How to authenticate the Google Gen AI SDK.

Large language models (LLMs) like Gemini are incredibly powerful, but they have a fundamental limitation: their knowledge is frozen at the time they were trained. They don't have access to live, real-time information from the internet. This means if you ask about today's news, stock prices, or the weather, they can't give you a current answer.

This is where grounding comes in. Grounding connects the model to external, authoritative sources of information, like Google Search. By giving Gemini the ability to search the web, we can unlock its potential to answer questions about the here and now, ensuring its responses are timely, accurate, and verifiable. 🌐

How to turn Google Docs into speech.

How to turn Google Docs into speech.

How to build an AI interactive voice agent (IVA) with Gemini Multimodal Live & Twilio.

As artificial intelligence (AI) continues to evolve, one area that remains crucial is intent classification. In the midst of the constant excitement about generative models like GPT-4 and their abilities to produce human-like text, one might wonder, do we still need intent classification? The answer is a resounding yes and is rooted in the deterministic nature of intent classification, a trait that generative AI models, no matter how advanced, cannot currently replicate.

Companies across the globe are using data to unlock insights, cut costs, and grow revenue. When collected properly, data can tell a story about how to improve current workflows and manage teams better. Sales teams can unlock exponential potential by harnessing data and using it to drive decision making.