Imagine telling a computer what you want a chip to do, and it designs the Verilog code for you. That's the promise of VeriSeek, a new open-source AI model making waves in hardware design. Traditionally, designing chips has been a complex, time-consuming process, demanding high expertise. But recent advances in large language models (LLMs), like the ones powering ChatGPT, have sparked interest in automating parts of this process using AI. While impressive, commercial LLMs are black boxes – their inner workings hidden from researchers. This limits customization and raises data privacy issues for companies. VeriSeek addresses these limitations by offering an open-source solution, meaning researchers can understand and modify it, and companies retain control over their sensitive data. But building a powerful open-source model for chip design isn’t easy. The biggest challenge is the lack of good training data. Chip designs are proprietary, jealously guarded by the companies that create them. Publicly available data is often messy and unusable. VeriSeek’s creators overcame this hurdle with a clever two-pronged approach. First, they ‘pre-trained’ their AI model on a mix of existing Verilog code and, surprisingly, C-language programs. This helped the model grasp the logic of hardware design. Next, they refined it with ‘reinforcement learning.’ This technique is like training a dog with treats – the AI gets ‘rewarded’ when it produces correct Verilog code, incentivizing it to learn the right patterns. The results? VeriSeek, despite being smaller than other leading models, beat them all in generating functional Verilog designs. It's not perfect yet, but it demonstrates a huge leap forward. This success opens exciting possibilities. Imagine AI assistants helping engineers design more complex, efficient chips, freeing up human time for creative problem-solving. There's still work to do. The research team highlights the importance of developing better 'supervisory signals,' which are ways to guide the AI's learning toward genuinely useful outputs. The parallel nature of Verilog poses a challenge, requiring new thinking in how we train AI for these tasks. But VeriSeek’s achievement marks a major step towards the future of automated chip design, demonstrating the power of open-source collaboration and innovative training methods.