Apple is gearing up for a significant push into AI in 2024, aiming to enhance its platforms with advanced technologies. A recent analyst note from JP Morgan sheds light on how Apple might navigate the competitive AI field by leveraging both external partnerships and its expertise in on-device processing.
This strategy aligns with Apple’s historical approach to integrating new technologies into its ecosystem.
The company is reportedly considering a partnership with a large language model (LLM) provider, such as Google, to license its Gemini LLM for use in Apple products. Concurrently, Apple is focused on developing smaller, local AI models that can operate directly on users’ devices, emphasizing privacy and efficiency. This approach was hinted at with the publication of Apple’s research on MM1, a compact model designed for local execution.
This two-pronged strategy suggests Apple is not putting all its eggs in one basket. Instead of committing solely to a proprietary LLM, which would rely on vast amounts of web data and potentially raise privacy concerns, Apple seems to be positioning itself to offer the best of both worlds.
By licensing an established LLM for broader needs and focusing on developing local models for privacy-sensitive tasks, Apple could offer a compelling AI experience that respects user privacy.
This methodology mirrors Apple’s existing strategy in web search, where it uses Google as the default search engine while also providing Spotlight, a local search tool that prioritizes the privacy of the user.
The reported discussions around licensing Google’s Gemini LLM and the development of tools like Ask, which relies on a local knowledge database, further illustrate Apple’s commitment to combining external AI capabilities with its proprietary, privacy-focused solutions.
Moreover, the analyst note highlights the financial benefits of this strategy, noting potential savings on infrastructure and enhanced consumer experiences in applications.
JP Morgan reaffirms its confidence in Apple’s strategic direction with an overweight rating and a price target of $215, indicating optimism about the company’s prospects in leveraging AI technology effectively.
