Comparing the 'innovativeness' of ChatGPT 3.5 vs GPT4
Using a simple test, I prompted ChatGPT3.5 and GPT4 with the task of innovating a toy car using TRIZ principles. Here's what I found.
A recent, long but very informative, article I read, proposed that employing GPT-4 for [smaller] tasks is akin to using a space shuttle for a cross-town commute. So it left me wondering about the innovation capability of 3.5 v 4. Could GPT4 be better at innovating than 3.5. With a very simple, quick, and rudimentary test I checked it out.
Here’s what I did. Invented a problem statement. My problem statement is that a popular toy manufacturer needed some ideas for a new line of small toy cars to fill the ever evolving toy car selection in toy stores.
So I give this prompt:
“Using TRIZ principle 32 on color, give me the specifications for an innovation on toy cars. Be as innovative as possible.”
ChatGPT3.5 gave the following results:
TRIZ (Theory of Inventive Problem Solving) principle 32, also known as "Color Changes," suggests using changes in color or optical properties to improve the functionality or aesthetics of a system. Applying this principle to the innovation of toy cars, here's an idea that combines technology, engagement, and creativity:
(Chat GPT3.5) Innovative Toy Car: Augmented Reality Color Morph Racer
Description: Design a line of toy cars that leverage augmented reality (AR) and color-changing technology to create an interactive and engaging play experience for children. These cars would dynamically change colors based on various factors, enhancing both the visual appeal and imaginative play potential of the toys.
Specifications:
Color-Changing Body: The toy cars should have a specialized body material that allows for color changes through the application of an electrical current or temperature variations (Mark: Interesting!). This could be achieved using thermochromic or electrochromic materials, enabling the cars to switch colors with ease.
Integrated Augmented Reality (AR) System: Each toy car should come with an integrated AR system that includes a camera, sensors, and a small display. This system would interact with a companion AR app, available on smartphones or tablets. (Mark: Hmmmm. Jumping on a bandwagon maybe)
Companion AR App: Develop an AR app that pairs with the toy cars. The app would be used to control the color changes of the cars and provide additional interactive features, such as virtual tracks, obstacles, and challenges.
Color Customization: The app should allow users (both children and parents) to customize the toy car's appearance. Users can choose from a wide range of colors, patterns, and designs. This customization feature enhances creativity and personalization.
Interactive Gameplay: The AR app would provide a virtual environment in which the color-changing toy cars can race, navigate obstacles, and complete challenges. The cars' color changes could be linked to in-game power-ups, boosts, or specific interactions within the app's virtual world.
Educational Content: Integrate educational content within the AR app. As children interact with the virtual environment, they could learn about color mixing, physics concepts, and even basic coding principles.
Social Interaction: Implement a feature that allows children to share their customized cars and gameplay experiences with friends and family. This could foster social interaction and friendly competition.
Expansion Packs: Offer expansion packs that include new color patterns, virtual tracks, and interactive challenges. This encourages continued engagement and excitement over time.
Safety Considerations: Ensure that the toy cars and AR app are designed with child safety in mind. The materials used should be non-toxic, and the app should have parental controls to manage screen time and content.
Collectible Aspect: Introduce limited-edition color patterns or collaborations with popular franchises to create a collectible aspect, encouraging repeat purchases.
The color changing aspect would be expected from any individual or team of humans looking to innovate a new toy car. The AR aspect was unexpected but quite an interesting innovation. But I’m left wondering how this would actually be technically possible to create and manufacture.
Here’s what happens if I give the same prompt to GPT4 which is supposedly better at reasoning and chain of thought:
ChatGPT4 gave the following results:
Color-Changing Toy Cars
1. Overview: The Color-Changing Toy Cars are designed to change color based on different factors such as temperature, speed, light exposure, or user interaction. This adds an interactive and engaging element to the toy, making it more appealing to children and collectors alike.
2. Features:
A. Temperature-Sensitive Color Change:
The car's exterior paint is made with thermochromic pigments that change color based on temperature.
When the car is rolled over a warm surface, it changes color, allowing children to create tracks and patterns.
B. Speed-Sensitive Color Change:
Integrated sensors detect the speed of the car, and the color changes according to different speed levels.
This can be used to create races where the color indicates the leading car or to teach children about speed and motion.
C. Light-Responsive Color Change:
The car's color changes in response to different light conditions, such as UV light or darkness.
This can create a magical effect where the car appears different in sunlight versus indoor lighting.
D. User-Interactive Color Change:
The car comes with a remote control or a mobile app that allows users to customize the color of the car.
Children can choose their favorite colors or even design patterns, enhancing creativity and personalization.
E. Educational Aspect:
The color-changing feature can be used to teach children about various scientific principles like temperature, speed, and light.
3. Materials and Technology:
Thermochromic pigments for temperature-sensitive color change.
Speed sensors and microcontrollers for speed-sensitive color change.
Photochromic materials for light-responsive color change.
Bluetooth or Wi-Fi connectivity for user-interactive color change.
4. Safety Considerations:
All materials used must be non-toxic and safe for children.
The design must include safeguards to prevent small parts from being a choking hazard.
5. Target Audience:
Children aged 3 and up.
Toy car collectors interested in unique and innovative designs.
6. Potential Extensions:
Integration with augmented reality (AR) apps for enhanced play experiences.
Collaboration with popular media franchises for themed color-changing cars.
By applying TRIZ Principle 32 on color, the Color-Changing Toy Cars offer an innovative and engaging play experience that can also be educational. The various color-changing mechanisms add layers of interactivity and excitement, making the toy cars more appealing and versatile.
Here we see that the color changing aspect has come up again, but what I appreciate more about the GPT4 response is that it has bothered to generate some idea about the materials and technology that would be needed to actually create it. After all, innovations are only meaningful if it’s possible to make them (as opposed to time machine patents). Speed sensitive and light responsive color changing were definitely more innovative additions than the output from 3.5.
So is GPT4 capable of more innovative generation than GPT3.5? I think it’s inconclusive with such a small and basic test. But GPT4 definitely seems to have an edge in ‘thinking’ things through more. Especially in this case where ‘being as innovative as possible’ was part of the prompt.
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