Podcasts about expert systems

In this episode Allan and Drew consult Tim Rohrbaugh, who has done quite a lot of research and work on the practical applications, deployment, use cases and limits of GenAI and LLM. Flavors and incarnations of AI - GenAI, Expert Systems, ML... Biomimicry and Allan's weird sea cucumber references Practical LLM deployment - Tim's maxims Offline or online?  Open or proprietary models? Precision, accuracy, asking the right questions in the first place Your smartest employee as your limiting factor Probabilistic vs. deterministic outcomes Hallucinations - not necessarily a negative term How long before we get the person out of the loop? The actual skills required to be a "GenAI engineer" Getting started at home - hardware and models Fabric AI and patterns It's a great show and you will most definitely learn a lot!  Thank you Tim, thank you, listeners!  Y'all be good now!

 Today, Paul reflects on his journey as an innovation evangelist and shares the valuable lessons he's learned over nearly four decades in the industry. He expresses gratitude to his listeners, guests, and colleagues while recounting the significant milestones that have shaped the Innovation Talks series. This introspective episode serves as a heartfelt farewell as Innovation Talks closes its podcast run, leaving a legacy of knowledge and insight for innovators worldwide. Paul Heller has an illustrious career advancing innovation practices across various organizations. Paul's work has influenced countless professionals in the field. With a background at IBM and startup experience, Paul's journey is rich with firsthand accounts of implementing cutting-edge solutions and methodologies such as Expert Systems and Stage Gate. His unique perspective on cross-functional integration and empathy in innovation has made him a revered voice in the industry. “Staying positive and seeing the good in every situation keeps the spirit of innovation alive through any challenge.” ~ Paul Heller Today on Innovation Talks: • The importance of cross-functional understanding: Innovation involves marketing, sales, manufacturing, distribution, product development, and customer success, aligning towards a common goal. • Embracing diverse business disciplines: Experience in sales, consulting, customer support, and engineering development can significantly enhance one's capability in innovation. • The value of empathy: Empathy towards colleagues, especially when challenges arise, is crucial for a positive and collaborative work environment. • Staying positive as a strategic advantage: Maintaining a positive attitude and seeing the best in people can drive team morale and productivity. • Configurability as a cornerstone: Unique processes and success measurements require adaptable systems, a lesson learned from product configurator projects. • The evolution of Expert Systems to AI: Early experience with Expert Systems demonstrates how foundational technologies have evolved into modern AI applications. • Importance of compassion in leadership: Genuine compassion and understanding within teams foster a collaborative environment conducive to innovation. • Continuous learning and respect for colleagues: Maintaining a beginner's mindset and respecting peers can lead to ongoing personal growth and team success. Resources Mentioned: • Guy Kawasaki's Wikipedia page: To learn about the origins of the term "evangelist" in a technology context. https://en.wikipedia.org/wiki/Guy_Kawasaki • Sopheon: A company supporting innovation and methodologies like Stage Gate. https://www.sopheon.com/ • Union Pacific Railroad innovations: Historical examples of early AI application in rail maintenance and optimization.https://www.up.com/aboutup/community/inside_track/ai-rahul-insights-it-230721.htm • Gateway 2000: A case study in product configurators for complex product sales. https://www.techspot.com/article/2087-gateway-2000/  This Podcast is brought to you by Sopheon Thanks for tuning into this week's episode of Innovation Talks. If you enjoyed this episode, please subscribe and leave a review wherever you get your podcasts. Apple Podcasts | TuneIn | GooglePlay | Stitcher | Spotify | iHeart Be sure to connect with us on Facebook, Twitter, and LinkedIn, and share your favorite episodes on social media to help us reach more listeners, like you. For additional information around new product development or corporate innovation, sign up for Sopheon's newsletter where we share news and industry best practices monthly! The fastest way to do this is to go to sopheon.com and click here.

Sramana Mitra is the founder and CEO of One Million by One Million (1Mby1M), the world's first and only global virtual incubator/accelerator. Its goal is to help a million entrepreneurs globally reach a million dollars in annual revenue, build a trillion dollars in global GDP, and create 10 million jobs.Since its founding in 2010, 1Mby1M has become a powerful platform for democratization of entrepreneurship acceleration.Sramana also developed 1Mby1M's Incubator-in-a-Box methodology for Corporate Incubation that is used by enterprises to manage internal and external innovation endeavors.In 2015, LinkedIn named Sramana one of their Top 10 Influencers alongside Bill Gates and Richard Branson.Sramana has been an entrepreneur and a strategy consultant in Silicon Valley since 1994. Her fields of experience span from hardcore technology disciplines like Artificial Intelligence, Cloud Computing and Semiconductors, to sophisticated consumer marketing industries including e-commerce, fashion and education.As an entrepreneur CEO, Sramana founded three companies: Dais (off-shore software services), Intarka (sales lead generation and qualification software using Artificial Intelligence algorithms; VC: NEA) and Uuma (online personalized store for selling clothes using Expert Systems software; VC: Redwood). Two of these were acquired, while the third received an acquisition offer from Ralph Lauren which the company did not accept.As strategy consultant, Sramana has consulted with over 80 companies, including public companies such as SAP, Cadence Design Systems, Webex, KLA-Tencor, Best Buy, MercadoLibre and Tessera among others. Her work has also included numerous startups and VCs.Sramana has a Masters degree in EECS from MIT and a Bachelors degree in Computer Science and Economics from Smith College.From 2000 to 2004, Sramana chaired the MIT Club of Northern California's entrepreneurship program in Silicon Valley.Learn more at www.1Mby1M.com

