AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics

Chris Fernandez, founding CEO of EnsoData, uses AI to solve sleep problems by making sleep studies more efficient, cost-effective, and accurate. He discusses how AI and machine learning can be applied to sleep apnea, the potential of 'smart rooms' for healthy sleep, and the importance of controlling AI bias. He also shares tips on improving sleep quality from an expert's perspective. Listen and learn about the intersection of technology and healthcare, the risks in AI software development, and the challenges of scaling a startup.

We’ve had interesting recent discussions about AI and the law with great guests like Robert Plotkin. And we’ve had many interesting conversations about AI with CIO legends like Mark Settle from Okta and Carter Busse from Workato to name a few. In over 200 episodes we haven’t yet discussed how to deliver IT service to the legal industry.Jim McKenna has been delivering technology to attorneys and coaching others who do the same for more than two decades. In his current role at perennial Silicon Valley top law firm Fenwick & West, Jim supports an organization of more than 1,000 employees as CIO. He oversees teams that manage IT and security and is first and foremost a thought leader for the business. Prior to Fenwick, Jim held similar roles at Morrison and Forester. He is also a member of the Board of Directors of the International Legal Technology Association.Thanks to Xavier, unsung hero and Fenwick IT specialist, for helping with A/V issues.Listen and learn...What's unique about delivering IT and security service to lawyersHow the legal industry shifted to work from home during the pandemicWhat's ahead for LegalTechWhere there are opportunities for AI to predict future employee needsHow Jim keeps up with security and compliance requirements... while innovatingJim's leadership advice: "Prepare in advance so when the tough occurs you're not afraid!"References in this episode...Robert Plotkin on AI and the Future of WorkMark Settle on AI and the Future of WorkCarter Busse on AI and the Future of WorkHow generative AI is being used to analyze patterns in DNA sequences

Today’s guest has had a front row seat for every technology platform shift for the past 20+ years. More important, he has played an important role in enabling several of them.Kit Colbert joined tech stalwart VMware in September 2003 and currently serves as senior vice president and chief technology officer. He is responsible for ensuring VMware’s long term technology leadership through research and innovation programs. Kit manages the VMware Engineering Services team, advanced R&D initiatives, the Design/UX team and the company’s ESG commitments.Kit was previously VMware’s Cloud CTO, General Manager of VMware’s Cloud-Native Apps business, CTO for VMware’s End-User Computing Business, and the lead architect for the vRealize Operations Suite. Kit is a recognized thought-leader on application modernization and multi-cloud trends and a frequent speaker. He holds a bachelor’s of science in computer science from Brown University.Listen and learn...How a Silicon Valley stalwart like VMware innovates from the insideHow VMware's founder-led culture continues to influence the company todayHow VMware reinvented itself beyond desktop virtualizationKit's recipe for innovationWhy crypto and AI hype are similarKit's perspective on how to regulate AIVMware's generative AI strategyReferences in this episode...Andi Mann from Sageable and Splunk on AI and the Future of WorkDiane Greene and the history of VMwareKit's team's blog

Ron Bodkin is a self-described “serial entrepreneur focused on beneficial uses of AI”. Ron founded ChainML in April 2022 to make it easier to integrate AI models into applications. The AI we know today is immature in so many ways and many of them relate to how crude the tooling is for traditional developers building AI-first features. The ChainML protocol is a cost-efficient, decentralized network built for compute-intensive applications running on blockchain technology. Prior to founding ChainML Ron had a distinguished entrepreneurial career having founded Think Big Analytics before it was eventually acquired by Teradata after which he spent three years in applied AI at Google. Ron is also an active investor and advisor and has degrees in Computer Science from McGill and MIT.Listen and learn...What led Ron to focus on how AI can have a positive impact on the worldWhy Hinton's right when he says "we've invented a superior form of learning"Where the current toolstack for building LLM apps is incredibly immatureHow to control the cost and performance of LLM appsWhy human brains are inefficientWhy the "effective cost of computing" is being reduced by 50% every yearHow we may get to AGI within 20 yearsWhy proprietary datasets and commercial issues will slow down AI innovationThe right way to regulate AIReferences in this episode...Meredith Broussard, professor and author, on AI and the Future of WorkAttorney relies on court cases made up by ChatGPTThe Microsoft Sparks of AGI paper

