Understanding AI: Integrating Features vs. Developing Standalone Products

Popular tech YouTuber Marques Brownlee recently delved into the debate of AI as a feature versus AI as a product. This distinction has become more pronounced with recent advancements in AI technology.

One commenter on the video remarked, “AI as a feature was normal before; smartphones with assistants are proof. AI as a product started recently with the advancement of LLMs, with people using AI as a buzzword without fully understanding it.”

Understanding AI as a Feature

AI as a feature involves integrating AI technologies into existing products to enhance their capabilities. Here are some examples:

• Chatbots: AI-powered chatbots are integrated into websites and applications to provide instant customer support, answer frequently asked questions, and even guide users through processes. This feature improves user experience by providing quick and efficient responses, reducing the need for human intervention.

• AI Audio Enhancements: Audio enhancement features use AI algorithms to improve sound quality in real-time. This can include noise reduction, echo cancellation, and even upscaling audio to higher quality. These enhancements are commonly found in video conferencing tools, music streaming services, and hearing aids, significantly improving the auditory experience.

• AI Video Upscaling: AI-powered video upscaling involves using machine learning algorithms to increase the resolution of videos, making them sharper and more detailed. This feature is especially useful for streaming services and video editing software, allowing users to enjoy higher-quality visuals without needing to re-record or reshoot content.

A notable example of AI as a feature is Microsoft’s Copilot Pro. This AI assistant is integrated into Microsoft’s enterprise products such as Word, Excel, PowerPoint, and Outlook. Copilot Pro helps users create documents, analyze data, and manage communications more efficiently by providing intelligent suggestions, automating repetitive tasks, and offering real-time insights.

AI as a Product

In contrast, AI as a product refers to standalone AI-driven applications designed for specific tasks or services. Here are some examples:

• Humane AI Pin: The Humane AI Pin was launched as an innovative AI product aimed at providing personalized assistance and connectivity. It was marketed for a year through ads and events, promising to revolutionize how users interact with technology. Despite its promising concept, the product received mixed reviews. Users reported issues with its functionality, calling it “totally broken” and highlighting “glaring flaws.” Marques Brownlee even described it as “the worst product I’ve ever reviewed.” Despite raising $240 million and being valued at $1 billion, the company failed to deliver on its futuristic promises after five years of development.

• Rabbit R1: Created by Rabbit Inc. and design firm Teenage Engineering, the Rabbit R1 was hailed as the “future of human-machine interface” at the Mobile World Congress (MWC) 2024. It was designed to provide advanced AI-driven interactions. However, reviews pointed out significant issues such as its inability to browse the web, make calls, or send texts, and its short battery life requiring multiple recharges with slow charging. Reviewers, including Brownlee, described it as “another AI in a box” and “barely reviewable,” emphasizing its flaws over its intended innovations.

A commenter noted, “A product is just a feature that can be monetized now or later,” suggesting that the distinction between features and products may be fluid and dependent on how they are marketed and monetized.

Seamless AI Features

Big tech companies continue to integrate AI features into their existing products, enhancing their capabilities without creating standalone AI products. At the latest WWDC, Apple unveiled Apple Intelligence, a suite of AI-driven enhancements designed to improve existing features on Apple devices. Examples include:

• Improved Writing: Apple Intelligence offers features that assist users with writing by providing grammar and style suggestions, predicting text, and offering contextual recommendations. This helps users write more efficiently and effectively.

• Creative Expression: AI-powered tools assist users in creative tasks such as photo and video editing, music creation, and graphic design. These features use machine learning to automate complex processes, allowing users to achieve professional-quality results with ease.

• Task Automation: Apple Intelligence can automate repetitive tasks across various apps, saving users time and effort. For example, it can schedule reminders, sort emails, and organize files based on user preferences and behaviors.

Apple’s approach of embedding intelligent features within its devices, rather than marketing them as separate products, exemplifies AI as a feature. This seamless integration enhances user experience without requiring them to adopt entirely new products.

Is There a Clear Winner?

The debate over AI as a feature versus a product continues, with no definitive answer in sight. Recent releases suggest that AI products have struggled to meet expectations, often falling short in functionality and user satisfaction. As one YouTube commenter noted, “Definitely a feature because there isn’t copyright for the tech. They can all build theirs.”

It’s likely that both AI as a product and AI as a feature will find their own specific use cases, depending on varying needs and applications. While AI features enhance existing products and improve user experience, AI products aim to provide specialized services and may continue to evolve as technology advances.