148 episodes

Host Dan Turchin, PeopleReign CEO and InsightFinder advisor, explores how AI is changing the workplace. He interviews thought leaders across high-tech who share their experiences and insights about artificial intelligence and what it means to be human in the era of AI-driven automation. Learn more about InsightFinder, the system of intelligence for IT Operations: http://www.insightfinder.com. Learn more about PeopleReign, the AI platform for employee service: http://www.peoplereign.io

AI and the Future of Work Dan Turchin

    • Technology
    • 5.0 • 17 Ratings

Host Dan Turchin, PeopleReign CEO and InsightFinder advisor, explores how AI is changing the workplace. He interviews thought leaders across high-tech who share their experiences and insights about artificial intelligence and what it means to be human in the era of AI-driven automation. Learn more about InsightFinder, the system of intelligence for IT Operations: http://www.insightfinder.com. Learn more about PeopleReign, the AI platform for employee service: http://www.peoplereign.io

    Emmanuel Turlay, Founder and CEO of Sematic and machine learning pioneer, discusses what's required to turn every software engineer into an ML engineer

    Emmanuel Turlay, Founder and CEO of Sematic and machine learning pioneer, discusses what's required to turn every software engineer into an ML engineer

    Emmanuel Turlay spent more than a decade in engineering roles at tech-first companies like Instacart and Cruise before realizing machine learning engineers need a better solution. Emmanuel started Sematic earlier this year and was part of the YC summer 2022 batch. He recently raised a $3M seed round from investors including Race Capital and Soma Capital. Thanks to friend of the podcast and former guest Hina Dixit from Samsung NEXT for the intro to Emmanuel.
    I’ve been involved with the AutoML space for five years and, for full disclosure, I’m on the board of Auger which is in a related space. I’ve seen the space evolve and know how much room there is for innovation. This one's a great education about what’s broken and what’s ahead from a true machine learning pioneer.
    Listen and learn...
    How to turn every software engineer into a machine learning engineerHow AutoML platforms are automating tasks performed in traditional ML toolsHow Emmanuel translated learning from Cruise, the self-driving car company, into an open source platform available to all data engineering teamsHow to move from building an ML model locally to deploying it to the cloud and creating a data pipeline... in hoursWhat you should know about self-driving cars... from one of the experts who developed the brains that power themWhy 80% of AI and ML projects failReferences in this episode:
    Unscrupulous users manipulate LLMs to spew hateHina Dixit from Samsung NEXT on AI and the Future of WorkApache BeamEliot Shmukler, Anomalo CEO, on AI and the Future of Work

    • 45 min
    Kevin Mulcahy, co-author of the Future Workplace Experience, discusses how technology is improving the employee experience

    Kevin Mulcahy, co-author of the Future Workplace Experience, discusses how technology is improving the employee experience

    Kevin Mulcahy, co-author of the Future Workplace Experience, has been thinking and writing about the future of work since 2016. Six years ago the future of work was dramatically different. Reading Kevin’s book makes him seem like a clairvoyant who predicted the future. 
    In addition to being a successful author Kevin is a sought after speaker on all topics related to the future of work and workplace trends. In the past, he also lectured on entrepreneurship at Babson College.

    Listen and learn:
    What HR teams need to know about delivering great employee experiencesHow Airbnb created a culture of measuring and improving the employee experienceWhat are progressive employers doing to make the transition back to office work easierThe three "soft leadership" questions every manager should get great at askingHow to measure the quality of employee experiencesHow AI can be used to detect changes in tone in employee engagementWhere to start when using AI to improve the employee experienceHow the metaverse will improve remote workReferences in this episode:
    Twitter boss Elon Musk fires the entire ethics team as one of his first acts of "leadership"Charlene Li on AI and the Future of WorkGary Bolles on AI and the Future of WorkMark van Rijmenam on AI and the Future of WorkBurn In: A Novel of the Real Robotic Revolution by P.W.  Singer and August Cole

    • 38 min
    Michael Osterrieder, CEO and founder of vAIsual, discusses how generative AI is disrupting the stock media industry

    Michael Osterrieder, CEO and founder of vAIsual, discusses how generative AI is disrupting the stock media industry

    Today’s guest is the co-founder and CEO of vAIsual, the company pioneering the use of generative AI to create synthetic stock media. All of those photos you see online and in print publications of people promoting products usually are human models posing in generic ways. Their pictures are sold by companies like Getty Images in marketplaces that are inefficient and limited in scope.

    Michael Osterrieder and his partner Nico are legends in the world of stock media who realized there’s a better way. They created what they call an algorithmic camera and launched vAIsual last year to scratch their own catch. Michael is a serial entrepreneur and photographer based in Budapest and he’s out to test the limits of generative AI.

