Podcasts about Peter Voss

Dr. Martin Goodson is the founder and CEO of Evolution AI, a company he launched in 2012 to apply deep learning to optical character recognition (OCR). The company has received one of the largest AI R&D grants ever awarded by the UK government, along with investment from First Minute Capital. A former scientific researcher at Oxford University, Martin has led AI research across several organizations and was elected Chair of the Data Science and AI Section of the Royal Statistical Society in 2019.In this conversation, we discuss:Martin Goodson's journey from researching biological data to founding Evolution AI and pioneering deep learning for document understanding.Why traditional OCR missed the mark, and how combining visual and linguistic context unlocked a new frontier in document intelligence.The evolution from data extraction to true financial analysis, and why domain knowledge is essential for reading statements like income reports.The risks of LLM hallucinations, especially with numerical data, and why accuracy still requires combining techniques across model types.What Martin believes intelligence really is, and why language alone may be the wrong benchmark for AGI.Why recreating human intelligence shouldn't be the goal of AI research, and how we can build systems that support, not mimic, human thinking.Resources:Subscribe to the AI & The Future of Work NewsletterConnect with Martin on LinkedInCheck out the YouTube channel of the London Machine Learning MeetupAI fun fact articleOn How to Ovecome Imposter SyndromePast episodes mentioned:On Why doing Taxes is like finding the Best Route on a Map with Daniel MarcousOn Making AI Smarter Without Harming Humans with Peter Voss

Something doesn't smell right about generative AI. Earlier this week, we had a featuring a former Google researcher who described large language models (LLMs) as a “con”. Then, of course, there's OpenAI CEO Sam Altman who critics both inside and outside OpenAI, see as a little more than a persuasive conman. Scam or not, the biggest technical problem with LLMs, according to Peter Vos, who invented the term Artificial General Intelligence (AGI), is that it lacks memory and thus are inherently incapable of incremental learning. Voss, the current CEO of Aigo.ai, argues that LLMs therefore represent a technological “dead end” for AI. The industry, Voss argues, has gone “fundamentally wrong” with generative AI. It's a classic economic mania, he says. And, as with all bubbles in the past - like Dutch tulips, internet DotComs or Japanese real-estate - it will eventually burst with devastating consequences. Peter Voss is a pioneer in AI who coined the term 'AGI' (Artificial General Intelligence) in 2001. As an engineer, scientist, inventor, and serial entrepreneur, he developed a comprehensive ERP package, growing his company from zero to a 400-person IPO in seven years. For the past 20 years, he has studied intelligence and AI, leading to the creation of the Aigo engine, a proto-AGI natural language intelligence that is revolutionizing call centers and advancing towards human-level intelligence.Named as one of the "100 most connected men" by GQ magazine, Andrew Keen is amongst the world's best known broadcasters and commentators. In addition to presenting the daily KEEN ON show, he is the host of the long-running How To Fix Democracy interview series. He is also the author of four prescient books about digital technology: CULT OF THE AMATEUR, DIGITAL VERTIGO, THE INTERNET IS NOT THE ANSWER and HOW TO FIX THE FUTURE. Andrew lives in San Francisco, is married to Cassandra Knight, Google's VP of Litigation & Discovery, and has two grown children.Keen On America is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit keenon.substack.com/subscribe

AI is jumping from one hype cycle to another. First, it was simple AI, then came Generative AI, and currently, we are reeling from Agentic AI. The new term is already lurking—Artificial General Intelligence (AGI).  Actually, AGI is pretty old, dating back to the early 2000s. What is it, and why is it gathering attention now? I talk to the person who came up with the very term--Peter Voss, CEO & Chief Scientist at Aigo.ai. We delve into how AGI mimics human learning functions, how it differs from Gen AI, why it is cost- and power-efficient by orders of magnitude, whether today's Gen AI can evolve into AGI, and more. We also discuss whether AGI's human-like learning can create cyborgs and Skynet.

Send us a text"Ready to dive deep into the future of intelligent systems? Meet Peter Voss, Founder and CEO of Aigo.ai, who coined the term 'Artificial General Intelligence' and is pioneering hyper-personalized chatbots WITH a brain. Join us as we explore his revolutionary ideas and why Aigo.ai is leading the charge in AI innovation."#AIInnovation #PeterVoss #FutureOfAI #HyperPersonalization #BeyondChatGPT #TechPodcast #ArtificialIntelligence #MachineLearning #PersonalizedTech01:56 Meet Peter Voss08:23 Passion for Intelligent Systems12:54 Why only Aigo16:31 ChatGPT? A Different View22:03 A Use Case by Example30:53 What is Included, What is Not34:08 Who are your Clients36:10 The Engagement38:57 The Business Case41:59 AI that Reasons44:26 The Definition of AGI46:51 For FunLinkedIn: linkedin.com/in/vosspeterTwitter: @peterevossWebsite: aigo.ai/Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text"Ready to dive deep into the future of intelligent systems? Meet Peter Voss, Founder and CEO of Aigo.ai, who coined the term 'Artificial General Intelligence' and is pioneering hyper-personalized chatbots WITH a brain. Join us as we explore his revolutionary ideas and why Aigo.ai is leading the charge in AI innovation."#AIInnovation #PeterVoss #FutureOfAI #HyperPersonalization #BeyondChatGPT #TechPodcast #ArtificialIntelligence #MachineLearning #PersonalizedTech01:56 Meet Peter Voss08:23 Passion for Intelligent Systems12:54 Why only Aigo16:31 ChatGPT? A Different View22:03 A Use Case by Example30:53 What is Included, What is Not34:08 Who are your Clients36:10 The Engagement38:57 The Business Case41:59 AI that Reasons44:26 The Definition of AGI46:51 For FunLinkedIn: linkedin.com/in/vosspeterTwitter: @peterevossWebsite: aigo.ai/Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this fascinating episode of Think Tank Podcast, Robert welcomes Peter Voss, a pioneering expert in Artificial General Intelligence (AGI). The conversation delves into Peter's journey from founding a successful software company in South Africa to his current mission of creating true thinking machines. Peter provides insights into the evolution of AI, explaining the difference between narrow AI and AGI, and shares the story behind coining the term "Artificial General Intelligence" in 2002. The discussion touches on the challenges and possibilities of AGI, including how these systems might handle emotions, cognition, and human-like reasoning. Peter discusses his work on building machines that learn and think like humans and offers a vision for the future of AI, where AGI can dramatically boost human capabilities in areas like research, healthcare, and ethics. Robert and Peter also explore ethical concerns, societal impacts, and the future of AI technology, including the potential for AI to assist in life extension and revolutionize various fields. The episode leaves listeners with thought-provoking insights into how AGI might shape the future of human existence. Robert Edward Grant Books: https://robertedwardgrant.com/store/#books Courses: https://robertedwardgrant.com/courses/ Store: https://robertedwardgrant.com/store/#apparel Connect with Peter Voss  Linkedin: https://www.linkedin.com/in/vosspeter/ Company Website: https://aigo.ai/ Connect with Robert Grant: YouTube - https://www.youtube.com/@Robert_Edward_Grant  Instagram - https://www.instagram.com/robertedwardgrant/?hl=en Facebook - https://www.facebook.com/robertedwardgrant/ Website - https://robertedwardgrant.com/ Subscribe to the Robert Edward Grant Podcast: Spotify - https://open.spotify.com/show/2XrShu3YdP2cIvF6rR0nWB Apple Podcast - https://podcasts.apple.com/us/podcast/robert-edward-grant-think-tank/id1657287338  

Are we overlooking the most powerful model of intelligence we have  in our race to create smarter machines,  the human mind?  Peter Voss, CEO and Chief Scientist of Aigo.ai, coined the term "Artificial General Intelligence" (AGI) and brings decades of experience in AI research and development. We explore Peter's vision and challenge the current consensus path we are on.Episode HighlightsDefining AGI and Its DistinctionsMeasuring Intelligence Beyond the Turing TestCurrent AI Limitations and the Need for Real-Time Learning Building Cognitive AI to Mimic the Human Mind The Future of AI Development in AustinWhat's Next Austin?"I hope Austin becomes the center of cognitive AI and AGI"Peter Voss: LinkedIn, X/Twitter, Aigo.AIConcepts Is All You Need: A Direct Path to AGITowards Incremental LearningWhy We Don't Have AGI Yet?INSA – Integrated Neuro-Symbolic ArchitectureCreating The Future With Artificial General IntelligenceLLMs are not the Path to AGI -------------------Austin Next Links: Website, X/Twitter, YouTube, LinkedIn

