The core challenge in generative AI development isn't writing code, but mastering prompt engineering to get desired results, similar to writing performant SQL.
Google Gemini offers different models like Pro and Flash for varying needs, supporting a large context window for inputs like video, audio, and code.
Obtain a free-tier API key easily through AI Studio without needing the full Google Cloud Platform, and test it immediately with a provided curl command.
Use AI Studio as a playground to test prompts and generate starter code, then implement it using the Node.js SDK for simple question-and-answer interactions.
Leverage Gemini's multimodal capabilities by uploading images via the Files API to analyze their content and automate tasks like generating descriptive filenames.
Create stateful chat interactions by sending the entire conversation history with each new message, a process the Gemini SDK manages automatically.
Use system instructions to formally define a model's persona, tone, and subject matter constraints, ensuring consistent and tailored responses for specific use cases.
Ensure reliable and structured data from the model by specifying the desired output format as JSON and defining its precise structure using a JSON Schema.
Real-world applications of Gemini include a movie recommendation system and a Dungeons and Dragons tool, but it can fail at tasks requiring strategic reasoning like blackjack.
Gemini Nano brings generative AI directly into the Chrome browser, enabling on-device processing for tasks like summarization and translation without API calls.
Use the experimental `window.ai` object in Chrome to implement features like text summarization and translation that run entirely on the user's device.
50:12Sam Witteveen
1:00:43Logan Kilpatrick
47:25
59:16Ryan J Salva
33:51Thomas Steiner
27:12Ryan J. Salva
25:17Scott Hanselman
30:07Mete Atamel
Jobs that call for the skills explored in this talk.
Gemma Analytics
Conrad Electronic SE