Since then, May Habib and the team have raised $21M from an exceptional group of investors including Insight Partners and Gradient Ventures. Today, Writer helps company authors comply with style and brand guidelines and also ensure grammatical accuracy. It’s used by an amazing list or organizations including Spotify, Intuit, and Uber.

Prior to Writer, May co-founded Qordoba and was a Global Shaper for the World Economic Forum after graduating from Harvard with a BA in Economics.

Listen and learn…

• How May got her start in NLP
• What enterprise leaders don’t understand about the current state of generative AI
• How to speak to your data using LLMs
• Why Writer uses graph databases instead of vector databases for generative AI
• How Writer mitigates the impact of bias, copyright infringement, and hallucinations when using LLMs
• How AI is being used to replace tasks people hate… without eliminating jobs
• How AI helps users with neurodiversity issues like ADHD
• How May navigated a tough company pivot

References in this episode…

• Mona Akmal, Falkon CEO, on AI and the Future of Work
• Alex Capecelatro, Josh.ai CEO, on AI and the Future of Work
• Making the web more accessible with AI for those with disabilities

Pete started the company back in 2009 and has since produced over 150 events across 89 countries that have connected more than 125,000 people. Pete and the team have created communities for tech companies like Samsung and Amazon. Today, we get a glimpse into the mind of a great entrepreneur who is focused on making AI education accessible to everyone.

Listen and learn…

• How Modev went from a few people in a pizza shop… to a conversational AI event with more than  1,000 attendees
• How Modev trained developers to build Alexa skills… in 2009
• How new AI regulation is impacting the generative AI developer community
• How Pete would regulate generative AI
• About Sam Altman’s request to Congress for OpenAI to be regulated
• Should we expect AI vendors to regulate themselves?
• What we can learn from GDPR in Europe about forthcoming AI regulation
• How AI will transform the entertainment industry
• Which jobs will be replaced by AI… and which ones are future-proof
• What big news Pete will be announcing at the Voice & AI conference

References in this episode…

• The Voice & AI conference
• How Goldman Sachs says AI will increase global GDP
• Bradley Metrock, CEO of Project Voice, on AI and the Future of Work
• Daniel Davila, movie producer and Hollywood consultant, on AI and the Future of Work

Today’s guest is one of those. Nick Adams founded Differential Ventures in 2017 to invest in B2B, data-first seed-stage companies. Since then, Nick and the team have invested in an impressive group of companies including Private AI, Ocrolus, and Agnostiq.

Before Differential, Nick helped grow companies like OPower and RAGE Frameworks in sales, marketing, and product leadership roles. Today we get to learn about how to innovate and grow a startup when the product is a venture fund.

Listen and learn…

• How being an investor and entrepreneur are similar
• The most outrageous pitch Nick has heard… and how it involved porn
• How being a baseball player trained Nick to be a venture capitalist
• Nick’s advice for what to do after closing a big sales deal
• Where there are opportunities for generative AI entrepreneurs to get funded
• How AI is being used to design circuit boards
• Nick’s most recent investment… and what made him decide to write the check
• What Nick is telling Congress we need to do to regulate AI

References in this episode…

• Why generative AI is desperately in need of regulation
• Metafold, new Differential investment
• Dan Grunfeld from Lightspeed on AI and the Future of Work

Vijay is a visionary leader who has raised more than $400M and built a team of nearly 1,000 employees. Workato is a leader in the fast-growing enterprise automation space and the company’s customer list reads like the Wall Street Journal including organizations like Adobe, Atlassian, Coca-Cola, and Walmart to name a few.

Vijay’s latest achievement is his book The New Automation Mindset – launching today on this podcast – in which he and his co-authors put the current generative AI euphoria into historical context and provide timely insights and case studies.

Thanks to great former guest Carter Busse, Workato CIO, for the intro to Vijay.

