Apple Poised to Enter the Generative AI Space — Here’s Why It Could Succeed
Apple has always aimed to distinguish itself from its competitors, and when it comes to artificial intelligence (AI), the tech giant prefers to create its own hype rather than latch onto existing trends. However, this doesn’t mean that Apple doesn’t utilize AI technology. In fact, it heavily relies on machine learning, which falls under the broader category of AI. Apple’s products, such as the iPhone and the recently announced spatial computing Vision Pro, are embedded with machine-learning algorithms that power features like Face ID, battery usage optimization, photo organization, keyboard suggestions, and maps.
While other tech giants like Google, Microsoft, and Meta have been actively engaged in the race to develop and deploy consumer-facing generative AI, Apple has taken a more reserved approach. Instead of rushing into the development of a competing Large Language Model (LLM), Apple has been quietly working behind closed doors to build its own generative AI technology.
According to Bloomberg, Apple has been developing a framework called Ajax to support LLMs, and internally, it has already deployed a service similar to OpenAI’s ChatGPT, dubbed Apple GPT. The company is aiming to release a consumer-facing generative AI product in the near future.
Although Apple may be late to the generative AI party, its cautious approach could potentially benefit the company in the long run. Apple boasts an enormous and fiercely loyal consumer base, as highlighted by Warren Buffett. With customers willingly paying large sums for Apple devices, the opportunity for seamless integration across Apple’s ecosystem could make a product like ChatGPT unnecessary for a significant portion of its user base. Additionally, if existing generative AI options continue to face issues with accuracy and reliability, Apple’s entry into the market could easily disrupt the competition.
One recent study revealed that ChatGPT’s behavior and accuracy have fluctuated significantly between March and June. The chatbot’s accuracy plummeted from around 97.6% to a mere 2% during this period. Such instability raises concerns about relying on current LLMs for important tasks. Google’s Bard, another generative AI model, faced heavy criticism from its own engineers, who labeled it a pathological liar and worse than useless.
Apple’s decision to take a more cautious and meticulous approach in building its generative AI model indicates its commitment to delivering a refined and reliable product. While the quality of Apple’s upcoming model is yet to be determined, it is likely to avoid the glaring drawbacks observed in existing options.
As Apple prepares to enter the generative AI market, it will be crucial for the company to prioritize ease of integration and user experience. The seamless interaction between Apple devices will be a key factor in encouraging everyday adoption. By leveraging its loyal consumer base and focusing on enhancing the reliability and accuracy of its generative AI, Apple has the potential to make a significant impact in the space.
In conclusion, while Apple may be fashionably late to the generative AI party, its meticulous approach and commitment to user experience could position the company for success. With its vast consumer base, seamless integration, and the potential to overcome the shortcomings of existing generative AI models, Apple has the opportunity to make a lasting impression in the AI landscape.
