Personal GenAI in Your Pocket: LLMs and RAG on mobile device?

The future of work is undeniably mobile, and soon, a personal generative AI assistant, with access to your personal data might be your pocket companion. I recently discussed the opportunity in AI hardware and the immense computing power AI demands. With current GPU supply chain constraints, any additional processing power becomes a valuable asset.

While mobile devices can't match the raw power of GPUs and enterprise GenAI platforms, the sheer volume of processing power from billions of smartphones is undeniable. There are a staggering 6 billion smartphones globally, with Apple iPhones leading at 1.4 billion. This translates to a massive, untapped pool of processing power waiting to be harnessed. It becomes even more exciting when we consider the growing popularity of powerful mobile devices like M3-equipped iPads and Macs – the go-to choice for many business users.

Despite releasing their own open-source LLM in Q4 2023, Apple might seem to be behind in the LLM and GenAI race. However, recent news from March suggests collaboration with Google to bring their Gemini set of generative AI models to iPhones. This could be a game-changer, especially for on-device processing of multi-modal AI (text, vision, audio) while maintaining personal data privacy.

Imagine a future where generative AI is readily available on your mobile device, seamlessly leveraging your personal data to power RAG (Retrieval Augmented Generation) functions. No longer confined to the cloud, these AI assistants will be right in your pocket! While running LLMs directly on smartphones is still challenging, advancements in very small language models are happening rapidly. Mobile phone processors are also becoming increasingly powerful, paving the way for on-device GenAI capabilities. Even if the next iPhone offers just an improved Siri with GPT-like capabilities, the arrival of RAGs on mobile devices is likely just around the corner.

Here's why on-device RAGs have the potential to revolutionize how we work:

• Privacy Powerhouse: Apple devices are well known for robust biometric security and powerful Bionic chips, enabling on-device processing of your data, minimizing exposure risks, especially for business users juggling personal and confidential information.
• Tech Companies Collaboration: Apple cooperation with Google extends beyond search engines. This partnership could accelerate development, potentially leveraging Google's LLM expertise (including Small Language Models for on-device GenAI) while Apple ensures user privacy through on-device processing.

For business users, on-device RAGs hold immense potential:

• Secure, Personalized Content Creation: Generate customized reports, presentations, or marketing materials tailored to specific audiences, all while keeping your confidential data secure, on the device.
• Intelligent Communication: Craft clear, concise, and professional emails that reflect your writing style and tone, taking context of everything you have received or sent, saving you valuable time and effort.
• Enhanced Data Analysis: Uncover hidden insights and trends within complex private datasets directly on your mobile device or tablet, improving decision-making on the go.

On-device processing requires smaller, more efficient language models. This is where advancements in mobile-specific language models come into play. By combining the power of on-device processing with the efficiency of smaller LLMs, business users will be able to enjoy the benefits of RAGs without sacrificing significant performance.

The future holds intelligent assistance that respects privacy boundaries and empowers business users to be more productive on the go.

Are you ready to unleash the power of RAG in your pocket? When available, would you use it in your business?