SummaryArtificial intelligence has dominated the headlines for several months due to the successes of large language models. This has prompted numerous debates about the possibility of, and timeline for, artificial general intelligence (AGI). Peter Voss has dedicated decades of his life to the pursuit of truly intelligent software through the approach of cognitive AI. In this episode he explains his approach to building AI in a more human-like fashion and the emphasis on learning rather than statistical prediction.AnnouncementsHello and welcome to the AI Engineering Podcast, your guide to the fast-moving world of building scalable and maintainable AI systemsYour host is Tobias Macey and today I'm interviewing Peter Voss about what is involved in making your AI applications more "human"InterviewIntroductionHow did you get involved in machine learning?Can you start by unpacking the idea of "human-like" AI?How does that contrast with the conception of "AGI"?The applications and limitations of GPT/LLM models have been dominating the popular conversation around AI. How do you see that impacting the overrall ecosystem of ML/AI applications and investment?The fundamental/foundational challenge of every AI use case is sourcing appropriate data. What are the strategies that you have found useful to acquire, evaluate, and prepare data at an appropriate scale to build high quality models? What are the opportunities and limitations of causal modeling techniques for generalized AI models?As AI systems gain more sophistication there is a challenge with establishing and maintaining trust. What are the risks involved in deploying more human-level AI systems and monitoring their reliability?What are the practical/architectural methods necessary to build more cognitive AI systems?How would you characterize the ecosystem of tools/frameworks available for creating, evolving, and maintaining these applications?What are the most interesting, innovative, or unexpected ways that you have seen cognitive AI applied?What are the most interesting, unexpected, or challenging lessons that you have learned while working on desiging/developing cognitive AI systems?When is cognitive AI the wrong choice?What do you have planned for the future of cognitive AI applications at Aigo?Contact InfoLinkedInWebsiteParting QuestionFrom your perspective, what is the biggest barrier to adoption of machine learning today?Closing AnnouncementsThank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email hosts@aiengineeringpodcast.com with your story.To help other people find the show please leave a review on iTunes and tell your friends and co-workers.LinksAigo.aiArtificial General IntelligenceCognitive AIKnowledge GraphCausal ModelingBayesian StatisticsThinking Fast & Slow by Daniel Kahneman (affiliate link)Agent-Based ModelingReinforcement LearningDARPA 3 Waves of AI presentationWhy Don't We Have AGI Yet? whitepaperConcepts Is All You Need WhitepaperHellen KellerStephen HawkingThe intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0

Founder/CEO/Chief Scientist at AGI Innovations & Aigo.ai, Peter Voss, discusses the advancement of chatbots by giving them a "brain" to enhance customer experience. Over the past 15 years, Aigo.ai has been perfecting a highly intelligent and hyper-personalized Chatbot for large enterprise customers, focusing on cognitive AI technology. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Founder/CEO/Chief Scientist at AGI Innovations & Aigo.ai, Peter Voss, discusses the advancement of chatbots by giving them a "brain" to enhance customer experience. Over the past 15 years, Aigo.ai has been perfecting a highly intelligent and hyper-personalized Chatbot for large enterprise customers, focusing on cognitive AI technology. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Aigo.ai, one of the few companies globally with extensive experience in Cognitive AI, has been refining a highly intelligent and hyper-personalized Chatbot for large enterprise customers over the past 15 years. Peter Voss, the Founder/CEO/Chief Scientist at AGI Innovations & Aigo.ai, delves into the future of customer service through hyper-personalization in this episode. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Aigo.ai, one of the few companies globally with extensive experience in Cognitive AI, has been refining a highly intelligent and hyper-personalized Chatbot for large enterprise customers over the past 15 years. Peter Voss, the Founder/CEO/Chief Scientist at AGI Innovations & Aigo.ai, delves into the future of customer service through hyper-personalization in this episode. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Is Artificial General Intelligence “AGI" possible? If so, what would its effect be on humanity? In this episode, Adam Torres and Peter Voss, Founder, CEO & Chief Scientist at Aigo.ai, explore the Aigo.ai story and the future of AGI.  Follow Adam on Instagram at https://www.instagram.com/askadamtorres/ for up to date information on book releases and tour schedule. Apply to be a guest on our podcast: https://missionmatters.lpages.co/podcastguest/ Visit our website: https://missionmatters.com/ More FREE content from Mission Matters here: https://linktr.ee/missionmattersmedia

In this episode of AI, Government, and the Future, host Max Romanik is joined by Peter Voss, CEO of iGo.ai and a pioneer in artificial general intelligence (AGI). Peter discusses the critical differences between narrow AI and AGI, exploring how AGI aims to overcome the limitations of current AI technologies. He shares his vision for cognitive AI architectures, the potential impact of AGI on various industries, and his perspectives on AI regulation and development. Peter also addresses concerns about AI safety and emphasizes the need for a balanced view in discussions about AI's future.

Peter Voss is the visionary founder and CEO of Aigo.ai, a pioneering company at the forefront of conversational AI and natural language processing. Over the past 15 years, Peter and his team have perfected a highly intelligent, hyper-personalized chatbot designed for enterprise customers. In 2009, Peter founded SmartAction.ai, which developed the first AI-based contact center technology. Beyond his entrepreneurial endeavors, Peter is an engineer, inventor, and AI pioneer who writes and presents on philosophical topics such as rational ethics, free will, and artificial minds. He is also deeply involved in futurism and radical life extension.In this episode, we discuss:Peter Voss's Journey: From an electronics engineer to creating a successful software company, and his deep dive into the nature of intelligence and AI.Defining AGI: What Artificial General Intelligence (AGI) means to Peter, and how we will recognize its achievement.Cognitive Skills Gap: The differences between current AI technologies like large language models (LLMs) and true cognitive skills required for AGI.Path to AGI: The limitations of deep learning and LLMs, and why cognitive AI is the necessary path towards achieving AGI.Human Interaction and Intelligence: The importance of real-time learning, metacognition, and minimal sensory input in developing AGI.Ethics and Responsibility in AI: The philosophical and practical considerations of developing AGI, including the ethical implications and societal benefits.ResourceConnect with Peter AI fun fact articleAn episode you might like about the future of corporate VC

This week on The Index, host Alex Kehaya is joined by Peter Voss, Chief Scientist at Aigo, to discuss the cutting-edge advancements in conversational AI and its path towards Artificial General Intelligence (AGI). Peter shares his remarkable journey from electronics engineer to AGI pioneer, driven by a relentless curiosity that led him to develop a cognitive AI capable of outperforming thousands of human agents in customer service.Tune in for an in-depth exploration of the potential for AI to harness human-like intuition and the philosophical debates surrounding our pursuit of AGI. From breaking down the massive training methods employed by tech giants to examining the pivotal role of open-source in cognitive architectures, they delve into the complexities of AI development and its far-reaching implications for society.

In this #shifthappens podcast episode, AvePoint Chief Brand Officer Dux Raymond Sy dives into a fascinating conversation with Peter Voss, the CEO and Founder of Aigo.AI. Peter shares his decades-long journey in the field of artificial intelligence, from starting his own software company to ultimately setting his sights on building artificial general intelligence (AGI). He discusses the key differences between narrow AI and AGI, the challenges of commercializing AGI research, and his vision for how real AGI could transform industries and dramatically improve the human condition.

E36 Peter Voss | AIGO On this episode of Sound BITES we have Peter Voss founder and CEO of AIGO.AI. Peter is a serial entrepreneur, innovator, and technologist that has been on the leading edge of AI technology for years and is credited with coining the term “Artificial General intelligence”. His company AIGO is driving the future of customer experience and engagement to deliver hyper personalization at scale. Peter Voss: https://www.linkedin.com/in/vosspeter/ Aigo: https://aigo.ai/ Business Innovation Technology Entrepreneurship Strategy Spotify/Apple: https://www.nanochomp.com/podcast Instagram: https://www.instagram.com/nanochomp nanochomp's Strategic Mind GPT: https://nanochomp.com/strategygpt https://www.nanochomp.com Hosts: Lauren Taber: https://www.linkedin.com/in/laurentaber/ Derek Loyer: https://www.linkedin.com/in/derekloyer/ #Business #Innovation #Technology #Entrepreneurship #Strategy #Consulting #leadership #wellness #digitaltransformation #marketing #digitalmarketing #AI #artificialintelligence #agile #leadgen #sales #growth

Summary Artificial intelligence has dominated the headlines for several months due to the successes of large language models. This has prompted numerous debates about the possibility of, and timeline for, artificial general intelligence (AGI). Peter Voss has dedicated decades of his life to the pursuit of truly intelligent software through the approach of cognitive AI. In this episode he explains his approach to building AI in a more human-like fashion and the emphasis on learning rather than statistical prediction. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your team can get up and running in minutes thanks to Dagster Cloud, an enterprise-class hosted solution that offers serverless and hybrid deployments, enhanced security, and on-demand ephemeral test deployments. Go to dataengineeringpodcast.com/dagster (https://www.dataengineeringpodcast.com/dagster) today to get started. Your first 30 days are free! Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst (https://www.dataengineeringpodcast.com/starburst) and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'm interviewing Peter Voss about what is involved in making your AI applications more "human" Interview Introduction How did you get involved in machine learning? Can you start by unpacking the idea of "human-like" AI? How does that contrast with the conception of "AGI"? The applications and limitations of GPT/LLM models have been dominating the popular conversation around AI. How do you see that impacting the overrall ecosystem of ML/AI applications and investment? The fundamental/foundational challenge of every AI use case is sourcing appropriate data. What are the strategies that you have found useful to acquire, evaluate, and prepare data at an appropriate scale to build high quality models? What are the opportunities and limitations of causal modeling techniques for generalized AI models? As AI systems gain more sophistication there is a challenge with establishing and maintaining trust. What are the risks involved in deploying more human-level AI systems and monitoring their reliability? What are the practical/architectural methods necessary to build more cognitive AI systems? How would you characterize the ecosystem of tools/frameworks available for creating, evolving, and maintaining these applications? What are the most interesting, innovative, or unexpected ways that you have seen cognitive AI applied? What are the most interesting, unexpected, or challenging lessons that you have learned while working on desiging/developing cognitive AI systems? When is cognitive AI the wrong choice? What do you have planned for the future of cognitive AI applications at Aigo? Contact Info LinkedIn (https://www.linkedin.com/in/vosspeter/) Website (http://optimal.org/voss.html) Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. Links Aigo.ai (https://aigo.ai/) Artificial General Intelligence (https://aigo.ai/what-is-real-agi/) Cognitive AI (https://aigo.ai/cognitive-ai/) Knowledge Graph (https://en.wikipedia.org/wiki/Knowledge_graph) Causal Modeling (https://en.wikipedia.org/wiki/Causal_model) Bayesian Statistics (https://en.wikipedia.org/wiki/Bayesian_statistics) Thinking Fast & Slow (https://amzn.to/3UJKsmK) by Daniel Kahneman (affiliate link) Agent-Based Modeling (https://en.wikipedia.org/wiki/Agent-based_model) Reinforcement Learning (https://en.wikipedia.org/wiki/Reinforcement_learning) DARPA 3 Waves of AI (https://www.darpa.mil/about-us/darpa-perspective-on-ai) presentation Why Don't We Have AGI Yet? (https://arxiv.org/abs/2308.03598) whitepaper Concepts Is All You Need (https://arxiv.org/abs/2309.01622) Whitepaper Hellen Keller (https://en.wikipedia.org/wiki/Helen_Keller) Stephen Hawking (https://en.wikipedia.org/wiki/Stephen_Hawking) The intro and outro music is from Hitman's Lovesong feat. Paola Graziano (https://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Tales_Of_A_Dead_Fish/Hitmans_Lovesong/) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/)/CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0/)

