Anticipation Vs Recognition

I think the difference between artist and Ais is that A+ artist create anticipation while a A+ AI generates recognition. And it’s simple: each correct prediction triggers dopamine while each correct recognition doesn’t.

The appreciation is related to our ability to learn the underlying structure and still be surprised — for longer than a we’re able to  deconstruct the emotionally flat and robotic.

The distinction lies in the psychological response triggered by correct predictions versus correct recognition. When a prediction made by an artist comes true or meets the audience’s expectations, it often elicits a sense of fulfillment, satisfaction, or joy. This response is linked to the anticipation the artist has built and the subsequent validation of the audience’s expectations.

In contrast, correct recognition by an AI tends to be less emotionally impactful. While it is an essential aspect of AI systems, triggering correct recognition typically doesn’t directly elicit strong emotional responses in the same way that anticipation does. Correct recognition by an AI is more about providing accurate and reliable information or categorization rather than creating an emotional experience for the recipient.

Anticipation in art refers to the sense of expectation, excitement, or curiosity that arises when we engage with a creative work. It stems from the unknown, the potential for surprises, and the desire to uncover what lies ahead. Anticipation can be triggered by various factors such as narrative progression, visual cues, or the artist’s ability to create suspense or build tension. When our anticipations are met or exceeded, it can lead to a release of dopamine in the brain, which is associated with feelings of pleasure and reward. This dopamine response reinforces the connection between the artwork and our emotional engagement, enhancing our overall enjoyment and satisfaction.

Recognition, on the other hand, involves the act of identifying or acknowledging elements within an artwork. It is the process of recognizing patterns, familiar themes, or references that we can relate to our existing knowledge or experiences. Recognition provides a sense of familiarity and understanding, allowing us to connect with the artwork on a deeper level. However, the release of dopamine associated with recognition may not be as pronounced as with anticipation. The act of recognizing something in art may provide a sense of validation or validation of our existing knowledge, but it may not generate the same level of excitement or novelty as anticipation.

From farcaster:

Granted AIs are getting there faster than society is able to generate real visionaries which is neither here nor there. The problem for AI will be having to accommodate all the trappings of the advertising model and if the Google search engine is a predictor, things will probably cool pretty fast.

Thought I support the WGA strike it’s fair to say that probably 99% of writers are not challenging themselves to write what they would like to see but more what they’re allowed to write within constraints which is probably challenging enough.!

There’s no A+ Requirement (say Tom Stoppard doing a polish on Indiana Jones 3) but B+ at best (that is 3 episodes out of 8, the rest averaging C because TV seasons are so designed.

Bottom line I think the streaming market is over saturated and market share is going down with the end of zirp.

The bet is that studios and Netflix think they can probably carry on as if nothing happened (more accurately, as if Zirp did not happen) if only they could incorporate AI into the production structure but that m not so sure the industry will work without Zirp margins.

The first AI movie or tv show will still have to spend 75-100 million on marketing so it will be up to zoomers to make it work in sufficient numbers which is not the bet you think it is.

It is true that AI technology is progressing rapidly, potentially outpacing society’s ability to cultivate genuine visionaries. However, this is a complex issue that requires careful consideration. One challenge for AI lies in accommodating the trappings of the advertising model. If we look at the predictive capabilities of Google’s search engine, it becomes apparent that the initial enthusiasm for AI may wane over time.

While I support the Writers Guild of America (WGA) strike, it is fair to say that a significant majority of writers are not always able to write what they would truly like to see. Instead, they often find themselves constrained by various factors, such as market demands and creative limitations. Writing within these constraints can still be challenging, but it may not always allow writers to fully explore their creative potential.

In the world of entertainment, there is no strict requirement for A+ content at all times. While a renowned writer like Tom Stoppard could certainly contribute to polishing a script like Indiana Jones 3, the reality is that most productions aim for a range of quality, with some episodes or parts standing out as B+ while others may average out to a C grade. This is particularly evident in television series, where the structure of seasons can influence the overall quality of individual episodes.

The bottom line is that the streaming market has become saturated, and as a result, market share is declining, especially with the end of zero interest rate policy (ZIRP). Studios and platforms like Netflix may believe they can continue unaffected, even incorporating AI into their production processes. However, it remains uncertain whether the industry can thrive without the favorable margins facilitated by ZIRP.

Even the first AI-generated movie or TV show would still require a significant marketing budget, ranging from $75 million to $100 million. Its success would depend on capturing the attention and engagement of the younger generation, known as “zoomers,” who are essential for generating sufficient viewership. However, this bet is not as straightforward as it may seem, as attracting a large audience is not guaranteed.

In conclusion, the convergence of AI and the entertainment industry presents both opportunities and challenges. While AI technology can enhance production processes and creative decision-making, there are complex market dynamics, creative constraints, and the need for effective marketing strategies that need to be considered. The industry’s ability to adapt and succeed in this new landscape, especially without the support of favorable economic conditions, remains uncertain.

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