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Traditional marketing directly focuses on the needs of consumers; meanwhile some believe the shift AI may cause, will lead marketing agencies to manage consumer needs instead. [ 1 ] Artificial Intelligence is used in various digital marketing spaces, such as content marketing , email marketing , online advertisement (in combination with machine ...
The creator economy or also known as creator marketing and influencer economy, is a software-driven economy that is built around creators who produce and distribute content, products, or services directly to their audience, leveraging social media platforms and AI tools. [1]
Marketing is a complex field of decision making which involves a large degree of both judgment and intuition on behalf of the marketer. [10] The enormous increase in complexity that the individual decision-maker faces renders the decision-making process almost an impossible task. The marketing decision engine can help distill the noise.
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
Generative design, one of the four key methods for lightweight design in AM, is commonly applied to optimize structures for specific performance requirements. [25] Generative design can help create optimized solutions that balance multiple objectives, such as enhancing performance while minimizing cost. [26]
Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...
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A key breakthrough was LSTM (1995), [note 1] a RNN which used various innovations to overcome the vanishing gradient problem, allowing efficient learning of long-sequence modelling. One key innovation was the use of an attention mechanism which used neurons that multiply the outputs of other neurons, so-called multiplicative units . [ 11 ]