In this episode, JP McAvoy interviews AI pioneer Peter Voss about his journey working on artificial intelligence and his views on the path to achieving Artificial General Intelligence (AGI), a term he coined in 2002. For over 20 years, he has been researching approaches to building artificial general intelligence and aims to develop systems that can learn and reason like humans.Listen in as JP and Peter discuss the definition of AGI and its potential impact, Issues with current AI models and the need for more efficient approaches, blockchain technology and investment in AI companies, AI's risks and benefits, how AI can assist humans in decision-making and problem-solving, limitations of current AI techniques, ways for potential improvement, using cognitive AI for customer support applications, and more. Connect with Your Host, JP: WebsiteFacebookXInstagramLinkedInShowEpisode Highlights:03:40 The Need for a More Human-Like Approach to AI Development09:51 Blockchain and Video Tech Investment18:25 AI and Its Potential in Problem-Solving22:40 AI's Limitations and Potential for Improvement26:14 AI Development with a Focus on Investment and Progess30:53 Cognitive AI for Customer Support37:14 AI and Its Potential to Revolutionize Humanity

Step into the future with Peter Voss, CEO and Chief Scientist at Aigo.ai. Peter Voss, a pioneer in the artificial intelligence space, to explore the cutting edge of AI technology. This episode dives into the transformative world of Artificial General Intelligence (AGI), a leap beyond today's AI capabilities, aiming to replicate human cognitive abilities in software. Hear about the challenges and breakthroughs in developing AGI, including its potential to revolutionize industries, enhance customer service, and even redefine the nature of work itself. Thank you for listening! Please subscribe wherever you listen to podcasts and give us a rating. - Need marketing strategy? Go to alpenglo.digital/ - Contact Us: alpenglo.digital/get-in-touch/

In this episodes we invite Peter Voss from Aigo.ai into the studio to talk about Artificial Intelligence and how it can reduce friction for customers and consumers. Visit https://thetonyjohnson.teachable.com/ to invest in your sales team.   - Don't let the rulebook get in the way of creating great customer experiences. - Hyper pesonalization is a key way to build loyalty by customizing experiences and recognizing customer preferences. - Great automation can help you win during your peak periods by serving customers more quickly. - Cognitive AI will be a game changer to help supplement contact center agents and serve customers more effectively than generative AI. Get in touch with Peter Voss:  https://aigo.ai/   It's time for the great service comeback!  Visit Visit https://ignite-your-customer-service-master-class.teachable.com/p/six-canons-of-customer-service to invest in my latest virtual hospitality program.   Tony Johnson is a Customer Experience Expert, Keynote Speaker, and Author with a wide background including decades in retail and restaurants.  He regularly speaks and coaches organizations to IGNITE THEIR SERVICE using his common sense approach to Customer engagement.  Tony has spoken to government agencies and Fortune 500 companies to unlock their amazing capacity for excellence.   Check out my FREE Resources and Training Tools: Web: https://www.igniteyourservice.com/ YouTube: https://www.youtube.com/@TheTonyJohnson Twitter:  https://twitter.com/The_TonyJohnson Instagram: https://www.instagram.com/THE_TONYJOHNSON/ Tik Tok:   https://www.tiktok.com/@igniteyourservice Facebook:  https://www.facebook.com/tonyjohnsoncx/     Music: http://www.bensound.com

In this episode of The AI for Sales Podcast, we engage in an insightful conversation with Peter Voss, the CEO and chief scientist of Aigo.ai. Discover how AI-powered chatbots with cognitive capabilities are revolutionizing customer interactions, transforming sales processes, and shaping the future of AI in sales. Gain valuable insights into the potential of AI to solve complex problems, enhance personalization, and revolutionize customer service.KEY TAKEAWAYSThe evolution of AI-powered chatbots from basic automation to cognitive intelligence.The importance of cognitive AI in understanding, remembering, and reasoning within customer interactions.The limitations of statistical and generative AI in providing meaningful customer service compared to cognitive AI.The potential of AI to revolutionize various industries, including healthcare, education, and customer service.The ethical implications and future outlook of AI in the workforce.QUOTES"We're not there yet. And currently, the focus is all on statistical AI... but the real excitement is in cognitive AI.""True AI or AGI is really like everyone winning the lottery... it will free up people tremendously to do more of the things they want to do.""It's not the train that everybody wants to jump on... It's still very much the momentum with statistical and generative AI."Connect and learn more about Peter Voss through the link below:LinkedIn: https://www.linkedin.com/in/vosspeter/Learn more about AI for Sales with Chad:LinkedIn Group: https://www.linkedin.com/groups/12811259/LinkedIn Personal Page: https://www.linkedin.com/in/chadburmeister/YouTube Channel: https://www.youtube.com/@TheAIforSalesPodcastTikTok: https://www.tiktok.com/@ai4salesFacebook Page: https://www.facebook.com/theaiforsalespodcast/Twitter Page: https://twitter.com/saleshackThe AI For Sales Podcast is sponsored by our proud partners:BDR.ai | https://www.bdr.ai/TruVersity | https://www.truversity.com/Joe Papa's (Co-host) LinkedIn Profile | https://www.linkedin.com/in/mrjoepapa/

In this episode of What That Means, Camille gets into artificial general intelligence (AGI) and cognitive architecture with Peter Voss, CEO and Chief Scientist at Aigo.ai. They talk about how he helped coin the term artificial general intelligence, the definitions of AGI and intelligence, how current LLMs like ChatGPT are not really AGI, training and sensory input for AGI, metacognition, Aigo.ai's “chatbot with a brain,” and how AGI might shape the future of humanity. Read Peter Voss' book, Artificial General Intelligence, here: https://link.springer.com/book/10.1007/978-3-540-68677-4   The views and opinions expressed are those of the guests and author and do not necessarily reflect the official policy or position of Intel Corporation.  

On today's episode, Managing Editor James Kleimann talks with Peter Voss, the co-founder and broker-owner of 3% Listing Co. Peter and James talk about NAR's $418 million settlement agreement in the commission lawsuits, 3% Listing Co.'s commission model, and what Peter has experienced when representing sellers who would not commit to paying buyer's agents. Related to this episode: Connect with Peter on LinkedIn 3% Listing Co NAR settles commission lawsuits for $418 million The Gathering HousingWire's YouTube Channel Enjoy the episode! The HousingWire Daily podcast examines the most compelling articles reported across HW Media. Each morning, we provide our listeners with a deeper look into the stories coming across our newsrooms that are helping Move Markets Forward. Hosted and produced by the HW Media team. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of The Power Producers Podcast, David Carothers sits down with Peter Voss, CEO of Aigo.ai. Peter shares his deep insights into AI's role in enhancing operational efficiency, the critical balance of AI and human interaction, and offers a glimpse into the future of AI technologies. Key Topics: The potential and limitations of generative AI in business applications The importance of human oversight in AI-generated content and strategies The role of AI in automating, routine tasks and its impact on industries The evolution and future of cognitive AI as the next significant leap in technology Misconceptions about AI's capabilities and the reality of its implementation Practical applications of AI in improving business operations and customer service The societal and ethical considerations of integrating AI into everyday life Connect with: Peter Voss David Carothers LinkedIn Kyle Houck LinkedIn Visit Websites: Aigo.ai Florida Risk Partners The Extra 2 Minutes

In this episode of The Power Producers Podcast, David Carothers sits down with Peter Voss, CEO of Aigo.ai. Peter shares his deep insights into AI's role in enhancing operational efficiency, the critical balance of AI and human interaction, and offers a glimpse into the future of AI technologies. Key Topics: The potential and limitations of generative AI in business applications The importance of human oversight in AI-generated content and strategies The role of AI in automating, routine tasks and its impact on industries The evolution and future of cognitive AI as the next significant leap in technology Misconceptions about AI's capabilities and the reality of its implementation Practical applications of AI in improving business operations and customer service The societal and ethical considerations of integrating AI into everyday life Connect with: Peter Voss David Carothers LinkedIn Kyle Houck LinkedIn Visit Websites: Aigo.ai Florida Risk Partners The Extra 2 Minutes

IN CLEAR FOCUS: AI pioneer Peter Voss discusses the evolution from "narrow AI" tools such as ChatGPT towards Artificial General Intelligence (AGI). Sharing his journey from engineer to AI innovator, Peter explains how his company, AIGO.ai, has developed a "chatbot with a brain." Hear how its cognitive AI, with advanced understanding and memory, revolutionizes customer service with hyper-personalized interactions. We also discuss potential use cases for personalizing advertising and marketing.

