Inspiration
We went to a career fair and one of the companies there was hiring positions for an engineer that had experience in semiconductors. We wanted to expand on our experience in semiconductors by designing this AI assistant.
What it does
Our AI platform gives up to date recommendations on semiconductor products. By combining advanced machine learning with live market data, our platform delivers personalized product suggestions, instant availability and deep insights into performance and lifecycle trends.
How we built it
We built it using HuggingFace, Groq, Streamlit, Langchain, and other technologies to train our AI assistant to give detailed and accurate semiconductor product recommendations.
Challenges we ran into
One of the challenges was making the database for the AI update in real time and download the output into the csv file. However, through lots of trial and error, we were able to accomplish that task and continue working on our project.
Accomplishments that we're proud of
Something we're proud of is the real time database as mentioned above. We learnt to use AI tools and gained knowledge about the whole process for making a hackathon project. Again, it took a long time to work on and we think it's something that will make our AI platform stand out from the rest.
What we learned
We learned that there are many ways to use different AI tools to accomplish the same task, and that there are more AI tools than we possibly could've imagined
What's next for AI Semiconductor Product Recommender
Currently, the AI platform only recommends products from using dataset from NXP, Intel, and TSMC for analysis, we will continue and plan to expand it to make it able to recommend products from other companies.
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