In Part 4 of our series, 'Contracting in the Age of AI - Responsible AI - "This is the Way!", Rhonda Maus, Professor of Software Engineering, Agile Coach, and DAU's lead for AI Research, goes more in-depth into Responsible AI (RAI), what is RAI, trusting our systems (how do we keep control?), the beauty of AI (what about risk?), why does AI make errors?, importance of quality data (biases), how relate to AI ethical principals, and AI in small batches to be agile (to reduce the risk).  We will bring on other AI experts, with DoD and industry, to help answer your questions and bring additional perspectives - we need your help in giving us those AI topics.  Below are some great resources to grow your AI knowledge:For any Software Agile training (SWE XXXX), go to dau.edu - recommendations from Rhonda coming soon. Defense Cyber Workforce Framework:  https://dodcio.defense.gov/Cyber-Workforce/DCWF/Defense Cyber Workforce Framework Tool:  https://public.cyber.mil/wid/dcwf/DoD AI Ethical Principles:  https://www.ai.mil/docs/Ethical_Principles_for_Artificial_Intelligence.pdfDoD Memo:  Implementing Responsible Artificial Intelligence in the Department of Defense (2021): https://media.defense.gov/2021/May/27/2002730593/-1/-1/0/IMPLEMENTING-RESPONSIBLE-ARTIFICIAL-INTELLIGENCE-IN-THE-DEPARTMENT-OF-DEFENSE.PDFDoD Responsible AI (RAI Strategy & Implementation Pathway:  https://www.ai.mil/docs/RAI_Strategy_and_Implementation_Pathway_6-21-22.pdfCDAO Press Release on the new DoD RAI Toolkit:  https://www.defense.gov/News/Releases/Release/Article/3588743/cdao-releases-responsible-ai-rai-toolkit-for-ensuring-alignment-with-rai-best-p/CDAO's RAI Toolkit Website:  https://rai.tradewindai.com/  Access to Contracting Conversations can be found at:DAU Media:  https://media.dau.edu/channel//231324903YouTube:  https://www.youtube.com/@dau-contractingconversatio9271Apple Podcasts:  https://podcasts.apple.com/us/podcast/contracting-conversations/id1621567225Please subscribe, like and share - thank you for being part of the Contracting Conversations family!

In Part 3 of our series, 'Contracting in the AGE of AI - What is going on in DoD with AI?', Rhonda Maus, Professor of Software Engineering, Agile Coach, and DAU's lead for AI Research, talks about the adoption of AI mandates, how DoD is organizing itself, how we define the workforce roles, and Responsible AI (RAI) and what it means for DoD.We also want to hear from you and answer your questions about AI.  We will bring on other AI experts, with DoD and industry, to help answer your questions and bring additional perspectives.  Below are some great resources to grow your AI knowledge:Defense Cyber Workforce Framework:  https://dodcio.defense.gov/Cyber-Workforce/DCWF/ Defense Cyber Workforce Framework Tool:  https://public.cyber.mil/wid/dcwf/ DoD AI Ethical Principles:  https://www.ai.mil/docs/Ethical_Principles_for_Artificial_Intelligence.pdf DoD Memo:  Implementing Responsible Artificial Intelligence in the Department of Defense (2021): https://media.defense.gov/2021/May/27/2002730593/-1/-1/0/IMPLEMENTING-RESPONSIBLE-ARTIFICIAL-INTELLIGENCE-IN-THE-DEPARTMENT-OF-DEFENSE.PDF DoD Responsible AI (RAI Strategy & Implementation Pathway:  https://www.ai.mil/docs/RAI_Strategy_and_Implementation_Pathway_6-21-22.pdf CDAO Press Release on the new DoD RAI Toolkit:  https://www.defense.gov/News/Releases/Release/Article/3588743/cdao-releases-responsible-ai-rai-toolkit-for-ensuring-alignment-with-rai-best-p/ CDAO's RAI Toolkit Website:  https://rai.tradewindai.com/  Links from previous AI episodes:DAU AI Toolkit - AI Definition and Reference:   https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAI%20AI%20Toolkit%20-%20AI%20Descriptors%20and%20Definitions%20Reference%20Charts.pdfDAU AI Toolkit - AI Systems Intelligence Checklist: https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20System%20Intelligence%20Checklist%20-%20508.pdfDAU AI Toolkit - AI Glossary:  https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20Glossary.pdf    DAU AI Toolkit - Statute, Policy & Guidance Tracker:   https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20SPG%20Framework.pdfDAU's AI Learning Assets - Created for DoD!AI Channel Media Playlist:  https://media.dau.edu/channel/Artificial%2BIntelligence/310800832SWE0056 - What is AI? - Register at:  https://icatalog.dau.edu/onlinecatalog/courses.aspx?crs_id=13232SWE0056 Standalone video on What is AI? - https://media.dau.edu/media/t/1_fnlts39ySWE0057 What is Machine Learning (ML) - register at:  https://icatalog.dau.edu/onlinecatalog/courses.aspx?crs_id=13233SWE0057 Standalone video on What is Machine Learning (ML)?  https://media.dau.edu/playlist/dedicated/310800832/1_rv1ldfxr/1_hsij16avAccess to Contracting Conversations can be found at:DAU Media:  https://media.dau.edu/channel//231324903YouTube:  https://www.youtube.com/@dau-contractingconversatio9271Apple Podcasts:  https://podcasts.apple.com/us/podcast/contracting-conversations/id1621567225Please subscribe, like and share - thank you for being part of the Contracting Conversations family!

