There are exciting new updates to the Gemini model family! → https://goo.gle/3CDZ5Sc - Gemini 2.0 Flash is now generally available - Gemini 2.0 Pro Experimental is available in AI Studio and Vertex AI - Gemini 2.0 Flash-Lite, an efficient, cost-effective model is now in public preview
Google AI for Developers
Technology, Information and Internet
AI for every developer. So what will you build?
About us
Our goal is to equip developers with the most advanced models to build new applications, helpful tools to write better and faster code, and make it easy to integrate across platforms and devices.
- Website
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https://goo.gle/ai-devs
External link for Google AI for Developers
- Industry
- Technology, Information and Internet
- Company size
- 10,001+ employees
Updates
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Unlock the secrets to step up your game's performance at our #GDC2025 sessions → https://goo.gle/3EtCuIH Leverage this technology for: - Practical applications of Gemini and Gemma - Creating new AI-powered game features - The future of game development with Google DeepMind
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Langbase enables devs to build, deploy, and scale composable AI agents with Gemini models. With faster response times, efficiency and lower costs devs can focus on innovation, not infrastructure. → https://goo.gle/3X9Ss0Z
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Gemini 2.0 Flash-Lite makes accurate, cost-effective, and fast voice interactions a reality.
Google's Gemini 2.0 Flash-Lite solved the RAG problem for Voice AI. Put your KB in Gemini 2.0 Flash-Lite's system prompt and have your agent make a tool call to Gemini 2.0 Flash-Lite. Accuracy: You get the right answer EVERY TIME. Latency: Response time is about 900 ms. Cost: 300 queries per day on a 50-page KB costs $26 per month ($7 with prompt caching), on par with RAG-as-a-service providers. RAG is one of the last mile problems for real-time conversational AI. It’s very difficult to get production-worthy recall from a RAG pipeline. Model-Assisted Generation (MAG) with Gemini 2.0 Flash-Lite just works. Period. My cofounder Adrian Cowham made the Pipecat demo video above. In it, MAG gets the right answer every time. In our test data set (the CrossFit Games Rulebook), the native RAG system for a leading closed-source Voice AI orchestration platform only found the answer 36% of the time. Gemini 2.0 Flash-Lite returned the answer 100% of the time! Our blog post with more details about how this works: https://lnkd.in/gTrQZFjV Link to the Daily Pipecat code: https://lnkd.in/g6c_gy5D Thanks for your help on this project Kwindla Hultman Kramer, Mark Backman, Vishal Dharmadhikari, Shrestha Basu Mallick, Ivan Solovyev!
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PaliGemma 2 mix is an upgraded vision-language model that supports image captioning, OCR, image Q&A, object detection, and segmentation. With sizes from 3B-28B parameters, there's a model for everyone. Get started. → https://goo.gle/4i1jOOU
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Learn how community spotlight winner Geshan Manandhar used Gemini 2.0 Flash’s real-time streaming capabilities to help professionals improve their resumes and career profiles on LinkedIn and GitHub to help with their job search. → https://goo.gle/4b4wy5c Have an AI project you’d like to share? Submit it to the Google AI Developers Community Spotlight program. → https://goo.gle/4b7gW0K
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Explore Gemma, a family of open models and select the best model for your use case based on size, capabilities, and tasks. → https://goo.gle/4hTjG3Z
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Agentic AI with Gemma lets AI proactively make decisions, pursue goals, and take actions without explicit instructions. This new approach is effective for developing intelligent solutions across various domains. Learn more and explore the demo using Gemma 2 → https://goo.gle/3CYymQo
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Get started with Gemma. These resources and demos will walk you through everything you need to know about open models. → https://goo.gle/3D2hcRU
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Gemini 2.0 Pro Experimental has a 2 million token context window and is our best model yet for coding performance and complex prompts. Try it for free today in Google AI Studio and Vertex AI → https://goo.gle/4aRumO7
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