Generative AI for Leaders & Business Professionals

Empower leaders and business professionals to leverage ChatGPT basics—from sign-up and the UI to chats, custom GPTs, plugins, and custom instructions—for practical, real-world use.

Learn to generate images for free daily using Bing image creator, craft effective prompts, and compare DALL-E 3 with other tools, while saving, downloading, and customizing outputs.

Explore olly.social, a one-time-setup chrome extension that generates comments in your voice, checks post virality, and creates similar posts across LinkedIn, Facebook, Instagram, YouTube, and Twitter.

Learn to set up Midjourney on Discord, join the beta, and generate images using the imagine command, with options to upscale, vary, pan, zoom, and describe prompts.

Claude-2 introduction by Anthropic presents a text-to-text AI with an API that uploads and chats with up to 500 pages of documents, offering data-friendly insights differing from Bard or ChatGPT.

Explore Runway's video generation tools, including gen two, motion brush, and text-to-video prompts, to create, edit, and upscale AI videos with credits.

Showcase Gen-3’s state-of-the-art video generation with realistic motion and granular visuals, and teach prompt design, cost analysis, and workflows across Runway and Claude.

Discover the langflow UI for designing AI workflows, creating projects and flows, wiring input and output nodes, and integrating OpenAI language models with prompts and system messages.

Explore building a large language model flow with components, inputs, outputs, data sources, a prompt template, and flow control to streamline interactions.

Learn to install and run Llama 3 locally with Ollama and explore its features. Connect it to Visual Studio Code as a copilot replacement for code generation and math reasoning.

Define artificial intelligence as systems that learn, adapt, and decide, and explain how AI collaborates with humans, outlining narrow, general, and super intelligent AI, plus machine learning and multimodal capabilities.

Explore unsupervised learning, where algorithms identify patterns and cluster data without labels, grouping items like fruits by shape or color and customers by buying habits.

Learn reinforcement learning, where an agent acts in an environment and earns rewards or penalties, guided by positive and negative reinforcement. The approach powers image, video, and text generation tools.

Train models on labeled data to map inputs to outputs and manage false positives and false negatives, as seen in email spam detection.

Explore computer vision, a subset of artificial intelligence that lets machines interpret and categorize visual data in images and videos, using modern models like Stable Diffusion XL and DALL-E 3.

Explore expert systems that emulate human decision-making by encoding expert knowledge and applying reasoning with if-then rules, bridging human expertise and computer diagnosis.

Neural networks imitate the brain's interconnected neuron structure with input, hidden, and output layers, learning through training to process human language and recognize patterns, including voice and speech.

Explore generative adversarial networks where a generator creates data and a discriminator critiques it in a continual feedback loop to improve image synthesis and style transfer.

Explore how variational autoencoders encode images into compact representations with an encoder and reconstruct them through a decoder, balancing reconstruction quality with reduced processing power requirements.

RNNs retain past context in a looping memory to process sequential data, enabling text understanding and predicting future values.

Contrast gans and transformers by showing gan content generation refined through discriminator feedback, and transformers applied on top of gans to summarize the generated information.

Discover how reference text guides language models, reducing fabrication by constraining outputs to supplied material, using instruction plus reference content, and repurposing documents with cited passages.

Explain how to let models think through their own reasoning using chain-of-thought, inner monologue, and sequences of queries to improve answer reliability. Apply these tactics to solar installation cost calculations.