In Part 2 of our series, 'Contracting in the AGE of AI - So what is AI...Really?', Rhonda Maus, Professor of Software Engineering, Agile Coach, and DAU's lead for AI Research, talks about Applied versus Fundamental AI, types of AI software, AI Domains, the three DoD AI definitions, how AI can be applied to the contracting process, and will AI replace contracting personnel.  The last one is kind of scary, please listen in to hear what Rhonda has to say about it.We also want to hear from you and answer your questions about AI.  We will bring on other AI experts, with DoD and industry, to help answer your questions and bring additional perspectives.  Below are some great resources to grow your AI knowledge:DAU AI Toolkit - AI Definition and Reference:   https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAI%20AI%20Toolkit%20-%20AI%20Descriptors%20and%20Definitions%20Reference%20Charts.pdfDAU AI Toolkit - AI Systems Intelligence Checklist: https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20System%20Intelligence%20Checklist%20-%20508.pdf DAU AI Toolkit - AI Glossary:  https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20Glossary.pdf    DAU AI Toolkit - Statute, Policy & Guidance Tracker:   https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20SPG%20Framework.pdfDAU's AI Learning Assets - Created for DoD!AI Channel Media Playlist:  https://media.dau.edu/channel/Artificial%2BIntelligence/310800832 SWE0056 - What is AI? - Register at:  https://icatalog.dau.edu/onlinecatalog/courses.aspx?crs_id=13232 SWE0056 Standalone video on What is AI? - https://media.dau.edu/media/t/1_fnlts39y SWE0057 What is Machine Learning (ML) - register at:  https://icatalog.dau.edu/onlinecatalog/courses.aspx?crs_id=13233 SWE0057 Standalone video on What is Machine Learning (ML)?  https://media.dau.edu/playlist/dedicated/310800832/1_rv1ldfxr/1_hsij16av Access to Contracting Conversations can be found at:DAU Media:  https://media.dau.edu/channel//231324903 YouTube:  https://www.youtube.com/@dau-contractingconversatio9271 Apple Podcasts:  https://podcasts.apple.com/us/podcast/contracting-conversations/id1621567225 Please subscribe, like and share - thank you for being part of the Contracting Conversations family!

Are you curious about Artificial Intelligence (AI) and how it affects your work as a contracting professional? If so, you will want to tune in to the new series of DAU's Contracting Conversations podcast, Contracting in the Age of AI, where we will dive into the fascinating world of AI with our software expert, Rhonda Maus, Professor of Software Engineering, Agile Coach, and DAU's lead for AI research.  Please post your questions in the comments below or send them to james.valley@dau.edu.  You will learn what AI is and what it is not, how fast AI is changing and evolving, the difference between Fundamental and Applied AI, the types of AI software and how they work, how AI will impact your job and career, what is happening with AI within DoD and the challenges it poses, how to contract for AI effectively, and efficiently, how AI is being applied to contract management and the contracting process, and much more! We also want to hear from you and answer your questions about AI.  We will bring on other AI experts, within DoD and industry, to help answer your questions and bring additional perspectives. Below are some great resources to continue to grow your AI knowledge:        DAU AI Toolkit – AI Definition & Reference Chart chart:  https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAI%20AI%20Toolkit%20-%20AI%20Descript... DAU AI Toolkit-AI Systems Intelligence: https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20System%20Intelligence%20Che...  DAU AI Toolkit –AI Glossary: https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20Glossary.pdfDAU AI Toolkit – Statute, Policy & Guidance Tracker:  https://www.dau.edu/sites/default/files/Migrated/CopDocuments/DAU%20AI%20SPG%20Framework.pdf  DAU's AI Learning Assets – Created for DoD!    AI Channel Media Playlist:  https://media.dau.edu/channel/Artificial%2BIntelligence/310800832    SWE0056 – What is AI? - Register to take the course at   https://icatalog.dau.edu/onlinecatalog/courses.aspx?crs_id=13232Standalone Video on ‘What is AI?' - https://media.dau.edu/media/t/1_fnlts39y   SWE0057 – What is Machine Learning (ML) – Register for the course: https://icatalog.dau.edu/onlinecatalog/courses.aspx?crs_id=13233Standalone Video on ‘What is Machine Learning(ML)?' - https://media.dau.edu/playlist/dedicated/310800832/1_rv1ldfxr/1_hsij16avAccess to Contracting Conversations can be found at:DAU Media:  https://media.dau.edu/channel//231324903  YouTube:  https://www.youtube.com/@dau-contractingconversatio9271Apple Podcasts: https://podcasts.apple.com/us/podcast/contracting-conversations/id1621567225.Please subscribe, like and share – thank you for being part of Contracting Conversations!