Listen and learn…

• How Vijay got his start as a “digital plumber” at TIBCO and Oracle
• What Vijay learned about enterprise software delivering a consumer app at Qik
• How modern tools democratize access to automating work
• Vijay’s advice to leaders about what to automate first
• Why “replacing people with AI is the wrong approach”
• How Workato is incorporating generative AI into its product
• How AI is required to get the full benefit of automation
• What jobs will replace those eliminated by automation

References in this episode…

• The New Automation Mindset by Vijay Tella
• Carter Busse on AI and the Future of Work
• Guru Banavar from Viome on AI and the Future of Work
• The Khanmigo AI tutor

Christopher provides well-researched, thought-provoking commentary on all topics related to generative AI. Like recent guests Pradeep Menon and Ken Wenger Christopher doesn’t settle for soundbite-level commentary and he often shares unpopular opinions backed up with data.

Christopher is the Co-Founder and Chief Data Scientist at TrustInsights.ai. He’s a six-time IBM Champion in IBM Data and AI, a Brand24 Top 100 Digital Marketer, an Onalytica Top 100 AI in Marketing influencer, and co-host of the award-winning Marketing Over Coffee marketing podcast. He is also the author of two dozen marketing books. His list of accolades and accomplishments goes on for days.

Listen and learn…

• The number one question Christopher asks data-driven marketers
• What has surprised Christopher most about the capabilities of LLMs
• Why the letter to pause AI was “dumb”
• The right way to remove bias and hate speech from LLMs
• Open source vs. closed source AI… and how it’s related to making pizza
• Are we ready for AI vendors to censor content?
• Christopher’s predictions for how all enterprise software will incorporate generative AI
• Why Christopher continues to hone his bow and arrow skills=

References in this episode…

• Pradeep Menon on AI and the Future of Work
• Ken Wenger on AI and the Future of Work
• Tiernan Ray on AI and the Future of Work
• Christopher’s (entertaining and informative!) newsletter
• .. to glorify LLM hallucinations

The bots aren’t sentient!

Chris Fernandez co-founded EnsoData in June 2015 to use AI to make sleep studies more efficient, cost effective, and accurate.

Since then, he and the team have raised more than $30M from an exceptional group of investors including Zetta Venture Partners, M25 Ventures, and Inspire Medical Systems.

Chris received his bachelors and masters degrees from the University of Wisconsin-Madison in Biomedical and Medical Engineering. He also wrote one of the most thoughtful perspectives on the entrepreneurial journey when he handed over the reigns to new CEO Justin Mortara last November. At 8,200 words, it may also be one of the longest.

Listen and learn…

• What led Chris to care about solving sleep problems
• How EnsoData overcame being “a solution in search of a problem”
• How AI and machine learning can be applied to sleep apnea
• How being incubated by Y Combinator helped launch EnsoData
• How to use brainwaves to train AI models to diagnose sleep issues
• When we’ll get “smart rooms” that adjust the environment to optimize for healthy sleep
• How Chris and the team control for the impact of AI bias
• How to improve the quality of your sleep… from an expert
• What led Chris to replace himself as CEO

References in this episode…

• Gordon Wilson, Rain Neuromorphics CEO, on AI and the Future of Work
• Why We Sleep by Matt Walker
• Stanford Professor Dr. William Dement and the origins of sleep science

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 lawyers
• How the legal industry shifted to work from home during the pandemic
• What’s ahead for LegalTech
• Where there are opportunities for AI to predict future employee needs
• How Jim keeps up with security and compliance requirements… while innovating
• Jim’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 Work
• Mark Settle on AI and the Future of Work
• Carter Busse on AI and the Future of Work
• How generative AI is being used to analyze patterns in DNA sequences

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 inside
• How VMware’s founder-led culture continues to influence the company today
• How VMware reinvented itself beyond desktop virtualization
• Kit’s recipe for innovation
• Why crypto and AI hype are similar
• Kit’s perspective on how to regulate AI
• VMware’s generative AI strategy

References in this episode…

• Andi Mann from Sageable and Splunk on AI and the Future of Work
• Diane Greene and the history of VMware
• Kit’s team’s blog

