• Value, Value, Value!: What is the value for SMB’s? (We will focus on this in every presentation)
  • ChatBot SWOT:
  • Opportunities for SMBs: potential application in
  • Marketing: (content creation, targeted campaigns),
  • Customer service: (chatbots, sentiment analysis),
  • Data analysis (identifying trends, generating reports)
• Terminology: Lingo used in training: Differences Between AI, Machine Learning, and Deep Learning:
• Broad overview: The AI ChatBot Ecosystem and what is available to you: Major LLM Providers: (e.g., OpenAI, Google AI, Bing Microsoft Azure). – and major services.
• Comparing Offerings: A high-level comparison of features, functionalities, and pricing structures.
• SMB-friendly Solutions: LLM platforms with features and pricing tailored towards the needs of smb’s
• Staying Updated: Resources for staying informed about advancements in the LLM landscape
• Costs: Costs pro vs free and the various costs and roi for SMBs and potential additional costs
• Use Cases: What are appropriate use cases for business
• LLM Functionality: options: Visual, audio, chat, video, etc
• Strengths of AI ChatBot LLMs: Automation of tasks, data-driven insights, personalized experiences
• Threats to Consider: Risks – job displacement, security vulnerabilities, ethical concerns and privacy
• Finding Use Cases: LLMs relevant to different SMB depts (marketing, sales, customer service, etc)
• Integration planning: Initial integration steps for incorporating LLMs into existing workflows.
• Additional Resources: A list of helpful resources for further learning on LLM best practices, chatbot development tools, and use cases.

Setup and Usage:

• Account Creation and Access: Creating accounts and accessing ChatGPT/Gemini/Anthropic interfaces
• Basic Functionality: how to provide prompts and interpret LLM responses
• Exploring Features: Introduce available features and functionalities of the various LLM platforms
• Choosing an LLM? Machine Learning Models: An introduction to different types of machine learning models (supervised, unsupervised, reinforcement learning) and their applications.
• Bias in AI: Understanding implications, addressing bias, and ensuring fairness in AI models.
• AI in the Cloud: Overview of cloud AI services (AWS, Azure, Google Cloud, DigitalOcean/Paperspace), and how they can be leveraged for AI deployment and scalability.
• Practical AI Tools and Libraries: Introduction to popular tools and libraries such as TensorFlow, PyTorch, Scikit-learn, and their appropriate use cases.
• Security and Privacy in AI: Best practices for securing AI applications and managing data privacy.
• Evaluating AI Performance: Metrics and methods for assessing the performance of AI models.
• Case Studies and Industry Applications: Discussion of successful AI implementations across different sectors, focusing on relevant examples for SMBs.
• Accessing and Using AI LLMs: LLM access methods (Web, APIs, cloud platforms) and workflow integration.
• Understanding Output: Where and when do LLM’s get it wrong? Quality and repeatability
• Error Identification and Correction: How to identify and address potential errors or biases in LLM outputs
• Layman’s intro into API’s: What are some considerations. Is this possible for SMB’s. what knowledge is needed to tap into an API?

GPT Store:

• Brief Demo: Creating your own GPT
• Tailored Solutions: GPT models to address specific business needs and challenges. ex a model could be trained to understand and generate industry-specific terminology and processes, which could improve its usefulness and accuracy in tasks like customer support, technical documentation, and content creation.
• Integration and Automation: Custom models can be seamlessly integrated into existing business systems and workflows. This can lead to greater automation of processes like email management, scheduling, and CRM tasks, which can free up employees to focus on more complex or creative tasks.
• Enhanced Customer Experience: A custom GPT can provide a more personalized experience for customers. For instance, it could be used for building advanced chatbots that offer tailored advice, upsell services effectively, or handle complex customer queries more accurately.
• Innovative Services and Products: SMBs can use custom GPT models to develop innovative new products or services. For example, they could create unique educational tools, interactive experiences, or specialized advisory services that leverage the capabilities of AI.