Peter Voss, a Pioneer in AI who coined the term ‘Artificial General Intelligence' and the CEO and Chief Scientist at Aigo.ai. For the past 15 years, Voss and his team at Aigo have been perfecting an industry disruptive, highly intelligent and hyper-personalized Chatbot, with a brain, for large enterprise customers. Here are some key insights from this week's show: - Unlike AI, for humans, reasoning is an evolutionary afterthought. Data can direct but not decide. - Flowcharts don't often cover the way people actually want their problems solved. - Studying human intelligence can be a powerful tool to improve AI. - AI needs infusion of common sense. - When software starts to think, learn and reason, it can lead to a better life for everyone. - The ultimate goal is to have technology benefit humanity. - A fundamental limitation of current AI systems is that they cannot learn in real time and cannot think about their own cognitive abilities.

Peter Voss, a Pioneer in AI who coined the term ‘Artificial General Intelligence' and the CEO and Chief Scientist at Aigo.ai. For the past 15 years, Voss and his team at Aigo have been perfecting an industry disruptive, highly intelligent and hyper-personalized Chatbot, with a brain, for large enterprise customers. Here are some key insights from this week's show: - Unlike AI, for humans, reasoning is an evolutionary afterthought. Data can direct but not decide. - Flowcharts don't often cover the way people actually want their problems solved. - Studying human intelligence can be a powerful tool to improve AI. - AI needs infusion of common sense. - When software starts to think, learn and reason, it can lead to a better life for everyone. - The ultimate goal is to have technology benefit humanity. - A fundamental limitation of current AI systems is that they cannot learn in real time and cannot think about their own cognitive abilities. Watch the video version here: https://youtu.be/2GTv_QhwChQ

Welcome to another insightful episode of "The Scaling Edge," where we delve into the minds of innovators and entrepreneurs who are pushing the boundaries of technology and business. I'm your host, Michael Brooks, joined by my co-host, Max, and today we have the pleasure of speaking with a visionary in the field of artificial intelligence, Peter Voss, the CEO of AI Go.- Introduction to Peter Voss and his background as an electronics engineer who made the leap into the world of software entrepreneurship.- Voss shares his journey and the pivotal moments that sparked his interest in developing smarter, more intuitive software solutions.- Discussion on the concept of artificial general intelligence (AGI) and how it differs from the narrow AI applications we see today.- Peter Voss elaborates on the importance of concept formation and metacognition in achieving human-like intelligence in AI systems.- Insight into the limitations of current AI models, including popular ones like ChatGPT, and why they fall short in terms of self-awareness and understanding.- Voss introduces the audience to the innovative work his company, AI Go, is doing with cognitive AI, particularly in call centers, to provide hyper-personalized customer service experiences.- The conversation shifts to the broader implications of AGI development, including the potential risks and the ethical considerations that must be addressed.- Peter Voss talks about the future of AI and the exciting possibilities that lie ahead for those willing to invest and collaborate in this space.- Closing remarks with an invitation for listeners to engage with AI Go, whether it be through collaboration, investment, or simply learning more about their work in AGI.Thank you for tuning in to this episode of "The Scaling Edge." Don't forget to subscribe to our podcast for more discussions with the trailblazers and thought leaders at the forefront of technology and innovation.Remember to check out our website and follow us on social media for updates and exclusive content.#ArtificialGeneralIntelligence, #PeterVoss, #AIGo, #TheScalingEdgePodcast, #AIInnovation, #Entrepreneurship, #SoftwareDevelopment, #CognitiveAI, #CallCenterAI, #AGIEthics, #TechInvestment, #AIIndustryLeaders, #FutureOfAI, #TechPodcasts, #InnovationDiscussion, #MichaelBrooks, #AIChallenges, #MetacognitionAI, #AIBusinessApplications, #AIRevolution, #SmartSoftware, #AIInterviews

Join us in an enlightening conversation with Peter Voss, the pioneering founder of Aigo, as we go into the extraordinary journey of transforming the concept of AI beyond conventional chatbots. Discover the story behind Aigo's inception, where Peter's deep research into the nature of intelligence, reality, and human cognition laid the foundation for a groundbreaking 'intelligent human-like cognitive Brain.' This isn't just any AI - it's an innovative system capable of remembering, learning, understanding context, and adapting to individual users, poised to revolutionize how we interact with technology across industries.Whether you're a tech enthusiast, a marketing executive, or just curious about the future of AI, this video promises a deep dive into the world of intelligent, personalized AI assistants that are set to change the world.Tune in to gain invaluable insights from one of the industry's most respected figures! Find out more by visiting https://aigo.ai/ today.Subscribe to the Backstory on Marketing and AI for more updates on market trends and AI updates. Follow us on Facebook: https://www.facebook.com/profile.php?...Website: https://prorelevant.com/What's your backstory?

Join Scott "Shalom" Klein on his weekly radio show, Get Down To Business with guests: Jones Loflin Moshik Temkin Peter Voss Malcolm Peace

On episode #141 of Eye on AI, Craig Smith sits down with Peter Voss, founder, CEO, and Chief Scientist of Aigo.ai. Join us as we take a deep dive into the world of artificial general intelligence (AGI) In this episode we embark on Peter's remarkable journey, from his roots as an electronics engineer to his significant role in the pursuit of AGI. Discover how his vision differs from mainstream AI approaches, leaning on cognitive architectures and graph knowledge bases. Ever wondered about the immense potential of real-time learning in AGI? We unearth the secrets behind teaching a system general knowledge and enhancing its cognitive abilities. Dive into the concept of life logging and personalized AI assistants, gaining fresh insights into how AI can adapt and learn on the fly. We wrap things up with a discussion on the challenges of funding AGI projects and explore the competitive landscape in the realm of chatbots and large language models. Get an inside look at Aigo.ai's customer base and pricing strategy.   Peter Voss's LinkedIn: https://www.linkedin.com/in/vosspeter/ Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI   00:00 Preview and Data Stax 02:19 Starting an AI Company 07:26 What are Cognitive Architectures? 12:19 Knowledge Graphs in Aigo.ai 15:20 AI Personal Assistants 21:47 The Future of AGI 28:01 Challenges and Limitations of Current AI Models 36:55 Approaches to AGI Development 46:11 Development and Progress Toward AGI 58:08 The Importance of AGI and Collaboration  

