Technology

Why Gemini Must Learn from ChatGPT to Simplify AI Tools

OpenAI has announced plans to simplify its ChatGPT product roadmap, which has become complicated with various unfamiliar product names that confuse consumers. By abandoning obscure model identifiers such as o1 and o3, OpenAI is moving towards a more straightforward branding style with a structure of ChatGPT followed by a version number.

Table of Contents

The evolution of AIs like Google’s Gemini has similarly led to an overwhelming amount of choice for users. In my recent experience with the Gemini app on my phone, I was greeted by a multitude of options that left me bewildered:

Google Gemini on an iPhone

Talk about too many options…
(Image credit: Apple/Google)

At a glance, the layout of options within the Gemini application appears chaotic, raising questions about whether there has been any strategic planning involved in its design. Presently, users engaging with the Gemini Advanced subscription are faced with seven different language models, each bearing similar names that add to the confusion. An example is the convoluted title of ‘Google Gemini 2.0 Flash Thinking Experimental with apps,’ which may very well be among the longest in AI history. The ambiguity surrounding what this implies only compounds the issue.

Too much choice

While researchers or coders might benefit from access to a variety of large language models (LLMs), the average user seeking assistance with simple tasks—like helping kids with math homework or planning road trips—will find such variety overwhelming.

OpenAI’s responsive approach involves adopting a simpler method, with iterations designated as ChatGPT-4, ChatGPT-5, and so on. This approach allows the AI to assess the complexity of a user’s inquiry and decide automatically whether to employ a deep reasoning model or a standard LLM. As some might say, it’s akin to seeking a delicious hotdog without worrying about how it was made.

Google could certainly learn from this model. For instance, the previously mentioned ‘2.0 Flash Thinking Experimental with apps’ model can analyze YouTube videos, providing valuable insights or summarizing key points. Instead of requiring users to select a specific LLM, why not streamline it to simply ‘Gemini 2.0’? If a user poses a question concerning a video, the system could seamlessly switch to the relevant model, enhancing the user experience significantly.

Look at Apple

The ultimate goal is to facilitate AI that operates intuitively, with clear naming conventions. When observing Apple’s product branding strategy, we see a model of simplicity. Apple’s product lines typically feature several variations that are easily distinguishable:

Examples include:

  • MacBook Variants: MacBook Air and MacBook Pro
  • iPhone Series: iPhone 16 and iPhone 16 Pro

This straightforward approach stands in stark contrast to the current state of AI accessibility. As we navigate through the early phases of the AI revolution, an emphasis on streamlined consumer experiences must be prioritized. OpenAI’s decision to refine its branding is a significant step towards achieving this, suggesting that a smoother user experience is on the horizon. It is crucial for tech giants like Google to recognize and adapt to these evolving expectations.

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