Welcome to today's episode of "AI Lawyer Talking Tech," your daily review of the latest legal technology news. In today's episode, we dive into a range of topics, including the role of privacy and data security lawyers in helping clients comply with domestic and international laws, the rise of AI in the Chinese justice system, the departure of top leaders in law firms, Google's legal action against AI scammers, and the emerging trends in AI adoption within the legal industry. Practice Area Insights: Privacy & Data Security13 Nov 2023Firsthand.coOMG, China Has ACTUAL Legal Robots And All The Legal Tech Patents13 Nov 2023Above The LawAt least 25 top law firms will see departure of top leaders in 2023-2024; is there demographic bubble?13 Nov 2023ABA JournalGoogle Takes Legal Action Against AI Scammers & Copyright Fraud via @sejournal, @MattGSouthern13 Nov 2023Search Engine JournalJudge Will Toss Part of Authors' AI Copyright Lawsuit13 Nov 2023publishersweekly.comQuick Survey: AI & Emerging Technologies13 Nov 2023TheCorporateCounsel.net BlogThe Legal Industry Is Ripe for the Adoption of AI13 Nov 2023PYMNTS.comLegal IT Latest: News in brief from the UK, EMEA and North America13 Nov 2023Legal IT InsiderEp. 3: Law Meets the Theater in Successful Jury Trials13 Nov 2023Hurst Limontes LLCJimini AI, an AI co-pilot for legal professionals raises €1.9M13 Nov 2023Tech.euLaw.com launches search engine platform13 Nov 2023901amDigital Hollywood Focus on AI and Copyright12 Nov 2023Velocity of ContentGlobal Law Firm Breached & Data Stolen12 Nov 2023CyberSecurityIntelligence.comChief Legal Officers: 2024 Legal Services Trends Report by Santamarina + Steta12 Nov 2023ChaseThe E.U. is probing TikTok and YouTube over child safety, and it could challenge ad blocker bans10 Nov 2023TubefilterAttorney Time Management Tips for Peak Productivity10 Nov 2023LexBlogAI Update: The DPA, Faster (But Not Better) Legal Writing, Full AI Contract Negotiation10 Nov 2023Above The Law3 Top Requirements for a Legal Knowledge Management System13 Nov 2023Legal Technology News - Legal IT Professionals | Everything legal technologyNo consensus among lawyers about generative AI being an opportunity or threat13 Nov 2023GenAI-LexologyDual-agent Chatbots and Expert Systems design13 Nov 2023Legaltech on MediumAleph Alpha Raises a Total Investment of Over Half a Billion US Dollars From a Consortium of Industry Leaders and New Investors13 Nov 2023Legal Tech BlogThe Bletchley Declaration: further evidence of the global legislative focus on Artificial Intelligence13 Nov 2023Ireland IP & Technology Law BlogShould My Company Use Chat GPT for Commercial Use?09 Nov 2023GenAI-LexologyArtificial Intelligence Referees: Offsides and Out of Bounds13 Nov 2023Vanderbilt JETLawFrom London to California, Legal Innovators Are Go!13 Nov 2023Artificial LawyerRecognizing the Primacy of Artificial Intelligence in America: Biden's Executive Order Sets a High Bar for Regulation and Innovation10 Nov 2023GenAI-LexologyThe Persistent Gavel: A Curious Phenomenon in Chat GPT and DALL-E 3's AI Technology12 Nov 2023WardblawGHow to Make a Legal GPT Legally using Open AI's Chat GPT-4 Builder12 Nov 2023WardblawGThis Law Firm: Legal Call Systems for Modern Practices11 Nov 2023Legaltech on MediumLegal Tech for Law Schools: How to Prepare Law Students for the Future of the Legal Profession10 Nov 2023MatterSuite By CaseFoxOpen AI's “Copyright Shield” Broadens User IP Indemnities for AI-created Content10 Nov 2023New Media and Technology Law Blog

As we fight through layers of judgment and trauma, our "recovery" is regaining our true selves. The purpose of recovery is to no longer be a copy of someone else's vision. And how do we accomplish this? By intentionally creating expert systems to help you along the way. Tune in to this epeisode as we cover the last six expert systems, Intuition, Spirituality, Perspective, Consciousness, Compassion, and Mindfulness.

