A summary of a workshop presented at PyCon US on building software with LLMs, covering setup, prompting, building tools (text-to-SQL, structured data extraction, semantic search/RAG), tool usage, and security considerations like prompt injection. It also discusses the current LLM landscape, including models from OpenAI, Gemini, Anthropic, and open-weight alternatives.
Google's AI function brings Gemini-powered language models right into your spreadsheet cells without any add-ons. With it, you can generate fresh text, summarize blocks of data, categorize entries, or even guess sentiments—all by typing a simple formula.
The article provides examples such as:
- *sentiment analysis* ```=AI("Is this customer feedback positive, negative, or neutral?", A2)```
- *data categorization* `=AI("Classify this expense as Travel, Office, or Other", D3)`
- *simple calculations* `=AI("Add the numbers in these cells", A1:A5)`
The article provides examples such as:
- *sentiment analysis* ```=AI("Is this customer feedback positive, negative, or neutral?", A2)```
- *data categorization* `=AI("Classify this expense as Travel, Office, or Other", D3)`
- *simple calculations* `=AI("Add the numbers in these cells", A1:A5)`
Google will host a separate event, 'The Android Show: I/O Edition,' on May 13th to discuss Android updates, a week before Google I/O. This suggests Google I/O will focus more on Gemini and other AI efforts. Android will still be present at I/O, but it's no longer the primary focus.
DeepMind is prioritizing readiness, proactive risk assessment, and collaboration with the wider AI community as they explore the frontiers of AGI, focusing on mitigating risks like misuse and misalignment.
This tutorial demonstrates how to integrate Google’s Gemini 2.0 with an in-process Model Context Protocol (MCP) server using FastMCP, creating tools for weather information and integrating them into Gemini's function calling workflow.
Google's Gemini 2.5 Flash model is a new, faster, and more cost-effective model with adjustable 'thinking' capabilities. The article details how to use it with llm-gemini, explores pricing differences compared to Gemini 2.0 Flash, and shares example SVG outputs.
This blog post details an experiment testing the ability of LLMs (Gemini, ChatGPT, Perplexity) to accurately retrieve and summarize recent blog posts from a specific URL (searchresearch1.blogspot.com). The author found significant issues with hallucinations and inaccuracies, even in models claiming live web access, highlighting the unreliability of LLMs for even simple research tasks.
The Gemini API documentation provides comprehensive information about Google's Gemini models and their capabilities. It includes guides on generating content with Gemini models, native image generation, long context exploration, and generating structured outputs. The documentation offers examples in Python, Node.js, and REST for using the Gemini API, covering various applications like text and image generation, and integrating Gemini in Google AI Studio.
Google is upgrading Google Assistant users on mobile to Gemini, offering a new AI-powered assistant experience. The classic Google Assistant will no longer be accessible on most mobile devices later this year. Updates are also coming to tablets, cars, headphones, watches, and home devices.
Google is renaming 'Gemini Extensions' to 'apps' in the latest beta version of the Google app on Android. The change includes updates to the account menu and the full page for enabling and disabling each tool.
