, like medical textbooks, dictionaries, and clinical guidelines, to develop a set of ranked hypotheses. The doctors’ feedback is added back into the brute-force information retrieval capabilities to help further train the system.

For Watson, ingesting all 2.5 million unstructured documents is the easy part. For this, it would extract references to real-world entities, like corporations and people, and start looking for relationships between them, essentially building up context around each entity. This could be connected out to open-entity databases like Freebase, to provide even more context. A journalist might orient the system’s “attention” by indicating which politicians or tax-dodging tycoons might be of most interest. Other texts, like relevant legal codes in the target jurisdiction or news reports mentioning the entities of interest, could also be ingested and parsed. Watson would then draw on its domain-adapted logic to generate evidence, like “IF corporation A is associated with offshore tax-free account B, AND the owner of corporation A is married to an executive of corporation C, THEN add a tiny bit of inference of tax evasion by corporation C.” There would be many of these types of rules, perhaps hundreds, and probably written by the journalists themselves to help the system identify meaningful and newsworthy relationships. Other rules might be garnered from common sense reasoning databases, like MIT’s ConceptNet. At the end of the day (or probably just a few seconds later), Watson would spit out 100 leads for reporters to follow. The first step would be to peer behind those leads to see the relevant evidence, rate its accuracy, and further train the algorithm. Sure, those follow-ups might still take months, but it wouldn’t be hard to beat the 15 months the ICIJ took in its investigation.