As we fight through layers of judgment and trauma, our "recovery" is regaining our true selves. The purpose of recovery is to no longer be a copy of someone else's vision. And how do we accomplish this? By intentionally creating expert systems to help you along the way. Tune in to this epeisode as we cover the first six expert systems, Intention, Self-care, Accountability, Study, Reflection, & Recovery Support.

In the Software Process and Measurement Cast 762, we host a panel discussion on the impact of AI on project management prospects. The panel of Paul Clapis, Susan Parente, Michael Milutis, and Mark Tolbert state categorically that project administration will be overtaken, but the high-value human side of project management will not be displaced. I am not sure what that means for most people working in the project management space. Listen to the discussion and then look carefully at the work you are doing. Will AI be a boon or a bane for project management?  Let the conversation begin. About Paul J. Clapis, Ph.D.:  Dr. Clapis has over 30 years of experience managing AI, Machine Learning, and RPA projects for NASA, aerospace, and financial services industries. He also directed the Hughes Advanced Computing Lab at Yale Science Park, where he conducted applied research in AI, Expert Systems, Machine Learning, and Neural Networks.  About Susan Parente: Susan is an Engineer/Consultant, speaker, and author with experience managing both software and hardware development. She is proficient in managing complex system implementation for companies seeking to use enterprise business software to improve business process efficiency. Susan is a regular contributor to the Software Process and Measurement podcast.    About Michael Milutis: Michael Milutis is an international keynote speaker, instructor, and 25-year veteran of the IT industry who has dedicated his career to helping individuals learn, develop, and compete within a shifting technology landscape.   About Mark Tolbert: Mark has over 30 years of experience in I.T., including 27 years at Hewlett-Packard. He successfully managed support programs and projects within HP Services. He is a full-time instructor for PMP Prep classes since November 2007. He is very passionate about project management and believes adopting the best project management practices and skills is crucial to the success of enterprises today.    Re-Read Saturday News The votes are in and we have a near tie for the top spot. I decided to re-read by Chip and Dan Heath first. Part of the rationale is that I have two copies of this book and have not read by L. David Marquet – yet. Once we have completed Made to Stick, we will launch ourselves into Leadership Is Language. By then I will have read the book.  Buy a copy of the book and then catch up on the logistics of this re-read: Week 1: - https://bit.ly/46tn5Bz Next SPaMCAST  In the Software Process and Measurement Cast 763, we will continue with our summer theme on critical thinking by exploring whether sources should matter when considering a topic.  We will also have a visit from Jon M Quigley and his Alpha and Omega of Product Development.  

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define DeepBlue, including what it is and why it's notable for AI. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary AI Glossary Series – Symbolic Systems & Expert Systems AI Glossary Series: Cognitive Technology Continue reading AI Today Podcast: AI Glossary Series – Deep Blue at AI & Data Today.

Before this latest wave of AI where neural nets became the hottest algorithm of choice, an approach to machine learning that uses logic and constructs similar to the way that humans reason through problems called Symbolic Systems were actually the system of choice. Popularized in the late 1980s and early 1990s expert systems became the AI system of choice for organizations investing in cognitive technology. Continue reading AI Today Podcast: AI Glossary Series: Symbolic Systems & Expert Systems at AI & Data Today.

Expert systems are a sub-discipline within artificial intelligence concerned with creating problem solving programs based on machine-encoded human domain expertise. An expert system typically consists of a knowledge base, consisting of human-defined rules, and an inference engine that can run a problem through the rules. Expert systems were a very popular and successful area of AI research in the 1970s and 1980s, but fell out of favor in the 1990s during the so-called "AI winter."" Today, most of the excitement in AI is around machine learning based systems, but expert systems still have a place thanks to their ability to explain their conclusions. Show Notes Episode 13: Artificial Intelligence Artificial Intelligence in the 21st Century via Amazon Follow us on Twitter @KopecExplains. Theme “Place on Fire” Copyright 2019 Creo, CC BY 4.0 Find out more at http://kopec.live

