It was an easy choice for me. I'm not a pure academic person. I've done entrepreneurship before, worked at large tech firms, and hold CFA and PMP certifications. I love challenges. When I joined Z.ai, I saw fascinating challenges that I had a chance to conquer: product development, partnership building, commercialization, and establishing a global brand. The opportunity to build something from the ground up on a global scale was too compelling to pass up. The original hypothesis behind GLM was that the dichotomy between autoencoding (BERT-style) and autoregressive (GPT-style) models was a false choice. We believed a unified framework could capture the best of both worlds: strong bidirectional understanding and powerful generation capabilities. Back then, the landscape was fragmented. You had to choose between models good at understanding versus models good at generation. GLM's autoregressive blank infilling objective was designed to bridge that gap. This DNA still influences our...
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