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 world
• Why Hinton’s right when he says “we’ve invented a superior form of learning”
• Where the current toolstack for building LLM apps is incredibly immature
• How to control the cost and performance of LLM apps
• Why human brains are inefficient
• Why the “effective cost of computing” is being reduced by 50% every year
• How we may get to AGI within 20 years
• Why proprietary datasets and commercial issues will slow down AI innovation
• The right way to regulate AI

References in this episode…

• Meredith Broussard, professor and author, on AI and the Future of Work
• Attorney relies on court cases made up by ChatGPT
• The Microsoft Sparks of AGI paper

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 monitoring
• The role of AI in monitoring and operations
• Trent’s perspective on the evolution of monitoring tool sprawl
• What is AIOps vs. observability, monitoring, or event management
• How service-centric monitoring is essential for dynamic apps based on microservices
• The difference between generation one and two AIOps
• Where are manual rules insufficient and real AI is needed to monitor apps
• How LLMs are being used to improve observability
• Why Big Cloud won’t own monitoring of cloud-native apps
• Will there be a time when AI will replace DevOps engineers?

References in this episode…

• Colin Fletcher from Gartner on AI and the Future of Work
• Gareth Rushgrove from Snyk on AI and the Future of Work
• Charity Majors on AI and the Future of Work

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)

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 content
• Why 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 AI
• The SambaNova technical blog 
• The SambaNova partnership with Together.xyz to train BLOOMChat 
• Christopher Nguyen, Aitomatic CEO, on AI and the Future of Work

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 ago
• Why 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 problems
• How Karl formulated the Gainsight employee ChatGPT policy
• Why ChatGPT won’t replace the help desk
• Karl’s advice to vendors embedding AI in their products
• How Karl partners with his CISO and legal team to establish policies for LLM usage
• How Gainsight is using AI internally to improve productivity
• All about the quirky culture at Gainsight

References in this episode…

• Mark Settle on AI and the Future of Work
• Carter Busse on AI and the Future of Work
• Reza Nazeman on AI and the Future of Work
• Legendary Gainsight videos on YouTube

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 expert
• What entrepreneurs most often don’t understand about IP law
• Who 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-4
• Is there an AI winter up ahead?

References in this episode…

• Harvey raises $5M to be the AI co-pilot for lawyers
• Andy Clark’s Natural-Born Cyborgs
• Bob Rogers, AI pioneer, on AI and the Future of Work
• The Blueshift IP whitepaper about how AI is automating the inventive process

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 Action
• D-ID speaking avatars

https://podcasts.apple.com/us/podcast/p

Mark McCrindle is a best-selling author, futurist, demographer, and popular TEDx speaker who is regarded as one of Australia’s foremost social researchers. He works with senior leaders to help them devise strategies for making their products and services future-proof. He’s also the host of The Future Report, a podcast featuring the themes of his social research.

Listen and learn…

• How work culture directly impacts employee productivity
• How to measure the quality of employee experiences
• How the mining industry attracts and retains workers… and how AI may replace traditional roles
• Should humans feel threatened by AI?
• Mark’s advice to young leaders
• Why Mark says “we’re made for work”… but that doesn’t necessarily require an exchange of time for money
• How human relationships with machines will always be different than human relationships with each other
• Why the culture in Sydney is uniquely favorable for entrepreneurs

References in this episode

• Mark’s social research
• mccrindle publications
• AI’s impact on humanity with Gary F. Bengier
• Bryan Talebi, Ahura AI CEO, on AI and the Future of Work

As we unpack the World Economic Forum’s prediction that AI will generate 97 million new jobs while eliminating 85 million in the next three years, Gary and I contemplate the implications of machines and humans working together. We discuss the possibility that robots could eventually build robot factories, detaching the output of the economic system from labor hours, and explore the question of sentience in the age of advanced technology. Join us for an important conversation and peer into the mind of one of the great philosophers and technologists of our time.

Oh, and learn what Gary says is a better definition for the acronym “LLM” :).