Summary Machine learning is a data-hungry approach to problem solving. Unfortunately, there are a number of problems that would benefit from the automation provided by artificial intelligence capabilities that don’t come with troves of data to build from. Christopher Nguyen and his team at Aitomatic are working to address the "cold start" problem for ML by letting humans generate models by sharing their expertise through natural language. In this episode he explains how that works, the various ways that we can start to layer machine learning capabilities on top of each other, as well as the risks involved in doing so without incorporating lessons learned in the growth of the software industry. Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. Predibase is a low-code ML platform without low-code limits. Built on top of our open source foundations of Ludwig and Horovod, our platform allows you to train state-of-the-art ML and deep learning models on your datasets at scale. Our platform works on text, images, tabular, audio and multi-modal data using our novel compositional model architecture. We allow users to operationalize models on top of the modern data stack, through REST and PQL – an extension of SQL that puts predictive power in the hands of data practitioners. Go to themachinelearningpodcast.com/predibase today to learn more and try it out! Your host is Tobias Macey and today I’m interviewing Christopher Nguyen about how to address the cold start problem for ML/AI projects Interview Introduction How did you get involved in machine learning? Can you describe what the "cold start" or "small data" problem is and its impact on an organization’s ability to invest in machine learning? What are some examples of use cases where ML is a viable solution but there is a corresponding lack of usable data? How does the model design influence the data requirements to build it? (e.g. statistical model vs. deep learning, etc.) What are the available options for addressing a lack of data for ML? What are the characteristics of a given data set that make it suitable for ML use cases? Can you describe what you are building at Aitomatic and how it helps to address the cold start problem? How have the design and goals of the product changed since you first started working on it? What are some of the education challenges that you face when working with organizations to help them understand how to think about ML/AI investment and practical limitations? What are the most interesting, innovative, or unexpected ways that you have seen Aitomatic/H1st used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Aitomatic/H1st? When is a human/knowledge driven approach to ML development the wrong choice? What do you have planned for the future of Aitomatic? Contact Info LinkedIn @pentagoniac on Twitter Google Scholar 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. 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@themachinelearningpodcast.com) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Links Aitomatic Human First AI Knowledge First World Symposium Atari 800 Cold start problem Scale AI Snorkel AI Podcast Episode Anomaly Detection Expert Systems ICML == International Conference on Machine Learning NIST == National Institute of Standards and Technology Multi-modal Model SVM == Support Vector Machine Tensorflow Pytorch Podcast.__init__ Episode OSS Capital DALL-E The intro and outro music is from Hitman’s Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0

Ecosystem updates from CCP Rattati, new expert systems and their impact on the new player experience. --- Support this podcast: https://anchor.fm/trashtalktuesday/support

En este episodio de Value Investing FM, Adrián y Paco tenemos el placer de entrevistar a Rodrigo Villanueva, fundador de New Vila Equity Research, sobre invertir en microcaps. Nos hablará de: - Sus inicios en el mundo de la bolsa con el curso gratuito de Paco - Los motivos por los que invierte en empresas poco líquidas y de pequeña capitalización - Su método para encontrar ideas de inversión en microcaps - Algunas de las principales posiciones en su cartera como Makolab, Kaisa Prosperity, Expert Systems o Tak Lee - Sus mayores errores de inversión en Teekay LNG y Fork

For many decades, humans have lived with the alluring idea that it must be possible to design artificial intelligence systems that can advise us on the most critical life and death decisions we may have to take, in warfare, justice, or complex missions that push human boundaries. However, such systems can easily fail, resulting in flawed decisions or analysis paralysis. In this episode, we discuss three dystopian scenarios where expert systems failed to deliver on their promises.

We are back! Eve meets for this year have been announced and we dive into them along with reminiscing about old ones. Fleet formations are out as well as Expert Systems.

heute: Die Lore-Ley von @schenkelc Link zur Hausaufgabe: https://differentia.files.worpress.com/2021/03/hausuafgabe-schenkelc.pdf

Carneros explains Expert Systems and why CCP might have wanted them.

Expert Systems - a way for new players to try new things fast. Snuff gets put out. --- Send in a voice message: https://anchor.fm/talking-in-stations/message Support this podcast: https://anchor.fm/talking-in-stations/support

heute: Transhumanismus oder: Technik behindert, was Versachlichung bewirkt

Transzendentaler Vermeidungsirrtum

Heute: korrupte Systeme (Fortsetzung)

Heute: korrupte Systeme

gender bias

Störkommunikation, Hausaufgabe von Frédéric Glas https://ueberflusshaus.de/2020/12/22/hausaufgabe-von-frederic-glas-wie-kann-mit-social-media-stoerkommunikation-betrieben-werden/

Klaus' Hausaufgabe https://differentia.files.wordpress.com/2020/11/selbstreferenz-tautologie-paradoxie-rekursion-und-paranoia-1.pdf

Allgemeinverständlichkeit

Die Hausaufgabe von @j_nibiru https://ueberflusshaus.de/2020/11/12/hausaufgabe-von-julien-simonet-zum-zusammenhang-von-wahnsinn-und-subjektivitaet-objektivitaet/

Ausnahmsweise mal Corona

Dispositiv der Bundesliga und der Wissenschaft als Objektivierungsleistung von Wahnvorstellungen