We are thrilled to announce the third session of our new Incubator Program. If you have a business idea that involves a web or mobile app, we encourage you to apply to our eight-week program. We'll help you validate your market opportunity, experiment with messaging and product ideas, and move forward with confidence toward an MVP. Learn more and apply at tbot.io/incubator. We look forward to seeing your application in our inbox! Peter Voss is the CEO and Chief Scientist of Aigo.ai, a groundbreaking alternative to conventional chatbots and generative models like ChatGPT. Aigo's chatbot is powered by Artificial General Intelligence (AGI), enabling it to think, learn, and reason much like a human being. It boasts short-term and long-term memory, setting it apart in terms of personalized service and context-awareness. Along with host Chad Pytel, Peter talks about how most chatbots and AI systems today are basic. They can answer questions but can't understand or remember the context. Aigo.ai is different because it's built to think and learn more like humans. It can adapt and get better the more you use it. He also highlights the challenges Aigo.ai faces in securing venture capital, given that its innovative approach doesn't align with current investment models heavily focused on generative or deep learning AI. Peter and Chad agree that while generative AI serves certain functions well, the quest for a system that can think, learn, and reason like a human demands a fundamentally different approach. Aigo.ai (https://aigo.ai/) Follow Aigo.ai on LinkedIn (https://www.linkedin.com/company/aigo-ai/) or YouTube (https://www.youtube.com/channel/UCl3XKNOL5rEit0txjVA07Ew). Follow Peter Voss on LinkedIn (https://www.linkedin.com/in/vosspeter/). Visit his website: optimal.org/voss.html (http://optimal.org/voss.html) Follow thoughtbot on X (https://twitter.com/thoughtbot) or LinkedIn (https://www.linkedin.com/company/150727/). Become a Sponsor (https://thoughtbot.com/sponsorship) of Giant Robots! Transcript: CHAD: This is the Giant Robots Smashing Into Other Giant Robots Podcast, where we explore the design, development, and business of great products. I'm your host, Chad Pytel. And with me today is Peter Voss, CEO and Chief Scientist at Aigo.ai. Peter, thanks so much for joining me. PETER: Yes, thank you. CHAD: So, tell us a little bit about what Aigo.ai does. You've been working in AI for a long time. And it seems like Aigo is sort of the current culmination of a lot of your 15 years of work, so... PETER: Yes, exactly. So, the quick way to describe our current product is a chatbot with a brain, and the important part is the brain. That basically, for the last 15-plus years, I've been working on the core technology for what's called AGI, Artificial General Intelligence, a system that can think, learn, reason similar to the way humans do. Now, we're not yet at human level with this technology. But it's a lot smarter and a lot more usable than traditional chatbots that don't have a brain. CHAD: I want to dig into this idea a little bit. I think, like a lot of people, I've used just traditional chatbots, particularly like ChatGPT is the latest. I've built some things on top of it. What is the brain that makes it different? Especially if you've used one, what is using Aigo going to be different? PETER: Right. I can give a concrete example of one of our customers then I can talk about the technology. So, one of our big customers is the 1-800-Flowers group of companies, which is Harry & David Popcorn Factory and several others. And wanted to provide a hyper-personalized concierge service for their customers where, you know, the system learns who you buy gifts for, for what occasions, you know, what your relationship is to them, and to basically remember who you are and what you want for each of their 20 million customers. And they tried different technologies out there, you know, all the top brands and so on, and they just couldn't get it off the ground. And the reason is because they really don't learn. And we now have 89% self-service on the things that we've implemented, which is pretty much unheard of for complex conversations. So, why can we do that? The reason is that our system has deep understanding. So, we have deep pausing, deep understanding, but more importantly, that the system remembers. It has short-term memory. It has long-term memory. And it uses that as context. So, you know, when you call back a second time, it'll remember what your previous call was, you know, what your preferences are, and so on. And it can basically use that information, the short and long-term memory, and reason about it. And that is really a step forward. Now, until ChatGPT, which is really very different technology from chatbot technology, I mean, chatbot technology, you're assuming...the kind of thing we're talking about is really augmenting call center, you know, automatic call center calls. There, you need deep integration into the customers' back-end system. You obviously need to know what the latest product availability is, what the customers' outstanding orders are, you know, all sorts of things like, you know, delivery schedules. And we probably have, like, two dozen APIs that connect our system to their various corporate databases and so on. Now, traditional chatbots obviously can do that. You hook up the APIs and do things, and it's, you know, it's a lot of work. But traditional chatbot technology really hasn't really changed much in 30 years. You basically have a categorizer; how can I help you? Basically, try to...what is the intent, intent categorizer? And then once your intent has been identified, you basically have a flowchart-type program that, you know, forces you down a flowchart. And that's what makes them so horrible because it doesn't use context. It doesn't have short-term memory. CHAD: And I just wanted to clarify the product and where you mentioned call center. So, this isn't just...or only text-based chat. This is voice. PETER: Yes. We started off with chat, and we now also have voice, so omnichannel. And the beauty of the system having the brain as well is you can jump from text messaging to a chat on the website to Apple ABC to voice, you know. So, you can basically move from one channel to another seamlessly. You know, so that's against traditional chatbot technology, which is really what everybody is still using. Now, ChatGPT, of course, the fact that it's called ChatGPT sort of makes it a bit confusing. And, I mean, it's phenomenal. The technology is absolutely phenomenal in terms of what it can do, you know, write poems and give you ideas. And the amount of information it's amazing. However, it's really not suited for commercial-grade applications because it hallucinates and it doesn't have memory. CHAD: You can give it some context, but it's basically faking it. You're providing it information every time you start to use it. PETER: Correct. The next time you connect, that memory is gone, you know [crosstalk 05:58] CHAD: Unless you build an application that saves it and then feeds it in again. PETER: Right. Then you basically run out of context we know very quickly. In fact, I just published a white paper about how we can get to human-level AI. And one of the things we did and go over in the paper is we did a benchmark our technology where we fed the system about 300 or 400 facts, simple facts. You know, it might be my sister likes chocolate or, you know, it could be other things like I don't park my car in the garage or [chuckles], you know. It could be just simple facts, a few hundred of those. And then we asked questions about that. Now, ChatGPT scored less than 1% on that because, you know, with an 8K window, it basically just couldn't remember any of this stuff. So, we use -- CHAD: It also doesn't, in my experience...it's basically answering the way it thinks the answer should sound or look. And so, it doesn't actually understand the facts that you give it. PETER: Exactly. CHAD: And so, if you feed it a bunch of things which are similar, it gets really confused because it doesn't actually understand the things. It might answer correctly, but it will, in my experience, just as likely answer incorrectly. PETER: Yeah. So, it's extremely powerful technology for helping search as well if a company has all the documents and they...but the human always has to be in the loop. It just makes way too many mistakes. But it's very useful if it gives you information 8 out of 10 times and saves you a lot of time. And it's relatively easy to detect the other two times where it gives you wrong information. Now, I know in programming, sometimes, it's given me wrong information and ended up taking longer to debug the misinformation it gave me than it would have taken me. But overall, it's still a very, very powerful tool. But it really isn't suitable for, you know, serious chatbot applications that are integrated into back-end system because these need to be signed off by...legal department needs to be happy that it's not going to get the company into trouble. Marketing department needs to sign off on it and customer experience, you know. And a generative system like that, you really can't rely on what it's going to say, and that's apart from security concerns and, you know, the lack of memory and deep understanding. CHAD: Yeah. So, you mentioned generative AI, which is sort of one of the underlying pieces of ChatGPT. In your solutions, are you using any generative solutions? PETER: No, not at all. Well, I can give one example. You know, what 1-800-Flowers do is they have an option to write a poem for your mother's birthday or Mother's Day or something like it. And for that, we will use ChatGPT, or they use ChatGPT for that because that's what it's good at. But, you know, that's really just any other app that you might call up to do something for you, you know, like calling up FedEx to find out where your goods are. Apart from that, our technology...it's a good question you ask because, you know, statistical systems and generative AI now have really dominated the AI scene for the last about 12 years, really sort of since DeepMind started. Because it's been incredibly successful to take masses amounts of data and masses amounts of computing power and, you know, number crunch them and then be able to categorize and identify images and, you know, do all sorts of magical things. But, the approach we use is cognitive AI as opposed to generative. It's a relatively unknown approach, but that's what we've been working on for 15 years. And it starts with the question of what does intelligence require to build a system so that it doesn't use masses amounts of data? It's not the quantity of data that counts. It's the quality of data. And it's important that it can learn incrementally as you go along like humans do and that it can validate what it learns. It can reason about, you know, new information. Does this make sense? Do I need to ask a follow-up question? You know, that kind of thing. So, it's cognitive AI. That's the approach we're using. CHAD: And, obviously, you have a product, and you've productized it. But you said, you know, we've been working on this, or you've been working on this model for a long time. How has it progressed? PETER: Yes, we are now on, depending on how you count, but on the third major version of it that we've started. And really, the progress has been determined by resources really than any technology. You know, it's not that we sort of have a big R&D requirement. It's really more development. But we are a relatively small company. And because we're using such different technology, it's actually been pretty hard to raise VC money. You know, they look at it and, you know, ask you, "What's your training data? How big is your model?" You know, and that kind of thing. CHAD: Oh, so the questions investors or people know to ask aren't relevant. PETER: Correct. And, you know, they bring in the AI experts, and then they say, "Well, what kind of deep learning, machine learning, or generative, or what transformer model are using?" And we say, "Well, we don't." And typically, that's kind of, "Oh okay, well, then it can't possibly work, you know, we don't understand it." So, we just recently launched. You know, with all the excitement of generative AI now recently, with so much money flowing into it, we actually launched a major development effort. Now we want to hire an additional a hundred people to basically crank up the IQ. So, over the years, you know, we're working on two aspects of it: one is to continually crank up the IQ of the system, that it can understand more and more complex situations; it can reason better and be able to handle bigger amounts of data. So, that's sort of the technical part that we've been working on. But then the other side, of course, running a business, a lot of our effort over the last 15 years has gone into making it industrial strength, you know, security, scalability, robustness of the system. Our current technology, our first version, was actually a SaaS model that we deployed behind a customer's firewall. CHAD: Yeah, I noticed that you're targeting more enterprise deployments. PETER: Yeah, that's at the moment because, financially, it makes more sense for us to kind of get off the ground to work with, you know, larger companies where we supply the technology, and it's deployed usually in the cloud but in their own cloud behind their firewall. So, they're very happy with that. You know, they have complete control over their data and reliability, and so on. But we provide the technology and then just licensing it. CHAD: Now, a lot of people are familiar with generative AI, you know, it runs on GPUs and that kind of thing. Does the hardware profile for where you're hosting it look the same as that, or is it different? PETER: No, no, no, it requires much less horsepower. So, I mean, we can run an agent on a five-year-old laptop, you know, and it doesn't...instead of it costing $100 million to train the model, it's like pennies [laughter] to train the model. I mean, we train it during our regression testing, and that we train it several times a day. Mid-Roll Ad: When starting a new project, we understand that you want to make the right choices in technology, features, and investment but that you don't have all year to do extended research. In just a few weeks, thoughtbot's Discovery Sprints deliver a user-centered product journey, a clickable prototype or Proof of Concept, and key market insights from focused user research. We'll help you to identify the primary user flow, decide which framework should be used to bring it to life, and set a firm estimate on future development efforts. Maximize impact and minimize risk with a validated roadmap for your new product. Get started at: tbot.io/sprint. CHAD: So, you mentioned ramping up the IQ is a goal of yours. With a cognitive model, does that mean just teaching it more things? What does it entail? PETER: Yes, there's a little bit of tension between commercial requirements and what you ultimately want for intelligence because a truly intelligent system, you want it to be very autonomous and adaptive and have a wide range of knowledge. Now, for current commercial applications we're doing, you actually don't want the system to learn things by itself or to make up stuff, you know, you want it to be predictable. So, they develop and to ultimately get to full human-level or AGI capability requires a system to be more adaptive–be able to learn things more. So, the one big change we are making to the system right now is natural language understanding or English understanding. And our current commercial version was actually developed through our—we call them AI psychologists, our linguists, and cognitive psychologists—by basically teaching it the rules of English grammar. And we've always known that that's suboptimal. So, with the current version, we are now actually teaching it English from the ground up the way a child might learn a language, so the language itself. So, it can learn any language. So, for commercial applications, that wasn't really a need. But to ultimately get to human level, it needs to be more adaptive, more autonomous, and have a wider range of knowledge than the commercial version. That's basically where our focus is. And, you know, we know what needs to be done, but, you know, it's quite a bit of work. That's why we need to hire about 100 people to deal with all of the different training things. It's largely training the system, you know, but there are also some architectural improvements we need to make on performance and the way the system reasons. CHAD: Well, you used the term Artificial General Intelligence. I understand you're one of the people who coined that term [chuckles] or the person. PETER: Yes. In 2002, I got together with two other people who felt that the time was ripe to get back to the original dream of AI, you know, from 60 years