References in this episode:

• Tiernan Ray on AI and the Future of Work
• Wow.. ChatGPT is very thirsty!
• The Santa Fe Institute
• Gary’s book Unfettered Journey

Today’s guest is an expert in the entertainment industry having founded Divisadero Pictures in 2011 to advise entertainment companies from Disney to Comcast to Microsoft on strategy and finance topics. Daniel Davila received his MFA from USC and his MBA from Stanford.

For historical perspective, today is only the second episode in more than 190 where we’ve discussed AI and the future of the work in the entertainment industry. For long-time listeners the last time was episode 87 back in April 21 with Michael Solomon and Rishon Blumberg, authors of Game Changer: How to be 10x in the Talent Economy, who  managed Bruce Springsteen and John Mayer in a previous life.

Thank you to friend of the podcast Matthew Perez for the introduction to Daniel.

Listen and learn…

• The history of media consumption patterns
• The economics of the entertainment industry
• How AI is changing the entertainment industry
• How Daniel used generative AI tools to write a 70-page movie script
• Daniel’s pitch to Francis Ford Coppola about the role of AI in movie-making
• The impact of streaming on media production and consumption
• The bias inherent in text to image tools like Midjourney

References in this episode…

• Michael and Rishon, Bruce Springsteen’s former managers, on AI and the Future of Work
• Divisadero Pictures
• The Hollywood writers strike

Prior to Viome, Guru was a global VP & Chief Science Officer at IBM and the founding VP of the Watson AI Research team.

Guru has received many awards including a Leadership in Technology Management Award and a National Innovation Award from the President of India. He has published extensively and holds more than 35 US patents. His work has been featured in media outlets including the New York Times, the Economist, the Wall Street Journal, BBC, and NPR.

Listen and learn…

• Why our healthspan is more important than our lifespan
• How DNA to RNA transcription determines your health state
• How to sequence your mRNA to understand how to optimize your diet and predict disease risk
• What AI techniques can be used to develop personalized treatments
• How to use data that varies across patients to make automated decisions for all patients
• How Guru thinks about false positive prescriptions as a scientist when health and safety are at stake
• Where the FDA is regulating how AI is used to make healthcare recommendations
• Why it’s impossible to know the best diet for you without first understanding the composition of your microbiome
• How to use biomarkers to turn your biological fingerprint into a data problem
• Guru’s perspective on the ethical and philosophical implications of extending the healthspan
• How digital twins will help perfect the ability to engineer biology

References in this episode…

• What it means to practice responsible AI
• The KEGG ontology of biological pathways 
• The Viome blog 
• Shiv Rao, CEO of Abridge, on AI and the Future of Work

Dr. Hyde raised a $14M series in August 2022 from an exceptional group of investors including Breyer Capital and Emerson Capital.

Dr. Hyde is joined by an early user of Atropos, Dr. John Halamka, President of the Mayo Clinic Platform. Dr. Halamka has been developing and implementing healthcare information strategy and policy for more than 25 years. He specializes in artificial intelligence, the adoption of electronic health records and the secure sharing of healthcare data for care coordination, population health, and quality improvement. He was elected to the National Academy of Medicine in 2020.

For AI and the Future of Work trivia buffs this is one of only three episodes we’ve recorded with multiple guests. The last one with Tooso founders Ciro Greco and Jacopo Tagliabue was one of our most memorable.

Listen and learn…

• Why ChatGPT shouldn’t be used for medical diagnoses
• How Atropos uses healthcare data from the Mayo Clinic Platform combined with AI to assist caregivers
• How to use AI to automate the research that can otherwise takes weeks or months
• How the lack of access to data-driven recommendations leads to dangerous patient outcomes
• Who is responsible when AI makes a bad decision that adversely impacts a patient
• How to use NLP to remove PII to make it usable by AI (and certify data hygiene)
• The challenges of managing patient data at scale in a way that complies with HIPAA regulations

References in this episode…

• ChatGPT’s phenomenal adoption rate… by the numbers
• Ciro and Jacopo from Tooso (acquired by Coveo) on AI and the Future of Work
• Paddy Padmanabhan on AI and the Future of Work
• Dipanwita Das, Sorcero CEO, on AI and the Future of Work
• The Mayo Clinic Platform
• Atropos Health