9 Demos of Gemini Omni and Gemini 3.5 in Action: The Future of AI Is Here

Google just dropped something that makes you stop and stare. Not a press release. Not a blog post with vague promises. Nine demos. Live. Raw. Showing exactly what Gemini Omni and Gemini 3.5 can do right now in June 2026. If you thought AI was already impressive, wait until you see what these models pull off. We’re talking real-time multimodal reasoning, seamless cross-tool execution, and a kind of fluid intelligence that feels less like a chatbot and more like a collaborative partner. Today, we’re breaking down all nine demos step by step — what they show, why they matter, and how you can start thinking about using these capabilities in your own work. No hype. Just the facts. [Source](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-omni-3-5-videos/) --- ## What Makes Gemini Omni and Gemini 3.5 Different? Before we dive into the demos, a quick primer. Gemini Omni is Google’s answer to the challenge of truly multimodal AI — it processes text, images, audio, and video natively, not as separate pipelines glued together. Gemini 3.5 builds on that with enhanced reasoning, longer context windows, and better tool use. Together, they represent a leap: AI that doesn’t just answer questions but actively helps you solve problems across formats and platforms. --- ## Demo 1: Real-Time Video Understanding The first demo shows Gemini Omni watching a live video feed of someone assembling a piece of furniture. As the person picks up a screwdriver, the model identifies the tool, predicts the next step, and offers spoken guidance — all in real time. **Why this matters:** This isn’t just object recognition. It’s temporal reasoning. The model understands sequence, intent, and context. Think of applications in remote assistance, manufacturing training, or even cooking guidance. --- ## Demo 2: Multimodal Data Analysis from a Single Image A user uploads a photo of a whiteboard covered in handwritten notes and a chart. Gemini 3.5 extracts the text, interprets the chart’s trends, and generates a clean summary with key insights — no manual transcription needed. **Practical takeaway:** For analysts, researchers, and project managers, this eliminates hours of manual data entry. Just snap a picture and get structured output. --- ## Demo 3: Code Generation from a Screenshot In this demo, the model is given a screenshot of a web page. It generates the corresponding HTML, CSS, and JavaScript — and then explains each block of code. The result is a fully functional replica. **Why developers should care:** This goes beyond boilerplate generation. It’s a design-to-code pipeline that works from any visual reference. Prototyping just got a whole lot faster. --- ## Demo 4: Long-Context Document Analysis Gemini 3.5 processes a 500-page PDF — an entire technical manual — and answers detailed questions about specific sections, cross-references, and even contradictions buried in different chapters. **The insight:** With extended context windows (measured in millions of tokens), you no longer need to chunk documents or summarize in advance. The model reads the whole thing and finds what you need. --- ## Demo 5: Interactive Voice Assistant with Visual Context A user asks, “What’s wrong with my plant?” while pointing their phone at a yellowing leaf. Gemini Omni listens, sees the leaf, and diagnoses a nitrogen deficiency — complete with care instructions. **Why this is a game changer:** True multimodal interaction. The model doesn’t just hear your words — it sees your world. This is the foundation for next-gen AI assistants that actually understand your environment. --- ## Demo 6: Automated Workflow with Tool Integration Here, Gemini 3.5 connects to a calendar, email, and a project management tool. Given a natural language request — “Schedule a review for the Q3 report with the team and send them the latest draft” — it creates the event, attaches the file, and composes the email. ASI Biont supports connecting to tools like Google Calendar and project management platforms via API — learn more at asibiont.com. **What this means for productivity:** The model becomes an orchestrator, not just a chat interface. It’s the difference between asking for instructions and having the work done for you. --- ## Demo 7: Real-Time Language Translation with Cultural Context A user speaks in English, and Gemini Omni translates into Japanese — but it doesn’t just convert words. It adjusts formality levels, adds appropriate honorifics, and even rephrases idioms to make sense culturally. **Why it stands out:** Most translation tools are literal. This demo shows understanding of pragmatics — how language works in context. For global teams, this is huge. --- ## Demo 8: AI That Generates and Edits Video In a surprising demo, Gemini 3.5 takes a short clip of a person speaking, analyzes the audio, and generates a new video with the speaker’s mouth movements synced to a rewritten script. The result is natural and seamless. **Ethical note:** Google emphasizes this is for creative and accessibility use cases (like dubbing). The implications for content creation, localization, and accessibility are massive — but so is the responsibility. --- ## Demo 9: Multi-Agent Collaboration The final demo is the most futuristic. Two instances of Gemini Omni are set up to debate a business problem — one playing the role of a product manager, the other a customer. They argue, refine ideas, and produce a joint recommendation. **The big idea:** AI agents can simulate perspectives, test arguments, and help humans make better decisions. This isn’t just a chatbot — it’s a brainstorming partner that never gets tired. --- ## What These Demos Tell Us About the Future Taken together, the nine demos paint a clear picture: AI is moving from answering questions to participating in workflows. The barriers between text, image, video, and voice are crumbling. And the ability to reason across formats in real time is no longer theoretical. For businesses, this means new possibilities in automation, customer support, content creation, and data analysis. For developers, it means richer APIs and fewer constraints. For everyone else, it means tools that actually understand what you’re trying to do. Google has shared these demos not just to show off, but to invite developers and enterprises to start building. The models are available now through Google AI Studio and Vertex AI. The question isn’t whether this technology works — it’s what you’ll build with it. --- *Want to stay ahead of AI trends and see how models like Gemini can work in your business? Follow the ASI Biont blog for deep dives, tutorials, and real-world use cases.*

9 Demos of Gemini Omni and Gemini 3.5 in Action: The Future of AI Is Here

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