Mayfield CXO Insight Calls

Video - 59 min | Quantum computing itself can be loosely thought of as a new class of supercomputers for certain specialized types of use cases and problems, notably: machine learning, optimization, chemical simulations, and more. Manufacturers are continuing to announce exponential increases in the number of available qubits – the basic unit of processing capacity for these machines. And since the capacity of a quantum computer increases exponentially with each qubit instead of linearly, what does that mean for the future of quantum in the enterprise? We believe that quantum will be a gamechanger for the computing industry – and that IT leaders have the opportunity to take a perspective now, on how they plan to leverage it, while we're still in the early innings.

Video - 60 min | For some time now, machines have been able to master the art of analyzing data - but unfortunately, they have struggled to create new content. OpenAI and the many models being built on top of it, mark the beginning of a new category widely known as "Generative AI" - meaning that an AI is generating something novel, rather than simply analyzing or acting on existing data. And this evolution won't just apply to traditional creative work - every industry will feel the impact. Adam will be discussing how businesses will be able to leverage OpenAI in a very practical sense - and how some of the first big use cases will look.

Video - 60 min | The revolution around generative AI first started at Google back in 2017, when the team invented Transformer, which kickstarted the LLM revolution. In recent times, generative AI has come much farther: new opportunities emerge every day in operational efficiencies, cost savings, and value creation.

Video - 60 min | Even before ChatGPT, one-third of CIOs said their organization had already deployed artificial intelligence (AI) technologies, and 15% more believed they would deploy AI within the next year, according to the 2023 Gartner CIO and Technology Executive Survey. But deciding how best to proceed means factoring AI into business value, risk, talent, and investment priorities. As a next step, CIOs and other organizational leaders must create an AI strategy roadmap that synthesizes the enterprise's vision for the future - outlining potential benefits, while mitigating risk, capturing KPIs, and implementing best practices for value creation.

Video - 60 min | Mayfield is deeply engaged in the space, and Vijay is our new lead investor for our AI-dedicated fund, AI Start. He shares the primary segments that comprise the opportunity, the best practices he's seeing, breakout technologies, and how CXOs can leverage these forward-looking insights. He's supported by Isaac, who brings extensive CIO leadership and transformational advisory work.

Video - 60 min | Today, executives are in the process of considering large, looming issues around AI, such as accuracy, privacy, and bias, as well as the potential impact on “knowledge workers” and even economy-wide job losses and societal risks. While this view is important, it’s difficult to translate to what it means for businesses today. A bottoms-up view is necessary to take in what's directly ahead and identify the immediate opportunities and threats.

Video - 60 min | Over the past 6 months, we’ve hosted several CXO Insight Calls around the topic of AI. However, there’s a real need to solve a number of core issues before enterprise IT leaders can adopt and move to production. According to Forbes, 55% of business leaders say their teams are resistant towards adopting AI today. It’s not hard to see why.

Video - 60 min | The promise of generative AI is immense, but when it comes to building and scaling successful LLM applications, it can be difficult to move from curiosity to a solid proof of concept with repeatable results. The future is going to require new plumbing to make this all a bit less painful - on our call today, we spent some time discussing how to utilize frameworks like LangChain and dev tools like MindsDB.