ago, to build thinking machines basically. So, we decided to write a book on the topic to put our ideas out there. And we were looking for a title for the book, and three of us—myself, Ben Goertzel, and Shane Legg, who's actually one of the founders of DeepMind; he was working for me at the time. And we were brainstorming it, and that's what we came up with was AGI, Artificial General Intelligence. CHAD: So, for people who aren't familiar, it's what you were sort of alluding to. You're basically trying to replicate the human brain, the way humans learn, right? That's the basic idea is -- PETER: Yeah, the human cognition really, yeah, human mind, human cognition. That's exactly right. I mean, we want an AI that can think, learn, and reason the way humans do, you know, that it can hit the box and learn a new topic, you know, you can have any kind of conversation. And we really believe we have the technology to do that. We've built quite a number of different prototypes that already show this kind of capability where it can, you know, read Wikipedia, integrate that with existing knowledge, and then have a conversation about it. And if it's not sure about something, it'll ask for clarification and things like that. We really just need to scale it up. And, of course, it's a huge deal for us to eventually get to human-level AI. CHAD: Yeah. How much sort of studying of the brain or cognition do you do in your work, where, you know, sort of going back and saying, "Okay, we want to tackle this thing"? Do you do research into cognition? PETER: Yeah, that's a very interesting question. It really gets to the heart of why I think we haven't made more progress in developing AGI. In fact, another white paper I published recently is "Why Don't We Have AGI Yet?" And, you know, one of the big problems is that statistical AI has been so incredibly successful over the last decade or so that it sucked all of the oxygen out of the air. But to your question, before I started on this project, I actually took off five years to study intelligence because, to me, that's really what cognitive AI approach is all about is you start off by saying, what is intelligence? What does it require? And I studied it from the perspective of philosophy, epistemology, theory of knowledge. You know, what's reality? How do we know anything? CHAD: [laughs] PETER: How can we be sure? You know, really those most fundamental questions. Then how do children learn? What do IQ tests measure? How does our intelligence differ to animal intelligence? What is that magic difference between, you know, evolution? Suddenly, we have this high-level cognition. And the short answer of that is being able to form abstract concepts or concept formation is sort of key, and to have metacognition, to be able to think about your own thinking. So, those are kind of the things I discovered during the five years of study. Obviously, I also looked at what had already been done in the field of AI, as in good old-fashioned AI, and neural networks, and so on. So, this is what brought me together. So, absolutely, as a starting point to say, what is intelligence? Or what are the aspects of intelligence that are really important and core? Now, as far as studying the brain is concerned, I certainly looked at that, but I pretty quickly decided that that wasn't that relevant. It's, you know, you certainly get some ideas. I mean, neural networks, ours is kind of a neural network or knowledge graph, so there's some similarity with that. But the analogy one often gives, which I think is not bad, is, you know, we've had flying machines for 100 years. We are still nowhere near reverse engineering a bird. CHAD: Right. PETER: So, you know, evolution and biology are just very different from designing things and using the materials that we need to use in computers. So, definitely, understanding intelligence, I think, is key to being able to build it. CHAD: Well, in some ways, that is part of the reason why statistical AI has gotten so much attention with that sort of airplane analogy because it's like, maybe we need to not try to replicate human cognition [chuckles]. Maybe we need to just embrace what computers are good at and try to find a different way. PETER: Right, right. But that argument really falls down when you say you are ignoring intelligence, you know, or you're ignoring the kind of intelligence. And we can see how ridiculous the sort of the current...well, I mean, first of all, let me say Sam Altman, and everybody says...well, they say two things: one, we have no idea how these things work, which is not a good thing if you're [chuckles] trying to build something and improve it. And the second thing they say...Demis Hassabis and, you know, everybody says it, "This is not going to get us to human-level AI, to human-level intelligence." They realize that this is the wrong approach. But they also haven't come up with what the right approach is because they are stuck within the statistical big data approach, you know, we need another 100 billion dollars to build even bigger computers with bigger models, you know, but that's really -- CHAD: Right. It might be creating a tool, which has some uses, but it is not actual; I mean, it's not really even actual artificial intelligence -- PETER: Correct. And, I mean, you can sort of see this very easily if...imagine you hired a personal assistant for yourself, a human. And, you know, they come to you, and they know how to use Excel and do QuickBooks or whatever, and a lot of things, so great. They start working with you. But, you know, every now and again, they say something that's completely wrong with full confidence, so that's a problem. Then the second thing is you tell them, "Well, we've just introduced a new product. We shut down this branch here. And, you know, I've got a new partner in the business and a new board member." And the next day, they come in, and they remember nothing of that, you know, [chuckles] that's not very intelligent. CHAD: Right. No, no, it's not. It's possible that there's a way for these two things to use each other, like generating intelligent-sounding, understanding what someone is saying and finding like things to it, and being able to generate meaningful, intelligent language might be useful in a cognitive model. PETER: We obviously thought long and hard about this, especially when, you know, generative AI became so powerful. I mean, it does some amazing things. So, can we combine the technology? And the answer is quite simply no. As I mentioned earlier, we can use generative AI kind of as an API or as a tool or something. You know, so if our system needs to write a poem or something, then yes, you know, these systems can do a good job of it. But the reason you can't really just combine them and kind of build a Frankensteinian kind of [laughs] thing is you really need to have context that you currently have fully integrated. So you can't have two brains, you know, the one brain, which is a read-only brain, and then our brain, our cognitive brain, which basically constantly adapts and uses the context of what it's heard using short-term memory, long-term memory, reasoning, and so on. So, all of those mental mechanisms of deep understanding of context, short-term and long-term memory, reasoning, language generation–they all have to be tightly integrated and work together. And that's basically the approach that we have. Now, like a human to...if you write, you know, "Generate an essay," and you want to have it come up with maybe some ideas, changing the style, for example, you know, it would make sense for our system to use a generative AI system like a tool because humans are good tool users. You know, I wouldn't expect our system to be the world chess champion or Go champion. It can use a chess-playing AI or a Go-playing AI to do that job. CHAD: That's really cool. You mentioned the short-term, long-term memory. If I am using or working on a deployment for Aigo, is that something that I specify, like, oh, this thing where we've collected goes in short term versus long term, or does the system actually do that automatically? PETER: That's the beauty of the system that: it automatically has short and long-term memory. So, really, the only thing that needs to be sort of externally specified is things you don't want to keep in long-term memory, you know, that for some reason, security reasons, or a company gives you a password or whatever. So, then, they need to be tagged. So, we have, like, an ontology that describes all of the different kinds of knowledge that you have. And in the ontology, you can tag certain branches of the ontology or certain nodes in the ontology to say, this should not be remembered, or this should be encrypted or, you know, whatever. But by default, everything that comes into short-term memory is remembered. So, you know, a computer can have photographic memory. CHAD: You know, that is part of why...someone critical of what they've heard might say, "Well, you're just replicating a human brain. How is this going to be better?" And I think that that's where you're just...what you said, like, when we do artificial general intelligence with computers, they all have photographic memory. PETER: Right. Well, in my presentations, when I give talks on this, I have the one slide that actually talks about how AI is superior to humans in as far as getting work done in cognition, and there's actually quite a number of things. So, let me first kind of give one example here. So, imagine you train up one AI to be a PhD-level cancer researcher, you know, it goes through whatever training, and reading, and coaching, and so on. So, you now have this PhD-level cancer researcher. You now make a million copies of that, and you have a million PhD-level cancer researchers chipping away at the problem. Now, I'm sure we would make a lot more progress, and you can now replicate that idea, that same thinking, you know, in energy, pollution, poverty, whatever, I mean, any disease, that kind of approach. So, I mean, that already is one major difference that you make copies of an AI, which you can't of humans. But there are other things. First of all, they are significantly less expensive than humans. Humans are very expensive. So much lower cost. They work 24/7 without breaks, without getting tired. I don't know the best human on how many hours they can concentrate without needing a break, maybe a few hours a day, or six, maybe four hours a day. So, 24/7. Then, they can communicate with each other much better than humans do because they could share information sort of by transferring blocks of data across from one to the other without the ego getting in the way. I mean, you take humans, not very good at sharing information and discoveries. Then they don't have certain distractions that we have like romantic things and kids in schools and, you know. CHAD: Although if you actually do get a full [laughs] AGI, then it might start to have those things [laughs]. PETER: Well, yeah, that's a whole nother topic. But our AIs, we basically build them not to want to have children [laughs] so, you know. And then, of course, things we spoke about, photographic memory. It has instantaneous access to all the information in the world, all the databases, you know, much better than we have, like, if we had a direct connection to the internet and brain, you know, but at a much higher bandwidth than we could ever achieve with our wetware. And then, lastly, they are much better at reasoning than humans are. I mean, our ability to reason is what I call an evolutionary afterthought. We are not actually that good at logical thinking, and AIs can be, you know. CHAD: We like to think we are, though. PETER: [chuckles] Well, you know, compared to animals, yes, definitely. We are significantly better. But realistically, humans are not that good at rational, logical thinking. CHAD: You know, I read something that a lot of decisions are made at a different level than the logical part. And then, the logical part justifies the decision. PETER: Yeah, absolutely. And, in fact, this is why smart people are actually worse at that because they're really good at rationalizations. You know, they can rationalize their weird beliefs and/or their weird behavior or something. That's true. CHAD: You mentioned that your primary customers are enterprises. Who makes up your ideal customer? And if someone was listening who matched that profile and wanted to get in touch with you, what would they look like? PETER: The simplest and most obvious way is if they have call centers of 100 people or more—hundreds, or thousands, tens of thousands even. But the economics from about 100 people in the call center, where we might be able to save them 50% of that, you know, depending on the kind of business. CHAD: And are your solutions typically employed before the actual people, and then they fall back to people in certain circumstances? PETER: Correct. That's exactly right. And, you know, the advantage there is, whatever Aigo already gathers, we then summarize it and pop that to the human operator so that, you know, that the customer -- CHAD: That's great because that's super annoying. PETER: It is. CHAD: [laughs] PETER: It is super annoying and -- CHAD: When you finally get to a person, and it's like, I just spent five minutes providing all this information that you apparently don't have. PETER: Right. Yeah, no, absolutely, that's kind of one of the key things that the AI has that information. It can summarize it and provide it to the live operator. So that would be, you know, the sort of the most obvious use case. But we also have use cases on the go with student assistant, for example, where it's sort of more on an individual basis. You know, imagine your kid just starts at university. It's just overwhelming. It can have a personal personal assistant, you know, that knows all about you in particular. But then also knows about the university, knows its way around, where you get your books, your meals, and, you know, different societies and curriculum and so on. Or diabetes coach, you know, where it can help people with diabetes manage their meals and activities, where it can learn whether you love broccoli, or you're vegetarian, or whatever, and help guide you through that. Internal help desks are another application, of course. CHAD: Yeah. I was going to say even the same thing as at a university when people join a big company, you know, there's an onboarding process. PETER: Exactly. Yeah. CHAD: And there could be things that you're not aware of or don't know where to find. PETER: Internal HR and IT, absolutely, as you say, on onboarding. Those are other applications where our technology is well-suited. And one other category is what we call a co-pilot. So, think of it as Clippy on steroids, you know, where basically you have complex software like, you know, SAP, or Salesforce, or something like that. And you can basically just have Aigo as a front end to it, and you can just talk to it. And it will know where to navigate, what to get, and basically do things, complex things in the software. And software vendors like that idea because people utilize more features of the software than they would otherwise, you know. It can accelerate your learning curve and make it much easier to use the product. So, you know, really, the technology that we have is industry and application-agnostic to a large extent. We're just currently not yet at human level. CHAD: Right. I hope you get there eventually. It'll be certainly exciting when you do. PETER: Yes. Well, we do expect to get there. We just, you know, as I said, we've just launched a project now to raise the additional money we need to hire the people that we need. And we actually believe we are only a few years away from full human-level intelligence or AGI. CHAD: Wow, that's exciting. So, if the solution that you currently have and people want to go along for the journey with you, how can they get in touch with Aigo? PETER: They could contact me directly: peter@aigo.ai. I'm also active on Twitter, LinkedIn. CHAD: Cool. We'll include all of those links in the show notes, which people can find at giantrobots.fm. If you have questions for me, email me at hosts@giantrobots.fm. Find me on Mastodon @cpytel@thoughtbot.social. You can find a complete transcript for this episode as well at giantrobots.fm. Peter, thank you so much for joining me. I really appreciate it and all of the wisdom that you've shared with us today. PETER: Well, thank you. They were good questions. Thank you. CHAD: This podcast is brought to you by thoughtbot and produced and edited by Mandy Moore. Thanks for listening, and see you next time. ANNOUNCER: This podcast is brought to you by thoughtbot, your expert strategy, design, development, and product management partner. We bring digital products from idea to success and teach you how because we care. Learn more at thoughtbot.com. Special Guest: Peter Voss.

