AI and the Future of Work

Host Dan Turchin, PeopleReign CEO, explores how AI is changing the workplace. He interviews thought leaders and technologists from industry and academia who share their experiences and insights about artificial intelligence and what it means to be human in the era of AI-driven automation.
  • Episode Number : 176

    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.

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    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…

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  • Episode Number : 175

    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.

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    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…

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  • Episode Number : 174

    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.

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    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…

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  • Episode Number : 173

    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.

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    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…

     

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  • Episode Number : 172

    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.

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    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…

     

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

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  • Episode Number : 171

    We often discuss the technology that is automating the future of work. We perhaps don’t spend enough time talking about the human element – what it’s like being an employee whose career may be at risk or whose employer may not share her values. The future of work is about employers embracing the humanness of every employee and creating safe places.

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    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

     

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  • Episode Number : 170

    What does it mean to be human when your colleague’s a bot? Can AI ever truly understand us? This week, we’re thrilled to welcome Gary F Bengier, eBay’s first CFO and author of the award-winning novel, Unfettered Journey, as we dive into the future of work and the role of AI. Gary’s background in Silicon Valley and his understanding of AI and technology make him the perfect guest to shed light on the ethical implications of AI, the potential impact of large language models on business, and the crucial differences between symbolic software and large language models.

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    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:

     

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  • Episode Number : 169

    The current Hollywood writers strike is the highest profile example of shifting dynamics in the entertainment industry. Studios are spending less to produce more content. Fees paid to writers have plummeted. Generative AI is only accelerating the trend. This has profound implications for the future of storytelling.

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    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…

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  • Episode Number : 168

    Guru Banavar is the founding CTO of Viome where he helped raise $150M from a list of top-tier investors including Khosla Ventures and Bold Capital Group. Viome offers insights into health and disease using host and microbiome gene expression. Guru led the development of a first-of-a-kind saliva-based early detection system for oral and throat cancers which won the FDA’s designation as a breakthrough device.

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    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…

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  • Episode Number : 167

    Dr. Hyde , CEO and co-founder of Atropos Health, and Dr. Halamka, Mayo Clinic Platform President, discuss the future of AI in healthcare

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    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…

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  • Episode Number : 166

    Dr. Shiv Rao is a cardiologist, teacher, former corporate VC, and the CEO of an exciting company that is changing how doctors help patients. Dr. Rao started Abridge in March 2018 to solve one of the biggest problems in healthcare. He has since raised $27M most recently in a $12.5M series A extension last August from leading investors, including Bessemer, Union Square, Wittington Ventures, and legendary AI pioneer Yoshua Bengio.

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    Today we explore what happens when AI automates the error-prone task of doctors taking notes during patient visits. It’s easy to imagine a world where quality of life improves because doctors are present, focused on patient outcomes, and able to develop more genuine human relationships while AI automates everything else.

    Listen and learn…

    • How much of a doctor’s time is spent not focused on patient care
    • How AI can replace “pajama time” for doctors… and reduce burnout
    • Why doctors require a 27-hour work day to deliver the quality of care patients expect
    • How to use generative AI to assist doctors to capture better notes
    • Who is responsible when AI makes mistakes that lead to incorrect diagnoses for patients
    • Why AI won’t replace doctors… but doctors using AI may replace doctors not using it
    • How Abridge reduces the risk of generative AI hallucinations
    • How a design thinking lecture changed Dr. Rao’s life

    References in this episode…

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  • Episode Number : 165

    Guillermo Corea is the Managing Director of the SHRM Workplace Innovation Lab and Venture Capital initiatives. He joined SHRM in 2015. He and his team are focused on finding and cultivating technologies that will impact the future of work. Guillermo’s team organizes the SHRM Better Workplaces Challenge Cup and Workplace Tech Accelerator plus they lead the organization’s impact investing program. Guillermo is a vocal leader in the HRTech community.

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    This was a fun one because we got to record in person at SHRMTech 2023 in San Francisco. Only our fifth live recording in more than 190 episodes!

    Listen and learn…

    • How HR teams should drive workplace innovation
    • Which Shark Tank shark is judging the Better Workplaces Challenge Cup
    • How SHRM Labs connects tech entrepreneurs with HR leaders
    • Why the CHRO is the most strategic exec in the C-suite
    • How the pandemic and an aging employee population are creating opportunities for HRTech
    • The technology Guillermo says will change work most in the next decade
    • How to confront the problem of biased algorithms making HR decisions
    • Why the HR blockchain will replace background check vendors
    • The HRTech company Guillermo is ready to fund!