    Listen and learn:
    How growing up listening to heavy metal inspired Michael's career in visual mediaWhat are the challenges of using generative AI to create synthetic stock images of peopleHow visual media content creation has evolvedThe ethics of generative AIWhat Michael describes as "the biggest art heist in history"How vAIsual extends human photos using machine vision and human labelingCan an AI be the owner of copyrighted material it produces?What is the definition of consciousness?References in this episode...
    AI has a burnout problemEric Olson from Consensus on AI and the Future of WorkJonathan Frankle on AI and the Future of WorkMichael's whitepaper about vAIsual

    • 42 min
    Otto Soderlund, CEO and co-founder of Speechly, discusses what's hard about adding conversational AI to apps

    Otto Soderlund, CEO and co-founder of Speechly, discusses what's hard about adding conversational AI to apps

    Otto Soderlund co-founded Speechly in 2016 with Hannes Heikinheimo in their hometown of Helsinki. He believes voice should be a first-class citizen for all apps and making it easy for developers to add voice support from any platform will unlock new innovation.
    Speechly is a member of the YC Winter 22 batch. Otto and I recently co-presented at the VOICE22 event in Washington DC although I presented remote so this is the first time we’re actually meeting. I heard good things about his talk so I was eager for this discussion. It didn't disappoint.
    Listen and learn...
    Why voice is the new app and what it means to develop "voice-first" appsHow RAIN Agency uses Speechly to help auto technicians use voice assistants to fix cars How to accurately detect and transcribe speech when dealing with common challenges like background noise and accentsWhen speech detection achieved "superhuman" levels of accuracyHow Speechly combines speech recognition with natural language understanding (NLU) on the local deviceHow Otto thinks about exercising responsible AIWhy "voice technology won't exist as a separate field in a decade"References in this episode...
    Responsible AI has a burnout problemAlex Capecelatro from Josh.ai on AI and the Future of WorkKrish Ramineni from Fireflies on AI and the Future of WorkThe Speechly demo site

    • 36 min
    Jonathan Frankle, Harvard Professor and MosaicML Chief Scientist, discusses the past, present, and future of deep learning

    Jonathan Frankle, Harvard Professor and MosaicML Chief Scientist, discusses the past, present, and future of deep learning

    Jonathan Frankle, incoming Harvard Professor and Chief Scientist at MosaicML, is focused on reducing the cost of training neural nets. He received his PhD at MIT and his BSE and MSE from Princeton.
    Jonathan has also been instrumental in shaping technology policy related to AI. He worked on a landmark facial recognition report while working as a Staff Technologist at the Center on Privacy and Technology at Georgetown Law.
    Thanks to great guest Hina Dixit from Samsung NEXT for the introduction to Jonathan!
    Listen and learn...
    Why we can't understand deep neural nets like we can understand biology or physics.Jonathan's "lottery hypothesis" that neural nets are 50-90% bigger than they need to be...but it's hard to find which parts aren't necessary.How researchers are finding ways to reduce the cost and complexity of training neural nets.Why we shouldn't expect another AI winter because "it's now a fundamental substrate of research".Which AI problems are a good fit for deep learning... and which ones aren't.What's the role for regulation in enforcing responsible use of AI.How Jonathan and his CTO Hanlin Tang at MosaicML create a culture that fosters responsible use of AI.Why Jonathan says "...We're building a ladder to the moon if we think today's neural nets will lead to AGI."References in this episode...
    The AI Bill of RightsMosaicMLJonathan's personal site

    • 39 min
    Eric Olson, CEO and co-founder of Consensus, discusses how to use LLMs to help researchers get better answers faster from evidence-based journals

    Eric Olson, CEO and co-founder of Consensus, discusses how to use LLMs to help researchers get better answers faster from evidence-based journals

    Eric Olson, CEO and co-founder of Consensus, is a collegiate athlete turned data scientist turned entrepreneur who needed faster access to reliable data while working at DraftKings. Consensus is a search engine that uses a large language model to find answers in peer-reviewed research articles. Eric's living proof that the best entrepreneurs start by solving a problem they've encountered. Hear how Eric's scratching his own itch.

    Listen and learn...
    Why Google isn't the answer for scientists seeking evidence-based answers onlineWhy a business model that relies on ads can't solve the "unbiased answer" problem for researchersHow Consensus addresses the problem of conflicting information online from credible resourcesHow to use labels to improve search retrieval accuracy... without introducing bias into resultsHow to use extractive large language models (LLMs), to extract relevant portions of documents and match them to NLP questions Why generative AI like GPT-3 can't answer "what's the consensus opinion out there" when multiple potential answers existWho is responsible if Consensus delivers answers that lead to harmful outcomesWhat Eric learned as a division I NCAA athlete (Go Wildcats!) that has helped him as a high-tech entrepreneur
    References in this episode:
    Elon Musk launches the Optimus bi-pedal robot at AI dayDan Grunfeld, Stanford athlete and Lightspeed partner, on AI and the Future of WorkConsensus

    • 36 min

Customer Reviews

5.0 out of 5
17 Ratings

17 Ratings

Aditihd ,

The Best in Tech

Dan does excellent work by inviting key people in tech and asking really hard and important questions. I will recommend this to all the founders, VCs and techies.

Benny-Bear ,

The best guests!

I discovered this podcast late and realized dozens of my heroes are guests. Such a gold mine of info, awesome for founders, VCs, IT folks and anyone with a vested interest in the future of work. 10/10, absolutely recommend this pod.

ASobering ,

A New Favorite in My Feed 🎧

Whether you’re well established in the world of AI, or just getting started in your career, this is a must-listen podcast for you! Dan does an incredible job leading engaging conversations with industry leaders who’ve actually experienced success themselves, and every. single. episode. is jam-packed with insightful takeaways. Highly recommend listening and subscribing!

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