Trent Fitz is the Chief Product Officer at Zenoss after having spent two decades in product and marketing leadership roles at companies like Trustwave and SailPoint.Trent owns product strategy and marketing at one of the pioneers in the space. Zenoss was founded in 2005 and has continued to reinvent itself. With the advent of generative AI, it’s more relevant than ever.We’ve explored the topics of service assurance and monitoring in the past with great guests like Colin Fletcher who coined the term AIOps while at Gartner and Gareth Rushgrove from Snyk who publishes the popular DevOps Weekly newsletter.The field of monitoring is evolving rapidly as new architecture patterns emerge and the data exhaust they generate continues to increase. Listen and learn...Trent's history lesson in system monitoringThe role of AI in monitoring and operationsTrent's perspective on the evolution of monitoring tool sprawlWhat is AIOps vs. observability, monitoring, or event managementHow service-centric monitoring is essential for dynamic apps based on microservicesThe difference between generation one and two AIOpsWhere are manual rules insufficient and real AI is needed to monitor appsHow LLMs are being used to improve observabilityWhy Big Cloud won't own monitoring of cloud-native appsWill there be a time when AI will replace DevOps engineers?References in this episode...Colin Fletcher from Gartner on AI and the Future of WorkGareth Rushgrove from Snyk on AI and the Future of WorkCharity Majors on AI and the Future of Work

Today's guest is one of the pioneers in generative AI having spent nine years at Google Research building teams that developed breakthrough technologies that led to innovations like the transformer architecture behind ChatGPT.Jad Tarifi co-founded Integral AI in 2021 after a distinguished career in AI roles as a researcher and leader. He received his PhD in Computer Science and AI from the University of Florida and did his undergrad at the University of Waterloo.Thanks to great former guest and friend of the podcast Hina Dixit from Samsung NEXT for the intro to Jad.Listen and learn: Can machines learn common sense? Do humans have common sense? Why Integral AI is providing a “base model for the world” Can machines ever learn as quickly as humans? How to improve the efficiency of LLMs with better algorithms Why the current transformer architecture is poorly designed for next word prediction How to use AI and robotics to create “magic wands” and “crystal balls” How to use AI to do “science at scale” What are the ethical implications of bots that can change the human life span How AGI is related to objective morality Jad’s four tenets of a new definition of “freedom” References in this episode… Integral.ai Blake Lemoine and the “sentience” debate Podcastle, generative AI for podcasts (a technology nobody needs)

Today’s guest is one of the original AI-first entrepreneurs. SambaNova paved the way for generations of other companies including today’s generative AI cohort. Rodrigo Liang, CEO, and his team have raised more than a billion dollars from a legendary group of investors including Temasek, BlackRock, GV, and Walden International.The original vision for SambaNova’s chip architecture and software products came from work his co-founders did at Stanford’s famous AI Lab. Today, SambaNova has embraced generative AI and is again leading the industry. Before founding SambaNova, Rodrigo held senior leadership roles at Oracle and Sun after having received his masters and bachelors degrees in Electrical Engineering from Stanford.Listen and learn… Why AI will be bigger than the internet How SambaNova migrated from designing AI chip architectures to software How to build your own LLM like ChatGPT Where there are opportunities for companies beyond NVIDIA in the AI chip space What will lead to the “trough of disillusionment” for AI What are adjacent opportunities for AI outside chat that are at the early stages of maturity How every knowledge worker will soon benefit from an AI personal assistant How to address the problem of popular LLMs being trained mostly on English contentWhy we’re in the “Linux moment for AI” What contributes to the cost and complexity of training new LLMs What is fine-tuning and how does it work References in this episode… Sam Altman calls for global cooperation to regulate AIThe SambaNova technical blog The SambaNova partnership with Together.xyz to train BLOOMChat Christopher Nguyen, Aitomatic CEO, on AI and the Future of Work 