    References in this episode…

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  • Episode Number : 164

    Daniel Marcous comes to fintech from an unconventional background. Before co-founding April he was the CTO for the Waze product at Google, the social traffic app originally called FreeMap Israel that was acquired by Google in 2013 for $1.3B. Daniel started his career as a data scientist in the Israeli Defense Force and actively gives back to the Israeli Data Science community through involvement with DataHack, DataLearn, and KaggleIL.

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    Listen and learn…

    • What Daniel learned at Google and Waze about scaling AI
    • Why an Israeli data scientist left Google to start a company automating tax filing for Americans
    • Why doing taxes is like finding the best route on a map
    • Why continuous tax planning is the future of personal finance
    • How to manage consumer data responsibly… and still use it to train AI models
    • Why the U.S. tax code is so complicated
    • Why ChatGPT will never do your taxes
    • When AI will replace CPAs
    • Daniel’s favorite cocktail

    References in this episode…

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  • Episode Number : 163

    Artem and his team developed an app that listens in on virtual meetings and does all the note-taking for you including recommending action items and suggesting the most important topics. These are hard AI problems to solve and Sembly’s success is an indication they’re off to a great start.

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    Before Sembly, Artem was an executive and co-founder at companies including Neusana and Visual Trading Systems and he spent time as a manager in big company land at Ernst & Young.

    Listen and learn…

    • Why Artem and his co-founder decided to fix the problem of broken meetings
    • Why the evolution of online meetings… is like the evolution of airplanes
    • Why we’ll soon send AI agents to attend meetings on our behalf
    • When meetings are required… and how to make them more efficient
    • How neural nets are solving traditional voice transcription problems related to accents and background noise
    • How to solve the problem of automatically determining who said what in a conversation
    • How Sembly uses generative AI to summarize meetings
    • What are the risks of having AI decide what tasks to assign to meeting participants
    • How to prevent sensitive information from being passed to large language models as training data

    References in this episode…

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  • Episode Number : 162

    Today’s guest is one of the most recognized investors and thought leaders in the conversational AI community. Bradley Metrock is the CEO of Project Voice, author of the popular Substack newsletter This Week in Voice with more than 30,000 subscribers, and a General Partner at Project Voice Capital Partners. Congrats to Bradley and the team on their recent announcement of their new rolling fund.

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    Bradley’s a proud citizen of the Volunteer State of Tennessee. Fair warning: you may be ready to move to Chattanooga after today’s conversation. Oh, and he’s also an ironman in the world of podcasting having just launched season eight of This Week in Voice, a podcast he launched in 2017. We’re on about episode 180 of this podcast going back to 2019 so I admire Bradley’s stamina.

    Listen and learn…

    • Where there’s opportunity for entrepreneurs to innovate in conversational AI
    • How conversational AI is changing quick-serve restaurants, contact centers, banking, and hospitality
    • How Bradley evaluates new pitches at Project Voice Capital Partners
    • How Bradley defines voice technology in his market map
    • Is voice the new app… or perhaps the “original app”
    • Why generative AI is so disruptive
    • Should we be concerned about voice assistants like Siri and Alexa listening in on our conversations
    • What jobs will AI create over the next decade
    • Bradley sells the great state of Tennessee to entrepreneurs establishing roots outside a coastal state

    References in this episode…

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  • Episode Number : 161

    Ken Wenger is the author of the forthcoming book Is the Algorithm Plotting Against Us?: A Layperson’s Guide to the Concepts, Math, and Pitfalls of AI. I’ve been reading it and it is excellent. Ken is a deep thinker and a great writer. He’s also the senior director of research and innovation at CoreAVI and chief technology officer at Squint AI. 

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    His work focuses on the intersection of artificial intelligence and determinism, enabling neural networks to execute in safety critical systems. Kenneth has co-authored two articles in the scholarly journal Machine Learning with Applications and several white papers for different publications, including Embedded Computing Design. He also holds several patents under CoreAVI’s auspices.

    Listen and learn…

    • How neural nets emulate the brain to make decisions
    • Why we have to be careful when using the term “intelligence” to describe “AI” systems
    • When Ken trusts machines to make decisions… and when he doesn’t
    • Why LLMs like ChatGPT “hallucinate”
    • How generative AI replicates human bias
    • Why Ken feels “if we haven’t addressed ethical issues we’re not ready to deploy AI solutions”
    • What AI explainability is and why it’s important

    References in this episode…

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  • Episode Number : 160

    Bob Rogers, AI pioneer, entrepreneur, and author started Oii in 2019 to automate supply chain design. The company uses advanced modeling and AI to optimize supply chain planning and automate the configuration of complex networks. Bob started his career as a Harvard physicist using neural networks to measure activity near black holes in deep space.

