The future of AI assistants: from ChatGPT to Gemini Nano

AI assistants have come a long way from answering simple questions to helping people write code, manage tasks, and even summarise meetings. But in 2025, a new shift is underway. The next generation of AI assistants is not just smarter; it’s faster, more private, and deeply embedded in the devices we use every day.

From ChatGPT to Gemini Nano, the story of AI assistance is one of evolution: from cloud-based chatbots to on-device intelligence. As models become smaller, faster, and more multimodal, they’re transforming how humans interact with machines, turning AI from a digital companion into a seamless part of everyday life.

A brief history of AI assistants

The journey of AI assistants began with voice-based systems like Siri, Alexa, and Google Assistant. These tools followed simple instructions, setting alarms, playing music, or reading the news, all powered by cloud-based servers.

Then came ChatGPT, OpenAI’s conversational model that changed everything. Launched in late 2022, ChatGPT was the first AI system that could write essays, generate code, draft marketing copy, and hold natural conversations. Unlike traditional assistants, it understood nuance, followed context, and responded in complete paragraphs.

Its success sparked an arms race across the industry. Anthropic’s Claude, Microsoft’s Copilot, and Google’s Bard (now Gemini) all followed, pushing the limits of what AI could do for ordinary users. But while these models were powerful, they were also dependent on the cloud, meaning they required high-speed internet, large data centres, and massive computing power. That dependency is now starting to fade.

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How ChatGPT changed everything

ChatGPT introduced the world to generative AI systems capable of producing new text, images, and code from prompts. It was the first AI assistant to show that machines could generate, not just retrieve, information.

For millions of users, ChatGPT became a creative partner: summarising reports, brainstorming ideas, and even helping with professional writing. It redefined what people expected from AI assistants, not just transactional support, but collaboration.

However, ChatGPT’s strength was also its limitation. Its reliance on cloud infrastructure meant it couldn’t run offline or on low-power devices. Each interaction required sending data to remote servers for processing, raising latency, privacy, and accessibility concerns.

That’s where Gemini Nano comes in: a model built to bring generative AI down from the cloud and directly into your phone.

Read more: How Google Gemini Is Changing the Future of AI Assistants

Enter Gemini Nano: AI goes mobile

From cloud to chip

Gemini Nano, developed by Google DeepMind, is the smallest and most efficient version of Google’s Gemini AI family. Unlike ChatGPT, which runs on powerful servers, Gemini Nano operates entirely on-device, meaning it performs AI tasks locally without an internet connection.

This marks a major milestone for AI assistants. By integrating directly into Android’s operating system, Gemini Nano delivers lightning-fast responses, preserves user privacy, and reduces data dependency. It powers features like Smart Reply in Gboard, Summarise in Recorder, and other generative functions across Android apps.

The result? AI assistance that feels instantaneous, contextual, and personal, whether you’re online or offline.

Why size matters

Gemini Nano achieves its efficiency through model compression techniques like quantisation, distillation, and pruning. In simple terms, engineers teach a smaller model to replicate the intelligence of a larger one by removing unnecessary layers and optimising its parameters.

This downsizing allows Gemini Nano to fit inside mobile processors such as Google’s Tensor G3, Qualcomm’s Snapdragon AI Engine, and Samsung’s Exynos chips. Despite its size, it retains strong reasoning and language understanding capabilities enough to handle summarisation, transcription, and short-form content generation directly on the device.

While ChatGPT depends on vast cloud resources, Gemini Nano’s design brings that same creative potential to low- and mid-tier smartphones, a significant step towards democratising access to AI tools.

AI for everyone

What makes Gemini Nano revolutionary is not just how it works, but who it serves. By making generative AI possible on affordable devices, Google is extending access to millions of users who were previously excluded due to cost or connectivity barriers.

In markets like Africa, India, and Southeast Asia, where mobile internet can be slow or expensive, on-device AI could redefine productivity and communication. People will be able to translate languages, summarise conversations, or draft messages instantly, all without relying on the cloud.

This move represents a major step in making AI universal, bridging the digital divide and setting the stage for a new wave of inclusion-led innovation.

The new era of multimodal AI assistants

The next chapter of AI assistants is not just text-based, it’s multimodal. Models like Google Gemini, OpenAI’s GPT-4o, and Anthropic’s Claude 3 can process and generate across multiple inputs, from voice and text to images and video.

This means an assistant can now “see” a photo, “hear” an audio clip, and “respond” with an intelligent answer. For instance, you could show an AI a screenshot of your calendar and ask it to schedule a meeting or upload a chart and have it write a short report.

By combining perception, reasoning, and communication, multimodal AI brings assistants closer to how humans think. It turns AI from a reactive tool into an adaptive companion that learns and operates across all digital contexts.

Gemini Nano’s integration into Android hints at this direction. It’s not just a text model; it’s the foundation for on-device assistants that can understand voice, camera input, and context simultaneously.

What this means for users and tech professionals

For everyday users, the shift from ChatGPT to Gemini Nano means AI that’s faster, safer, and always available. Instead of waiting for server responses or worrying about privacy, they get real-time intelligence that fits seamlessly into their apps and workflows.

For tech professionals, this evolution opens new possibilities. Developers can now build AI assistants that run locally on devices, removing the cost and complexity of cloud infrastructure. Product designers can rethink how users interact with apps through natural conversation, visual context, and real-time collaboration.

Gemini Nano also enables hybrid AI architectures, where tasks start on-device and scale to the cloud only when necessary, striking the right balance between efficiency and capability. This is more than a technological upgrade; it’s a redesign of how AI connects with people.

The road ahead

The future of AI assistants will be defined by three words: personal, private, and pervasive. As models become smaller and smarter, they’ll live on every device, not just in servers or premium phones.

ChatGPT made AI conversational. Gemini Nano is making it mobile. Together, they mark two stages in a broader journey: from intelligent systems we visit to intelligent systems that live with us.

As computing becomes more personal, AI will fade into the background, powering voice commands, visuals, and decisions without needing to be asked. The assistant of the future won’t just answer questions; it will anticipate them.

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