We’ve interviewed some legendary CIOs including Mark Settle from Okta (a repeat guest), Reza Nazeman from SAP Concur, and, more recently, Carter Busse from Workato.We’re joined by another unicorn CIO today, Karl Mosgofian. Karl has helped grow Gainsight to more than $200M ARR and 1,200 employees. He has been leading the IT organization for nearly six years after having spent time at Harmonic, Apple, and Cadence Design.Thanks to friend of the podcast Carter Busse for the intro to Karl.Listen and learn...How Karl's role has changed since he joined Gainsight as a startup six years agoWhy it's hard for CIOs to "just keep the lights on"How Karl navigates the duel role of enabling the business to innovate with technology while making sure teams stay focused on solving business problemsHow Karl formulated the Gainsight employee ChatGPT policyWhy ChatGPT won't replace the help deskKarl's advice to vendors embedding AI in their productsHow Karl partners with his CISO and legal team to establish policies for LLM usageHow Gainsight is using AI internally to improve productivityAll about the quirky culture at GainsightReferences in this episode...Mark Settle on AI and the Future of WorkCarter Busse on AI and the Future of WorkReza Nazeman on AI and the Future of WorkLegendary Gainsight videos on YouTube

No field is being upended as much as the legal profession. We’re all confused about how content generated by AI will be protected under the law and many lawyers are also asking how relevant they’ll be in a world where large language models can pass the bar and do legal research.Robert Plotkin is a luminary in the software patent space having been in the field for 25 years and having been involved in important IP cases related to everything from AI to quantum computing to autonomous vehicles and speech recognition.Robert also published the book Genie in the Machine back in 2009 which amazingly foreshadowed the legal implications of AI on IP. Robert has lectured at the Boston University School of Law and received his undergrad in Computer Science and Engineering from MIT.Listen and learn...How we should regulate LLMs... from an expertWhat entrepreneurs most often don't understand about IP lawWho has the rights to the inputs to LLMs?Can work derived from LLMs be patented?Is AI-generated work subject to copyright laws?What surprised Bill Gates when he saw GPT-4Is there an AI winter up ahead?References in this episode...Robert's personal siteHarvey raises $5M to be the AI co-pilot for lawyersAndy Clark's Natural-Born CyborgsBob Rogers, AI pioneer, on AI and the Future of WorkThe Blueshift IP whitepaper about how AI is automating the inventive process

Today’s guest is the author of a popular Medium blog where he has recently been dissecting generative AI for technologists. I read his introduction to the transformer architecture and immediately realized our audience needs to meet him. A bit like great recent guest Ken Wenger, Pradeep makes complicated technology accessible. By day, Pradeep Menon is a CTO at Microsoft's digital natives division in APAC. He has had one of the best ground floor views of generative AI since Microsoft first invested in OpenAI in 2019 and then again in March of this year.Pradeep was previously in similar roles at Alibaba and IBM. He speaks frequently on topics related to emerging tech, data, and AI to global audiences and is a published author.Listen and learn...What surprises Pradeep most about the capabilities of LLMs What most people don't understand about how LLMs like GPT are trained The difference between prompting and fine-tuning Why ChatGPT performs so well as a coding co-pilot How RLHF works How Bing uses grounding to mitigate the impact of LLM hallucinations How Pradeep uses ChatGPT to improve his own productivity How we should regulate AI What new careers AI is creating References in this episode...Ken Wenger on AI and the Future of Work Pradeep's book Data Lakehouse in ActionD-ID speaking avatars