On today's episode, we're joined by Peter Voss, Founder/ CEO/ Chief Scientist, AGI Innovations & Aigo.ai, developers of the first and only “Chatbot with a Brain.” We talk about:The 3 waves of AIHyper personalization as compared to generative AIHow chatbot technology in the future will conduct interviews to learn requirementsTraceability to understand any mistakes with AIBuilding a truly personal assistant that serves your agenda, is hyper-personalized, & private

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. With the advancements in conversation AI technology, AI is able to deliver superior and hyper-personalized customer experiences. Sophisticated AI technology has the ability to remember all past interactions, works 24/7, and has no wait time. Today, Peter discusses hyper-personalization using AI in customer service. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. With the advancements in conversation AI technology, AI is able to deliver superior and hyper-personalized customer experiences. Sophisticated AI technology has the ability to remember all past interactions, works 24/7, and has no wait time. Today, Peter discusses hyper-personalization using AI in customer service. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Can machines really think like humans? What is the future of General Artificial Intelligence (GAI) when machines more closely resemble human behaviour than ever before? In this episode, Peter unveils his journey into the realm of General Artificial Intelligence (GAI) and his vision of machines possessing the ability to think, learn, and reason like humans. We look at the intricacies of General AI and how it sets itself apart from narrow AI.The episode also looks at how companies are tackling the immense challenges associated with crafting machines with general intelligence - from understanding the significance of concept formation in artificial general intelligence to discussing the role of quantum computing and resources in AI development.Peter also provided his views on the potential of machines developing empathy and the role of AI in ethical and moral debates, and answers the questions I've always wanted to ask - can AI feel empathy and love? Finally, we take a peek into the future as Peter shares how Aigo.ai is harnessing the power of conversational AI to revolutionize personalised experiences. More on PeterPeter on LinkedInPeter on MediumAigo websitePeter Voss is the world's foremost authority in Artificial General Intelligence. He coined the term 'AGI' in 2001 and published a book on Artificial General Intelligence in 2002. He is a Serial AI entrepreneur, technology innovator who has for the past 20 years been dedicated to advancing Artificial General Intelligence. Peter Voss' careers include being an entrepreneur, engineer and scientist. His experience includes founding and growing a technology company from zero to a 400-person IPO. For the past 20 years, his focus has been on developing AGI (artificial general intelligence). In 2008 Peter founded Smart Action Company, which offers the only call automation solution powered by an AGI engine. He is now CEO & Chief Scientist at Aigo.ai Inc., which is developing and selling increasingly advanced AGI systems for large enterprise customers. Peter also has a keen interest in the inter-relationship between philosophy, psychology, ethics, futurism, and computer science.Your Host: Actionable Futurist® & Chief Futurist Andrew GrillFor more on Andrew - what he speaks about and recent talks, please visit ActionableFuturist.com Andrew's Social ChannelsAndrew on LinkedIn@AndrewGrill on Twitter @Andrew.Grill on InstagramKeynote speeches hereAndrew's upcoming book

