Marketing and AI
Two important processes for foundation models are:
- Pre-training: this involves using a massive unstructured dataset to train an initial version of the model
- Fine-tuning: this involves using a smaller, targeted dataset to train the foundation model for use in a specific context
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Fine tuning is essential to differentiating content for content marketing purposes.
Wiley, Generative AI for Business Leaders, Udacity, 2024
Primary Areas of Business Challenges Addressed by GitHub Copilot
- Developer efficiency and productivity : Improving developer speed and reducing code creation time are central goals. The LLM aims to suggest code completions, functions, and tests, alleviating repetitive tasks and accelerating development cycles.
- Code correctness and security : The L
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Wiley, Generative AI for Business Leaders, Udacity, 2024
These could be adapted to a marketing team:
Creative efficiency and productivity
Content correctness and security
Personalized creator experience
How to Think about Generative AI from a Business Perspective
learn.udacity.comGenAI limitations:
—Factually incorrect / hallucinations
— Irreproducibility
— Validation and attribution
— Reductive
— Knowledge Cutoff
Benefits of Generative AI
Individual
Individual
- Customized content: AI systems can generate personalized news updates, recipes, vacation recommendations, and other content based on your preferences and interests.
- Assistance with creative tasks: Generative AI tools can help with tasks like emails, writing stories, poems, song lyrics, or scripts by generating
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Wiley, Generative AI for Business Leaders, Udacity, 2024
RAG, which stands for "Retrieval Augmented Generation," is a strategy in artificial intelligence where a large language model (LLM) retrieves relevant information from an external knowledge base (like a database or document collection) before generating a response to a user query, ensuring the response is more accurate and contextually relevant by ... See more
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This is what Nimble Press will do!
The Modern AI Marketer in GPT Era - Pam Didner
pamdidner.com
Book to read in 2 hours
Introduction to Generative AI
learn.udacity.comAttention Is All You Need (2017)(opens in a new tab) by Vaswani et al.
AI (Artificial Intelligence) and ML (Machine Learning) are two overlapping categories , in which popular applications involve tasks that require human-like intelligence and learning. AI encompasses any computer program aiming to replicate human intelligence, while ML algorithms use statistical models to perform tasks without explicit programming.
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Wiley, Generative AI for Business Leaders, Udacity, 2024
About half of workers (52%) say they’re worried about the future impact of AI use in the workplace, and 32% think it will lead to fewer job opportunities for them in the long run, according to a new Pew Research Center survey.
U.S. Workers Are More Worried Than Hopeful About Future AI Use in the Workplace
Pew Research Report, 2/2025