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    During his 35 year career Bob has been a trailblazer in using AI to solve complex problems. He’s also an Expert in Residence for AI at UCSF Smarter Health and was Chief Data Scientist in the Data Center Group at Intel as well as co-founder and Chief Scientist at Apixio, a Healthcare AI company.

    Additionally, he co-authored the books Artificial Neural Networks: Forecasting Time Series and “De-mystifying Big Data and Machine Learning for Healthcare“. Bob received his BA in physics at UC Berkeley and his PhD in physics at Harvard.

    Listen and learn…

    • How neural nets work… from a pioneer
    • What it was like to co-author a book with ChatGPT
    • What surprised Bob most when he tested the boundaries of ChatGPT
    • Why ChatGPT spews credible nonsense
    • The ethics of using generative AI to sell content derived from copyrighted materials
    • Why ChatGPT became an instant global phenomenon
    • How OpenAI trained ChatGPT “to be nice”
    • Is there another “AI winter” ahead?

    References in this episode:

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  • Episode Number : 159

    Cisco got its start in 1984 connecting computers at Stanford University to form the first local area network. Other than maybe Microsoft or Apple, it’s easy to argue Cisco has had more influence on the growth of the internet, and by extension, the modern world, than any other company. 15 years after Cisco started today’s guest was hired to begin what would become a legendary career.

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    Nearly 25 years later JP Vasseur has changed the world again and again. In the process, he has been recognized as the #1 inventor at Cisco with 600 patents to his name. He has authored or co-authored 35 standards, published three books on internet technologies, and has been recognized as a Cisco Fellow, a prestigious title awarded to the top few most-distinguished technical leaders at the company. Today we learn from a living legend about the past, present, and future of technology.

    Listen and learn…

    • How AI at Cisco has evolved in the past 12 years
    • Disruptive vs. incremental innovation
    • How predictive networks learn
    • The design principle JP used when designing the first predictive network
    • The challenges of predicting outages using unsupervised vs. supervised machine learning
    • JP’s process for innovating like a startup within Cisco
    • Innovation in networking we can expect in the next decade
    • JP’s best memory from the early days of Cisco

    References in this episode:

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  • Episode Number : 158

    Navindra Yadav is the co-founder and CEO of Theom, the cloud data security leader. He and the team recently raised a $16M series A from an impressive group of investors including Microsoft’s M12 venture fund and Ridge Ventures. Prior to Theom, Navindra was the founder and CEO at Tetration and prior to that he was a distinguished engineer at Cisco. Navindra’s work has received more than 182 patents.

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    For full disclosure, Dan is an investor in Theom. Thanks to Patty Hatter, great former guest, for introducing us to Navindra.

    Listen and learn…

    • What CISOs least understand about the security of enterprise data
    • Why CASBs (Cloud Access Security Brokers) are inherently vulnerable
    • The hardest technical problem Theom has solved
    • How to assign a “criticality score” to data
    • How to use NLP (natural language processing) to detect PII (personally identifiable information)
    • How to protect from unauthorized data access through social engineering
    • Why data stores like Snowflake, Databricks, and Confluent don’t already monitor data inappropriately leaving their platforms?
    • When consumers will be able to trust that data they provide SaaS vendors is secure.
    • The security startup Navindra and Dan are ready to fund!

     

    References in this episode…

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  • Episode Number : 157

    We often discuss the future of work for enterprise employees. What technology will they use, how will people and machines interact, and how teams will be organized when geography and language are no longer barriers. Few have spent more time in and around enterprise service management than today’s guest and few are better qualified to share insights about what’s ahead.

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    Andi Mann has been a technology leader in technology companies around the world since the 90s. He founded Sageable, the digital transformation advisory services practice, in 2015 and has also recently served in roles that include CTO for DevOps at Splunk and VP Products and Strategy at CA which is now part of Broadcom. Andi and I both did time at BMC Software in the early 2000s. Andi is the author of multiple books including The Innovative CIO, he’s a sought after speaker, and tech provocateur who is never shy about what’s wrong with IT and where the world of digital is headed.

    Thanks to friend of the podcast Steve Kaplan for the intro to Andi.

    Listen and learn…

    • Why Andi summarizes his career this way: “I make computers do more work to allow people to do more creative things”
    • The best use of enterprise AI Andi has seen
    • How Andi helped an industrial transportation company save a billion dollars
    • Why “less complex systems can’t understand more complex systems”
    • Why the best use of AI is targeting “known knowns” by augmenting vs. replacing human intelligence
    • How to overcome the lack of trust in AI
    • Why AI won’t eliminate any jobs… and why it will create many new ones
    • Skills to invest in today that will never be replaced by automation

     

    References in this episode…

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