Engineering
Generative AI
Generative AI is a subfield of artificial intelligence which focuses on the development of AI models that can generate output from a given input, such as natural language processing, image generation, music composition, and speech synthesis. By leveraging large datasets and Deep Learning models, generative AI can create data that previously did not exist, enabling new applications and opportunities for automation.
Learn Generative AI with the Practica AI Coach
The Practica AI Coach helps you improve in Generative AI by using your current work challenges as opportunities to improve. The AI Coach will ask you questions, instruct you on concepts and tactics, and give you feedback as you make progress.What is generative artificial intelligence?
- Generative Tech BeginsGenerative Tech is a new sector of technology that is rapidly developing and is characterized by the ability to generate unique pieces of content at the edge of the network in real time. Generative AI has opened up many opportunities for Founders, such as creating new types of games, legal claim mining services, and floor plan generation engines. Generative Tech also has the potential to replace curation with creation, and to provide low-friction interfaces. It is important for Founders to move quickly into the seams opening in the market, as this technology is still in its early stages and could easily become a feature of larger companies.
Prompt Engineering
The key to effective generative AI is prompt engineering, which involves designing prompts that allow the AI to generate high-quality outputs. This process requires careful consideration of the data inputs, as well as the desired output format and quality.- Prompt Engineering OverviewElvis delivers a one hour lecture on prompt engineer that is jam-packed with insights and actionable tips to get the most out of generative AI models in a variety of situations
- The Waluigi EffectThis viral post dives into why generative AI is so often wrong and explores techniques to avoid incorrectness
- Best practices for prompt engineering with OpenAI APIThe OpenAI team provides 8 specific tips on how to get stronger results from their generative models including positive and negative examples
Prompt Engineering for text-to-image
Prompt engineering for text-to-image generation is particularly challenging, as it requires the model to understand complex relationships between words and images.- A Beginner’s Guide to Prompt Design for Text-to-Image Generative ModelsLeonie shares insights on how to get the best results from the latest text-to-image AI models like DALL-E, StableDiffusion, and Midjourney
Using Generative AI in Product Development
Generative AI is increasingly being used inside of other tech products. Building with this technology comes with a new set of challenges and questions that are explored in this section.- Deterministic vs Non-deterministic productsBuilding with generative AI means adding non-determinism to your software. Umang explores what it means to build nondeterministic products and offers useful mental models and safeguards.
- AI Integration Walkthrough Tweet ThreadThis tweet thread explains how the team at Dayslice collaborated to quickly build and ship an AI-based feature to their users.
Chatbots
Chatbots are a popular application of generative AI, allowing companies to provide automated Customer Service and support. Careful consideration must be given to the design and implementation of chatbots to ensure they are effective.- Build ChatGPT-like Chatbots With Customized Knowledge for Your WebsitesIn this Article, Luciano shares techniques for getting the most out of the latest generative AI models in a chatbot setting. He discusses how to work around input length limitations and how to ensure continuity with historical context.
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