Doing it the Hard Way: Making the AI engine and language 🔥 of the future — with Chris Lattner of Modular | Latent Space: The AI Engineer Podcast | Podwise
In this episode of the Latent Space Podcast, the host interviews Chris Lanner, an experienced professional in the field of computer science. The discussion revolves around the challenges and developments in the AI research and development space. Chris shares insights into his work experience at Apple, Tesla, and Google, and his current role as the president of Approxin Engineering at RISC-V or PSI5. The conversation focuses on the importance of addressing the fragmentation and complexity in AI development through the creation of Mojo, a superset of Python that aims to build a unified AI engine. They discuss the challenges faced in AI research, including hardware compatibility, scalability, and optimization. The episode also highlights the significance of concurrent compatibility in the Python ecosystem and the importance of collaboration in AI development. Overall, the episode provides valuable insights into the challenges, innovations, and future directions in the AI research and development space.
