Marketing and AI
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
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!
How to Think about Generative AI from a Business Perspective
learn.udacity.comGenAI limitations:
—Factually incorrect / hallucinations
— Irreproducibility
— Validation and attribution
— Reductive
— Knowledge Cutoff
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
Strategic Prompting for Guided Generation
- Providing clear instructions and constraints : Airbnb used prompts to guide the GenAI models towards generating specific types of content, such as recommendations tailored to a guest's budget and travel preferences, agent suggestions for resolving inquiries, or chatbot paraphrases that maintained natural l
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Wiley, Generative AI for Business Leaders, Udacity, 2024
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
Key Innovations in Model Architecture
Two innovations have driven a lot of the recent improvements in Generative AI:
Two innovations have driven a lot of the recent improvements in Generative AI:
- Encoder-decoder system: two neural networks that compress and then expand the data
- Attention mechanism: ensures that important information isn't lost in the compression and expansion process, by "paying attention" to the important pi
Introduction to Generative AI
Wiley, Generative AI Business Leaders, Udacity, 2025
Foundation for the GTP.
Introduction to Generative AI
learn.udacity.comAttention Is All You Need (2017)(opens in a new tab) by Vaswani et al.
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