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M.T. Fletcher – WHY AGENCIES ARE OBSESSED WITH PITCHING ON PROCESS INSTEAD OF TALENT
“Every presentation featured a proprietary process designed by the agency. A custom approach to identify targets, develop campaigns and optimize impact—with every step of the process powered by AI, naturally.”
“The key to these one-of-a-kind models is apparently finding the perfect combination of circles, squares, diamonds and triangles…Arrows abounded and ellipses are replacing circles as the unifying shape of choice among the more fashionable strategists.”
“The only problem is that it’s all bullshit.”
“A blind man could see the creative ideas were not developed via the agency’s so-called process, and anyone who’s ever worked at an agency knows that creativity comes from collaboration, not an assembly line.”
“And since most clients can’t differentiate between creative ideas without validation from testing, data has become the collective crutch for an industry governed by fear.”
“If a proprietary process really produced foolproof creativity, then every formulaic movie would be a blockbuster, every potboiler novel published by risk-averse editors would become a bestseller and every clichéd pickup line would work in any bar in the world.”
FEATURED POSTS
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Composition and The Expressive Nature Of Light
http://www.huffingtonpost.com/bill-danskin/post_12457_b_10777222.html
George Sand once said “ The artist vocation is to send light into the human heart.”
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Photography basics: Solid Angle measures
http://www.calculator.org/property.aspx?name=solid+angle
A measure of how large the object appears to an observer looking from that point. Thus. A measure for objects in the sky. Useful to retuen the size of the sun and moon… and in perspective, how much of their contribution to lighting. Solid angle can be represented in ‘angular diameter’ as well.
http://en.wikipedia.org/wiki/Solid_angle
http://www.mathsisfun.com/geometry/steradian.html
A solid angle is expressed in a dimensionless unit called a steradian (symbol: sr). By default in terms of the total celestial sphere and before atmospheric’s scattering, the Sun and the Moon subtend fractional areas of 0.000546% (Sun) and 0.000531% (Moon).
http://en.wikipedia.org/wiki/Solid_angle#Sun_and_Moon
On earth the sun is likely closer to 0.00011 solid angle after athmospheric scattering. The sun as perceived from earth has a diameter of 0.53 degrees. This is about 0.000064 solid angle.
http://www.numericana.com/answer/angles.htm
The mean angular diameter of the full moon is 2q = 0.52° (it varies with time around that average, by about 0.009°). This translates into a solid angle of 0.0000647 sr, which means that the whole night sky covers a solid angle roughly one hundred thousand times greater than the full moon.
More info
http://lcogt.net/spacebook/using-angles-describe-positions-and-apparent-sizes-objects
http://amazing-space.stsci.edu/glossary/def.php.s=topic_astronomy
Angular Size
The apparent size of an object as seen by an observer; expressed in units of degrees (of arc), arc minutes, or arc seconds. The moon, as viewed from the Earth, has an angular diameter of one-half a degree.
The angle covered by the diameter of the full moon is about 31 arcmin or 1/2°, so astronomers would say the Moon’s angular diameter is 31 arcmin, or the Moon subtends an angle of 31 arcmin.
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Google – Artificial Intelligence free courses
1. Introduction to Large Language Models: Learn about the use cases and how to enhance the performance of large language models.
https://www.cloudskillsboost.google/course_templates/5392. Introduction to Generative AI: Discover the differences between Generative AI and traditional machine learning methods.
https://www.cloudskillsboost.google/course_templates/5363. Generative AI Fundamentals: Earn a skill badge by demonstrating your understanding of foundational concepts in Generative AI.
https://www.cloudskillsboost.google/paths4. Introduction to Responsible AI: Learn about the importance of Responsible AI and how Google implements it in its products.
https://www.cloudskillsboost.google/course_templates/5545. Encoder-Decoder Architecture: Learn about the encoder-decoder architecture, a critical component of machine learning for sequence-to-sequence tasks.
https://www.cloudskillsboost.google/course_templates/5436. Introduction to Image Generation: Discover diffusion models, a promising family of machine learning models in the image generation space.
https://www.cloudskillsboost.google/course_templates/5417. Transformer Models and BERT Model: Get a comprehensive introduction to the Transformer architecture and the Bidirectional Encoder Representations from the Transformers (BERT) model.
https://www.cloudskillsboost.google/course_templates/5388. Attention Mechanism: Learn about the attention mechanism, which allows neural networks to focus on specific parts of an input sequence.
https://www.cloudskillsboost.google/course_templates/537