Today's episode first appeared on Peter Scott's (excellent!) AI and You podcast.Peter Scott and David Wood are two of the most recognized AI futurists. Both are respected authors, speakers, and visionaries. Peter is a popular TEDx speaker and long-time NASA engineer. David was recently named one of the "top 100 most influential people in technology".Today's discussion is a must-listen in which we discuss the future of technology, the future of work, and the future of humanity. In this one, Peter hosted and the three of us had a round table discussion about everything from generative AI to sentience. Let us know what you think after listening. Our DMs are open on Twitter and LinkedIn.Listen and learn...Where AI won and lost in 2022Our predictions for AI in 2023What will the impact of ChatGPT be on the future of technologyWhat tasks are best-suited for generative AIHow we'll regulate generative AI when it spews nonsenseWhat is artificial general intelligence (AGI) and when we'll achieve itWhat is sentience and are today's bots sentient?How and where the US AI Bill of Rights falls short vs. AI regulation in the EUWhat we should be doing to systematize the practice of responsible AIReferences in the episode:Peter Scott on AI and the Future of WorkEric Olson from Consensus on AI and the Future of WorkMichael Osterrieder from vAIsual on AI and the Future of WorkJim Lawton from Zebra on AI and the Future of WorkGary Bolles on AI and the Future of WorkMeta's Galactica bot failure

We’ve met some brilliant product minds on this show over the years. If you’re a long-time listener you hopefully enjoyed discussions with legends like Phil McKinney, former CTO of HP, and Philippe Cases, founder and CEO of Topio Networks, among others. Today’s guest belongs on that list. Rich and I first met when he was starting UserVoice around 2010 and I was at ServiceNow. I love his approach to innovation. He pioneered the idea that listening to customers can be as easy as adding a feedback tab to every web page back when all that existed were clunky survey tools. Today, thousands of sites use the widget he invented. He’s now out to make meetings more productive by helping attendees focus on conversations while an app transcribes them and offers simple buttons to annotate what’s happening. It’s obvious once you’ve used Fathom that this is the future of meetings.Rich White is not only a serial innovator but also a repeat entrepreneur who has raised from a group of exceptional investors over the years and was part of the YC Winter 2021 batch. Enjoy!Listen and learn...As a product expert and innovator, how to know when you've found "an itch worth scratching"What is "product-market fit" and how to know when you've achieved itWhat is a viral coefficient and how do you calculate itHow the "jobs to be done" framework led Rich to develop the key feature of FathomThe hardest problem Fathom has solved... has nothing to do with voice transcriptionHow Fathom trains developers to practice responsible AIReferences in this episode:Project Linchpin from the US Army is centralizing more than 685 AI projectsPhil McKinney on AI and the Future of WorkPhilippe Cases on AI and the Future of WorkFathom

Special episode this week! We recorded two live discussions from Turing's BOUNDARYLESS "Future of Work" event in San Francisco. In the first, Rani Mavram, Complete.so CEO, discusses using data to transform compensation policies from being a liability to an asset for high-growth companies. In the second, Ankit Jain, Aviator CEO, discusses using automation to improve developer productivity for remote-first engineering teams.Listen and learn...From Rani Mavram:Why compensation policies have an outsize impact on employee engagementWhat's required to make compensation plans transparentThe difference between compensation plans and "total reward" packagesWhere innovation is happening in the field of employee compensationFrom Ankit Jain:How to make remote-first engineering teams successfulUsing automation to improve developer productivityHow startups can replicate the developer experience at Google and FacebookThe future of generative AI and GitHub Copilot in assisting human developersReferences in today's show:Turing's BOUNDARYLESS eventComplete.so for compensation transparencyAviator to improve developer productivity

Merve Hickok is one of the most recognized thought leaders in the emerging field of AI ethics. Merve is the founder of AIethicist.org and Lighthouse Career Consulting. Her work is at the intersection of AI and data ethics along with social justice and DEI policy and regulation.Merve was recently listed among the top 100 most brilliant women in AI ethics and in the past she lectured at the University of Michigan’s School of Information on Data Science ethics. Merve’s at the forefront of this emerging field that will define how we live and work for the next several decades. This is an important conversation. Enjoy!Listen and learn… What led to Merve founding AIEthicist.orgHow the AI ethics conversation has evolved over the past year What the White House got right (and wrong) in the blueprint for an AI Bill of Rights What responsible AI means to Merve Why regulation doesn’t necessarily constrain innovation How AI policy and regulation are different around the world References in this episode... Why Meta’s newest LLM survived only three days onlineJonathan Frankle on AI and the Future of WorkRene Morkos from ALICE Technologies on AI and the Future of WorkPanos Siozos from LearnWorlds on AI and the Future of WorkPaddy Padmanabhan from Damo Consulting on AI and the Future of Work

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

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

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

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

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

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 entrepreneurReferences 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