The Allure of Apple’s LLM Paper: A Closer Look at Stalling Tactics

In the tech world, particularly among product managers, there’s a tendency to seize any opportunity to delay the adoption of new technologies. This reflex was evident in response to Apple’s recent research paper on Large Language Models (LLMs), which suggested that these advanced tools are not the all-encompassing magic solutions many have hoped for. Instantly, some seem to treat this paper like a doctor’s note that grants them a temporary reprieve from engaging with AI technologies.

As quoted by Ethan Mollick, a prominent voice in the field:

“I think people are looking for a reason to not have to deal with what AI can do today … It is false comfort.”

This sentiment strikes a chord, doesn’t it? Many professionals might find themselves thinking:

• “Look, it’s still imperfect!”
• “I’ll come back to AI when it’s more polished—maybe in 2026.”
• “Now, back to that feature we’ve had on the drawing board since 2021.”

Meanwhile, the reality is that the AI technologies available today are transforming critical areas of business such as product development, operations, content creation, and customer support. Yet, while some hesitate to fully dive into AI, these advancements continue to evolve and reshape industries.

Let’s take a moment for some self-reflection: Are we genuinely critiquing these disruptive technologies, or are we simply searching for excuses to delay their integration? The challenge lies not just in acknowledging the imperfections of LLMs, but in recognizing the immense potential they hold and the opportunities they present for innovation and efficiency. It’s time to move beyond stalling tactics and embrace the change that AI can bring.