Wie Objektivierung gelingt - Die Bundesliga als Dispositiv

Sramana Mitra is the founder and CEO of One Million by One Million (1Mby1M), the world’s first and only global virtual incubator/accelerator. Its goal is to help a million entrepreneurs globally reach a million dollars in annual revenue, build a trillion dollars in global GDP, and create 10 million jobs. Since its founding in 2010, 1Mby1M has become a powerful platform for democratization of entrepreneurship acceleration. Sramana also developed 1Mby1M’s Incubator-in-a-Box methodology for Corporate Incubation that is used by enterprises to manage internal and external innovation endeavors. In 2015, LinkedIn named Sramana one of their Top 10 Influencers alongside Bill Gates and Richard Branson. Sramana has been an entrepreneur and a strategy consultant in Silicon Valley since 1994. Her fields of experience span from hardcore technology disciplines like Artificial Intelligence, Cloud Computing and Semiconductors, to sophisticated consumer marketing industries including e-commerce, fashion and education. As an entrepreneur CEO, Sramana founded three companies: Dais (off-shore software services), Intarka (sales lead generation and qualification software using Artificial Intelligence algorithms; VC: NEA) and Uuma (online personalized store for selling clothes using Expert Systems software; VC: Redwood). Two of these were acquired, while the third received an acquisition offer from Ralph Lauren which the company did not accept. As strategy consultant, Sramana has consulted with over 80 companies, including public companies such as SAP, Cadence Design Systems, Webex, KLA-Tencor, Best Buy, MercadoLibre and Tessera among others. Her work has also included numerous startups and VCs. Sramana has a Masters degree in EECS from MIT and a Bachelors degree in Computer Science and Economics from Smith College. From 2000 to 2004, Sramana chaired the MIT Club of Northern California’s entrepreneurship program in Silicon Valley. Learn more at www.1Mby1M.com

Are our roles as traders coming to an end soon? Is AI and ML (that’s Machine Learning, not Money Laundering or Meat Loaf…) going to take over the trading world? Trading veteran Bob Pardo from Pardo Capital joins us to discuss these topics plus much more, including: How AI is missing common inputs used by human traders, Modeling the expertise of human traders using Expert Systems, The dangers of using computers to blindly create strategies, Retail edges vs Institutional edges and how private traders can compete, The lifespans of edges (are they getting shorter?), The Dynamic Statistical Profile of strategies and taking strategies offline, Correlations (and how correlation can be a 2-edge sword), Objective functions and when it doesn't matter which one you choose, Using performance feedback and indicators on equity curves, Adaptive trading systems, fitting your process to your objective and much more!

Heute: Wie ein Leben kaum noch gelingt: verbessere deine Informationssituation

Davide Calì is an Italian executive, researcher, and founder, who during his twenty-five years long career, successfully delivered over five hundred IT projects. More than thirty of them were executed in cooperation with Fortune 500 companies. He led and participated in over twenty research projects, some of which resulted in Intellectual Property patents. He wrote a dozen of international IT scientific papers, specifically addressing AI-related areas such as Smart Agents, Expert Systems, NLP, Ontologies, and Machine Learning. From 2001 to 2015 he was CTO/CEO and partner of seven Technology and Artificial Intelligence Start-ups (four Italian and three International). In 2010, he was chosen as the software expert for the Italian government delegation at the World Exhibition in Shanghai and after few years of cross border projects, in 2015, he permanently relocated to Shanghai. In 2016 he co-founded EXPAND, a Technology Accelerator for early-stage start-ups focusing on Deep Tech, Digital Science, and Smart Industry.

In this episode, we are joined by Josh Cutler, VP & Sr. Distinguished Engineer for AI Platforms & Transformation Team at Optum. Josh shared with us his 15+ years of experience in applying data and intelligence to solve hard business problems. I really liked Josh's definition of the application of AI being, "How can we help computers make good decisions". This cuts to the core of why we are building these systems and what the outcome should be.Besides the applications Josh is building with his team today, he shared with us how he got into the field, the startups he founded, and how Microsoft was actually ahead of their time in this space with their Live Labs initiative and so much more. Enjoy!Finally, if you are interested in learning about how AI is being applied across multiple industries, be sure to join us at a future Applied AI Monthly meetup and help support us so we can make future Emerging Technologies North non-profit events!Emerging Technologies NorthAppliedAI MeetupHere's just a few of the many fun and interesting topics discussed during this podcast:Computer VisionNLPChoose Your Own AdventureNate SilverOffice AssistantRamblTwitterComputational Frameworks for Political and Social Research with PythonMVPFast.aiEnjoy!Your host,Justin Grammens

Si un tema domina las expectativas de empresas y personas hoy en día es el impacto, riesgos y oportunidades, de la Inteligencia Artificial; desde robots y coches automatizados a recomendaciones muy personalizadas de productos y servicios, las aplicaciones y por ello las oportunidades de llevar a la realidad ideas que antes parecían de ciencia ficción, son ilimitadas. De este campo y de las oportunidades concretas hablamos con Alberto Robles, CEO de Expert Systems para España.

