Sequoia helps daring founders build legendary companies from idea to IPO and beyond. We aim to be the first true believers in tomorrow’s most consequential companies. We partner with a few outliers each year and go all-in, providing them with the hands-on help required at every stage of the company building journey. Our expertise comes from nearly 50 years of working with legendary founders like Steve Jobs, Elon Musk, Larry Page, Jan Koum, Brian Chesky, Tony Xu, Lin Qiao, Eric Yuan, Christina Cacioppo, and Patrick Collison. In aggregate, Sequoia-backed companies account for more than 30% of NASDAQ's total value. The vast majority of the money we invest has been on behalf of nonprofits and schools like the Ford Foundation, Mayo Clinic and MIT, which means most of the returns we generate benefit these great causes.
Robotics is currently experiencing a transformative shift analogous to the rise of language models, where software adaptability—not hardware—serves as the primary constraint. Hugging Face’s LeRobot project addresses this by providing an open-source framework that integrates policy models, datasets, and physical hardwar...
In this episode, Ryan Daniels and John Sarihan, founders of Crosby, an AI-first law firm specializing in legal contract automation, discuss their decision to build a law firm instead of legal software, emphasizing the unique feedback loops created by having domain experts and engineers working side-by-side. They explor...
In this interview podcast, Pat Grady speaks with Mati Staniszewski from ElevenLabs about the company's success in the AI audio space despite competition from larger foundation models. They discuss the technical differences between voice AI and text AI, ElevenLabs' focus on audio, and the engineering challenges they've ...
Lin Qiao, CEO of Fireworks, outlines the future of AI inference as a multi-dimensional optimization problem focused on aligning model performance with specific application data distributions. Moving beyond off-the-shelf models, the next generation of inference requires co-optimizing quality, speed, and cost to drive do...
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