Gemini 1.5 AI News List | Blockchain.News
AI News List

List of AI News about Gemini 1.5

Time Details
2026-05-27
17:14
Gemini Spark Demos Reveal Agentic Power

According to @GeminiApp, Google will demo Gemini Spark and Daily Brief with live Q&A today at 11:30 AM PT, highlighting new agentic workflows.

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2026-04-08
21:34
Google launches Gemini-powered NotebookLM upgrade and new Notebooks with multimodal AI: 5 business-ready features

According to Sundar Pichai, Google published new details on Gemini-powered Notebooks and an upgraded NotebookLM on the Google Blog. According to Google Blog, Notebooks introduces a Gemini-native workspace that lets teams upload documents, data tables, and media, then ask grounded questions with source citations via Gemini 1.5, improving research and due diligence workflows. As reported by Google Blog, the new NotebookLM adds multimodal support, turning uploaded files and web pages into autogenerated study guides, outlines, and summaries with inline references, which reduces manual synthesis for product ops and client-facing teams. According to Google Blog, NotebookLM now supports linked data packs and shared, read-only notebooks for governance, helping enterprises maintain compliance when distributing AI-generated briefs. As reported by Google Blog, enterprise admins gain expanded data controls and audit visibility for Gemini interactions inside Notebooks and NotebookLM, aligning with regulated industry needs. According to Google Blog, early user pilots cite faster knowledge onboarding and proposal drafting, pointing to immediate ROI opportunities in content operations, RFP response, and internal training.

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2026-03-14
23:30
Qwen 3.5 vs GPT-4o, Claude Sonnet, Gemini 1.5: Latest Multimodal Analysis and Cost Efficiency for 2026 AI Agents

According to God of Prompt on X (Twitter), GPT-4o is multimodal but expensive to deploy at scale, Claude Sonnet delivers great quality with high compute cost, Gemini 1.5 is multimodal yet resource-heavy, while Qwen 3.5 is natively multimodal and designed for real-world agents without proportionally scaling compute budgets. As reported by the post’s comparison, this positions Qwen 3.5 as a cost-efficient choice for agentic workflows where latency and token throughput matter. According to the same source, businesses building voice, vision, and tool-using agents can reduce infrastructure overhead by prioritizing models with native multimodality and optimized serving footprints, indicating Qwen 3.5 may unlock lower total cost of ownership versus peers in production settings.

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