Peter Voss is a Serial Entrepreneur, Engineer, Inventor, and AI Pioneer who famously coined the term ‘AGI' (Artificial General Intelligence) alongside fellow luminaries. Beginning with electronics engineering, he transitioned to software, achieving a significant feat by leading a comprehensive ERP company from zero to a 400-person IPO within seven years. Motivated by software's delicacy, Peter embarked on a journey over 15 years ago, delving into intelligence's essence, its human development, and AI's contemporary landscape. This endeavor culminated in the birth of a natural language intelligence engine, capable of thinking, learning, reasoning, adapting, and growing alongside users.Currently, he is focused on advancing the second iteration of AGI-driven 'Conversational AI' technology, now presented as 'Aigo' (pronounced: I-go).Key Takeaways:Advances in Conversational AI: Newer chatbots with contextual understanding, memory, and reasoning are revolutionizing interactions, overcoming limitations of traditional flowchart-based bots.Language Nuances and Effectiveness: Detecting emotions and tone enhances chatbot responses, but the core challenge is making them genuinely helpful.AI's Spectrum and Practicality: AI spans diverse technologies, demanding careful implementation amidst the hype. Complexities in business contexts often overshadow AI's potential.Implementation Challenges: Large language models like ChatGPT have limitations, generating incorrect info. Vital industries require human oversight due to accuracy concerns.Balancing Adoption and Caution: Businesses must balance AI adoption with suitability, focusing on value addition while acknowledging risks and limitations.Realistic AI Expectations: Hype around AI, like ChatGPT, will decline as understanding grows. Swift replacement of professionals by AI is unrealistic.Human Expertise Vital: AI assists but lacks complex comprehension. Human experts remain crucial for intricate decision-making and nuanced scenarios.AI for Idea Generation: ChatGPT aids idea generation, content creation, but human review is essential for error correction.AI's Industry Impact: AI reshapes industries via automation. Valuable in content creation, AI won't fully replace human creativity.Balancing Automation and Humanity: AI streamlines, yet human touch remains crucial in interactions. Seamless transitions between AI and human involvement are the goal.Top 3 Takeaways:There is a lot to be excited about with the future of AI, especially AGI.AGI will become more capable of human-like thinking, learning, and reasoning.Peter envisions a future where there are highly personalized AI assistants, referred to as a "personal personal personal assistant." The assistant will tailor interactions based on individual relationships and share information selectively. This comprehensive assistant aims to enhance user experiences and simplify engagement with technology and services. How to connect with Peter:LinkedIn: https://www.linkedin.com/in/vosspeter/Website: https://aigo.ai

Peter Voss is the founder and CEO of Argo, whose AI has upped the chatbot interactions that companies can have with customers. We talked about what AI currently does, and what AI can't yet do that makes AI so artificial. We also talked about how AI helps clients provide value to customers better than chatbots. Learn more about your ad choices. Visit megaphone.fm/adchoices

On this episode of the AI For All Podcast, Peter Voss, CEO & Chief Scientist at Aigo.ai, joins Ryan Chacon and Neil Sahota to discuss AI chatbots, ChatGPT, and artificial general intelligence. They talk about how chatbots with a brain compare to average chatbots, why more people aren't working on AGI, the benefits of AGI, the business need for AI chatbots, using ChatGPT for business, GPT and memory, trusting AI chatbots, modeling the mind, and the future of AI chatbots. Peter Voss is the CEO and Chief Scientist at Aigo.ai. For the past 15 years, Voss and his team at Aigo have been perfecting an industry disruptive, highly intelligent, and hyper-personalized chatbot with a brain for large enterprise customers. Aigo.ai presents the most intelligent AI chatbot that acts as an enterprise digital assistant, enhancing customer experience. More about Aigo.ai: https://aigo.ai Connect with Peter: https://www.linkedin.com/in/vosspeter/ Key Questions and Topics from This Episode: (00:00) Intro to the AI For All Podcast (00:55) Intro to Peter Voss and Aigo.ai (01:14) Chatbots with a brain versus average chatbots (03:11) What is Artificial General Intelligence (AGI)? (05:25) Why aren't more people working on AGI? (08:06) Benefits of AGI for business (10:28) What was the business need for AI chatbots? (12:21) Applications of AI chatbots (15:15) ChatGPT and use in business (19:12) GPT and memory (22:38) Benefits of AI chatbots (26:13) Trust issues with AI chatbots (28:38) Automation vs innovation (31:03) Modeling the mind in a chatbot (34:52) The future of AI chatbots (37:30) Learn more about Aigo.ai Subscribe on YouTube: https://bit.ly/43dYQV9 Join Our Newsletter: https://ai-forall.com Follow Us on Twitter: https://twitter.com/_aiforall

In this episode of the Evolving Leader, co-hosts Jean Gomes and Scott Allender talk to serial entrepreneur, engineer, inventor and pioneer in artificial intelligence Peter Voss. Peter spent more than 15 years studying what intelligence is, how it develops in humans and also the current state of artificial intelligence, resulting in the creation of a natural language intelligence engine designed to “adapt and grow” with the user. During that time Peter was part of a group that coined the term AGI (artificial general intelligence) and is now focused on commercialising the second generation of an AGI-based conversational AI technology called Aigo. His mission is to provide “highly intelligent and hyper-personalised assistants for everyone”. Reference in this episode:Aigo.aiPeter's articles on Medium 0.00 Introduction3.31 How did you get into the artificial intelligence space?4.57 Can you give us a simple definition of AI?9.37 So when we look at these systems, why is it different this time?12.24 There's a lot of excitement and a lot of fear surround AI. How will AGI solve problems that need to be solved, and what are the risks?15.06 With this radical abundance, there is always a flip side. With every technology, human nature does what it does, good or bad. What are the ethical and/or moral challenges facing us with this technology?18.02 How in your mind would AGI stand in the gap between psychology and AI?20.38 The current investment that is being placed into all technologies is dependent on the current ways that the global economic system works. When we unleash this abundance, it changes some of the basic assumptions about how capitalism works. What are thoughts regarding that disruption and how is it going to change the fabric of our society?22.49  Are we at risk with getting to a level of AGI in every facet of our lives where people will struggle to find their human purpose other than depending on this technology?24.19 Where does AI start to harm us and how to prevent that existential crisis?26.07 Turning to what our audience should be doing to prepare for this AI revolution? Is there something that they should be thinking about and doing now?29.32 If you were advising a CEO on how to ready their organisation for the next decade, what would your checklist of top priorities be in getting them to think about things?30.52 What are the moral considerations to make sure that we can advertise to people but not take over their independent thinking in how they live their lives or what they want to buy?34.24 The reason why we're lured into this is that it's seemingly free. How do we break that economic cycle?35.52 Coming back to the fears, how do we ensure that the personal assistant is secure, that it won't flip and reveal all of our secrets to the world?39.39 How is the area that you're working in playing out compared to the big model systems?44.42 Can you set a time frame for us? What do you think the next 5-10 years holds in terms of what you're doing? When will it really start to change our lives?47.00 Your day job is commercially utilising this conversational AI technology and there are huge opportunities there. 49.36 So what is standing in your way to accelerate this?50.37 How can people get in touch with you? Social: Instagram           @evolvingleaderLinkedIn             The Evolving Leader PodcastTwitter               @Evolving_LeaderYouTube   Please take 5 minutes to complete our listener survey

Discover when Peter Voss (Founder and CEO of AIGO.AI) decided to create a "Chatbot with a Brain", why he was able to lead a team of 400 people, and how he discovered his leadership blind spot (12 minute episode). CEO BLINDSPOTS® PODCAST GUEST: Peter Voss. He is the Founder, CEO, and Chief Scientist of AIGO.AI, an AGI-based Cognitive AI company with the world's first and only Chatbot with a Brain. Aigo AI is used by enterprise customers to deliver hyper-personalized experiences for their customers and employees. Aigo AI is at the forefront of the trend where 'Conversational AI is the new UI'. Peter started out in electronics engineering, but quickly moved into software. After developing a comprehensive ERP software package, Peter took his first software company from a zero to 400-person IPO in seven years. Fueled by the fragile nature of software, Peter embarked on a 20-year journey to study intelligence (how it develops in humans, how to measure it, and current AI efforts), and to replicate it in software. His research culminated in the creation of a natural language intelligence engine that can think, learn, and reason -- and adapt to, and grow with the user. He even coined the term ‘AGI'(Artificial General Intelligence) with fellow luminaries in the space. Peter is a Serial Entrepreneur, Engineer, Inventor and a Pioneer in Artificial Intelligence. For more information about Peter Voss and his company AIGO.ai; https://aigo.ai/how-it-works/ CEO Blindspots® Podcast Host: ⁠⁠Birgit Kamps⁠⁠. Having built an Inc. 500 Fastest Growing Private Company, Birgit has become the world's most trusted bridge builder for getting leadership teams to go further, faster. Since Birgit sold her previous staffing company, she started a leadership consulting company and serves as a Board Member with various companies. In addition, Birgit started and is the host of the CEO Blindspots® Podcast, where leaders learn from other leaders as they share their best practices and blind spots; ⁠⁠https://www.ceoblindspots.com/⁠⁠ To ask questions about this or one of the 200+ other CEO Blindspots® Podcast episodes, send an email to⁠⁠ ⁠birgit@ceoblindspots.com⁠

Peter Voss is a Pioneer in AI who coined the term ‘Artificial General Intelligence' and the CEO and Chief Scientist at Aigo.ai. For the past 15 years, Voss and his team at Aigo have been perfecting an industry disruptive, highly intelligent and hyper-personalized Chatbot, with a brain, for large enterprise customers. In this episode of the Product Science Podcast, we cover career opportunities in AI development, the potential of AI to be personal and an assistant, and how embracing a future with AI means focusing on critical thinking skills. Read the show notes to learn more: URL: www.h2rproductscience.com/post/the-peter-voss-hypothesis-we-will-soon-need-to-embrace-ai-to-be-effective-in-the-world

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. With the advancements in conversation AI technology, AI is able to deliver superior and hyper-personalized customer experiences. Sophisticated AI technology has the ability to remember all past interactions, works 24/7, and has no wait time. Today, Peter discusses hyper-personalization using AI in customer service. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. With the advancements in conversation AI technology, AI is able to deliver superior and hyper-personalized customer experiences. Sophisticated AI technology has the ability to remember all past interactions, works 24/7, and has no wait time. Today, Peter discusses hyper-personalization using AI in customer service. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.