• Summarizing/Analyzing Content: Condense documents, articles, or reports into concise summaries.
• Key Point Extraction: identify and extract the main points and arguments from complex content
• Sentiment Analysis: Analyze the sentiment of content, providing insights into audience perception.
• Topic Modeling: Find underlying themes and topics within large datasets of text or content.
• New Formats from Existing Content: transform content into different formats
• Content Refreshing: Updating older content, extending its lifespan and reach.
• Personalized Content Variations: Personalize content based on demographics, interests.
• Brainstorming Ideas: Generate ideas for blog post topics, sm content, or marketing campaign concepts.
• Drafting Content: Initial drafts of content based on provided prompts and kw’s.
• Content Formatting and formats: Formatting content to styles (blog posts, product descriptions).
• Fact-Checking and Editing: Identify inconsistencies and suggest edits for clarity and conciseness.
• Storytelling: Craft narratives, scripts, or poems based on provided prompts or outlines.
• Dialogue Writing: Generate realistic and engaging dialogue for fictional characters.
• Reporting: Generate reports and presentations by summarizing data and extracting information.

Social Media:

• Automated Post Creation: Generate sm posts based on pre-defined templates and brand guidelines.
• Personalized Content for Different Platforms: Tailor social media content for specific platforms (e.g., Twitter, Instagram) considering character limitations and audience preferences.
• Trending Topic Identification: identify trending topics and hashtags to leverage in content
• Engagement Optimization: suggest strategies for optimizing content for better engagement

Email:

• Personalized Email Marketing: AI can personalize email subject lines, greetings, and content based on customer data and past interactions.
• Automated Email Drafts: LLMs can generate initial drafts of marketing emails, sales follow-up emails, or customer service responses.
• A/B Testing Subject Lines: A/B testing subject lines
• Spam Filter Avoidance: Crafting email content that avoids spam filters and reaches inboxes.
• Email Tools and services: Curated list of tools and services

Ideation:

• Beyond Bullet Points: expand on initial ideas by suggesting related topics, exploring different angles, and generating potential outlines or storyboards.
• Breakthrough Creative Blocks: Overcome writer’s block with unexpected ideas and brainstorming.
• Research and Data Integration: AI can integrate relevant data and research findings into content ideas, providing a data-driven foundation.

• Prompt Engineering: Emphasize the importance of crafting clear, concise, and specific prompts to guide LLM responses.
• Designing Chatbot Flows: Strategies for designing chatbot conversations that are natural, informative, and achieve user goals for repeatable usage
• Training Chatbots for Accuracy: How to train a chatbots interaction with quality data to ensure accurate responses.
• Identifying User Intent: Introduce techniques for chatbots to understand user intent from natural language queries and provide relevant responses.
• Handling Unexpected Inputs: Discuss strategies for chatbots to handle unexpected user inputs, clarify ambiguities, and gracefully redirect conversations if necessary.
• Iterative Refinement: How to refine prompts based on initial LLM outputs to achieve desired results.
• Evaluating Quality: Equip participants with techniques to assess the quality of LLM outputs for factual accuracy, coherence, and alignment with intent.
• Output Formats: Generate different creative text formats like poems, code, scripts, musical pieces, email, letters, etc.
• Image Generation: Ideogram, MidJourney, LLM Studio, StabilityAI, Google, Bing, Dalle
• How to: – specific tools – prompting

Tools and Services:

• Curated List: List of AI content creation tools and services relevant to the workshop audience (e.g., copywriting assistants, social media content generators, content ideation platforms).
• Usage: Functionalities and target use cases of each tool, allowing participants to identify the most suitable options for their needs.
• Evaluation: Discuss the importance of evaluating and selecting AI tools based on factors like pricing, features, and integration capabilities with existing workflows.

Data Analysis:

• Q&A: Answer questions based on a given dataset or factual knowledge base.
• Data Summarization: Use it to extract key points and insights from large datasets of text or code to identify trends, and generate reports.
• Research assistance: Summarize research papers, find relevant sources, and generate citations.
• Education and Training: Create personalized learning materials, answer student questions, and generate quizzes for specific tasks.
• Customer Service: Power chatbots for basic inquiries, answer FAQs, and improve response times.
• Campaign Targeting: Using for ads
• Social Media Support: Finding stuff on Linkedin, Reddit and other socials.
  

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