Engineering the Future: How AI/ML is Transforming Business Innovation
I’ve always been passionate about accelerating innovation in engineering, and recently, AI—especially large language models (LLMs)—has dramatically shortened my prototyping phase for analytics scripting. At Brindle Innovations, I’ve leveraged LLMs to jumpstart projects, allowing me to reach a working prototype much faster than if I had written every line of code from scratch.
Accelerating Prototyping with AI
Take, for example, my recent work on a convolutional neural network (CNN) for eye-tracking. I used an LLM to generate an initial script that organized datasets for training the model. While the first version needed several iterations before it was fully operational, the overall process was significantly faster than manually crafting the code from the ground up. This rapid prototyping enables me to test ideas quickly and refine algorithms with greater efficiency.
My Personal Experience with LLMs
Here are a few ways AI has enhanced my workflow:
Quick Prototyping: With a simple prompt, I can generate a functional starting point for complex tasks—like dataset organization for a CNN—saving countless hours during the initial development phase.
Faster Iteration: AI-generated scripts provide a robust foundation that I can iterate on, allowing me to experiment and refine ideas rapidly.
Enhanced Creativity: By reducing the time spent on initial coding, I can focus more on innovative problem-solving and fine-tuning the performance of my models.
Actionable Tips for Fellow Engineers
If you’re aiming to speed up your development process:
Start with AI-Assisted Prototyping: Use LLMs to create a baseline version of your code. Let AI help you get to a working prototype quickly before diving into optimizations.
Refine Through Iteration: Use the AI-generated code as a starting point. Test, tweak, and improve the script iteratively to suit your specific project needs.
Document and Learn: Keep track of how AI-generated solutions evolve into your final code. This documentation can be a valuable learning resource and help you refine your prompts for even better results next time.
Looking Ahead
The use of AI in engineering is a transformative tool—not because it automates the mundane, but because it helps us get to a working solution faster. This acceleration in the prototyping phase is opening up new possibilities for innovation, allowing engineers to focus on fine-tuning and creativity. I’m excited to continue exploring these AI-driven methods and sharing insights on how they can drive significant advancements in our field.
How have you used AI to accelerate your prototyping or development process? I’d love to hear your experiences and discuss ways we can further harness this technology for innovation.