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.
This episode explores the common pitfalls of integrating AI agent assistants into mature software products and offers a solution to avoid these issues. The speaker highlights how many established companies fail to create a seamless user experience with their AI agents, often resulting in feature-incomplete and frustra...
This episode explores the current and future landscape of AI, focusing on advancements in models, hardware, and applications. Jeff Dean shares insights on the evolution of neural networks, emphasizing the importance of scaling models and data for improved results, highlighting the potential of multimodal AI. Against th...
This episode explores OpenAI's journey, from its early days as a research lab to its current position as a leading AI company, and its future direction. Sam Altman reflects on the initial challenges, including the uncertainty around LLMs and the shift towards building a business model to sustain the investment required...
This episode explores OpenAI's advancements in AI reasoning, particularly focusing on scaling compute and reinforcement learning (RL). Dan Roberts, formerly of Sequoia and now at OpenAI, discusses the evolution of AI models from GPT-4 to O3, highlighting the increasing importance of test-time compute, where models impr...
This episode explores the development and capabilities of OpenAI's Deep Research, an agentic feature within ChatGPT. Isa Fulford, the lead of OpenAI's Deep Research team, details how this feature conducts multi-step online research to solve complex tasks, producing cited reports in minutes that would take humans hours...
This episode explores the evolving landscape of AI-driven customer service and the strategic shifts required for both startups and established companies to thrive. Bret Taylor shares insights from his experiences at Google, Facebook, and Salesforce, emphasizing the importance of adapting one's role to meet the most cri...
The AI industrial revolution demands a fundamental shift in infrastructure, moving beyond GPU clusters to prioritize the physical foundations of power, steel, and specialized data center construction. As the data center evolves into the new unit of compute, achieving massive scale requires an energy-first strategy, exe...
This episode explores the challenges and potential solutions in the field of physical AI, particularly robotics, contrasting it with the advancements in large language models (LLMs). It begins by introducing the concept of a "Physical Turing Test," which assesses a robot's ability to perform complex real-world tasks in...
This episode explores the current state and future trajectory of AI, focusing on investment strategies and technological advancements. Against the backdrop of AI's rapid evolution, the discussion highlights a framework for evaluating AI opportunities, emphasizing the importance of assessing the market size and potentia...
Isomorphic Labs is transforming drug discovery by building a general-purpose AI engine capable of navigating the vast chemical space of 10^60 potential molecules. Chief AI Officer Max Jaderberg explains that moving beyond traditional supervised learning, the company utilizes reinforcement learning and diffusion-based a...
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