Daniel has spent his entire professional and personal career in the field of Industrial Engineers.  In this episode, we explore the effects of the COVID-19 pandemic, a “Black Swan” event, on the way businesses might operate post-pandemic.   We start by discussing how telephony in education and the corporate world will be embraced more readily to its becoming ubiquitous.  While both Dan and myself have been working virtually long before it was cool, institutions for learning, from grade-school through university, and a great many companies that are not tech-companies, are getting a crash-course.  Dan shares that the technology is not new – companies like Google, Facebook, and others have been using “vc” for “visual chat” a long time.  And the benefits for time, efficiency, and effectiveness which, while known by some, will be more readily embraced by all – mostly because they discover how it can be an accelerant for achieving objectives. One of the biggest transformations will come in the field of education.  For decades, traditional institutes of higher learning have looked down upon those that delivered education telephonically – only to embrace it enthusiastically when faced with a crisis.  The challenge is to maintain quality, as if the quality of education delivered telephonically is inherently inferior.  But what if the quality of delivering education telephonically is actually superior – once its learned how to make it superior.    This leads us to a discussion on the value of face-to-face.  Humans are social beings and we need that close interaction.  This is not only necessary to make the learning experience more enjoyable and “sticky”, but also the primary driver for why people go to conferences.  The sessions are (usually) very good, but it’s the interaction with peers in a casual setting where the real value of attending is gained. The conversation continues with deep dives into the various ways companies are discovering there is a “silver lining” during this pandemic cloud; the various ways they are realizing how they can improve the performance in their operations, increase health and safety, accelerate the achievement of strategic initiatives, reduce operating costs (such as the overhead of real estate and travel) and so on. Come take a listen, open your mind, and start using your imagination as to what can be, what good can come from all this bad. Host: Joseph Paris, Founder of the;  XONITEK Group of Companies,  Operational Excellence Society & Readiness Institute Guest: Daniel P. Bumblauskas, Ph.D. Daniel P. Bumblauskas, Ph.D., is an Associate Professor of Management and the Hamilton / ESP International Fellow of Supply Chain and Logistics Management at the University of Northern Iowa; a visiting professor at the University of Washington; and holds a courtesy appointment at the University of Missouri where he previously held a faculty appointment.  Dan conducts research, teaches, and consults on various areas related to operational excellence and business development.  He has published over 45 peer reviewed journal articles and conference proceedings, including publications in journals such; as Expert Systems with Applications, IEEE Transactions on Industry Applications and Business Process Management.  He earned a B.S. in Industrial Engineering and Economics from Iowa State University, a master of liberal arts in general management from Harvard University, and received both his M.S. and Ph.D in Industrial Engineering from Iowa State University.  Prior to his faculty appointments, he was employed in industry by ABB Incorporated and Sears Holding Corporation.  He currently serves as a Vice President of PFC Services, Inc., a consulting firm based in Marietta, Georgia. Family: wife, Kendra, and four children (Addilyn, Taryn, Grayson and Weston; ages 11, 10, 7, and 5 respectively) Hobbies: golfing, ice hockey (Waterloo Youth Hockey Association – WYHA, USA Hockey 6U/8U Level 1 coach) LinkedIn: https://www.linkedin.com/in/dan-bumblauskas/ Company details: University of Northern Iowa https://uni.edu/   Headquarters; Cedar Falls, Iowa Founded in 1876 Company type; Higher Education Company size; ~ 639 academic staff PFC Services https://pfcservicesinc.com/ Headquarters; Marietta, Georgia Founded in 2000 Company type; Management Consulting Specialties; Industrial Engineering, Operations & Supply Chain Management, General Management

In this episode, we interview Renee Ahel, who is a Lead AI Expert at Cirtuo and a freelance data scientist in Croatia. He is dealing with Machine Learning since 2003, and recently he is working on Tree-based methods, with which he solves procurement problems. He is also dealing with Expert systems, you will hear why. His motto is: You should choose the most efficient tool for the problem you have, regardless of whether it is in fashion or not. AI applications in procurement: https://sievo.com/resources/ai-in-procurement Expert systems https://en.wikipedia.org/wiki/Expert_system Kraljic matrix https://www.forbes.com/sites/jwebb/2017/02/28/what-is-the-kraljic-matrix/#2d004b38675f Bayes network powered PCOS (polycystic ovary syndrome) diagnostics - implemented by Croatian company Vingd for the Berlin startup Clue: https://techcrunch.com/2019/09/04/period-app-clue-hopes-to-predict-if-you-have-pcos/ Renee Ahel on LinkedIn: https://www.linkedin.com/in/reneeahel/ Data Science Croatia: https://www.meetup.com/DataScienceCroatia/

Today we’re joined by return guest Xavier Amatriain, Co-founder and CTO of Curai. In our conversation, we discuss Curai’s goal of providing the world’s best primary care to patients via their smartphone, and how ML & AI will bring down costs healthcare accessible and scaleable.  The shortcomings of traditional primary care, and how Curai fills that role,  Some of the unique challenges his team faces in applying this use case in the healthcare space.  Their use of expert systems, how they develop and train their models with synthetic data through noise injection How NLP projects like BERT, Transformer, and GPT-2 fit into what Curai is building.  Check out the complete show notes page at twimlai.com/talk/316

Professor Maurice Pagnucco is the Deputy Dean of Education, and the Head of the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney Australia. A talk which turned into a Brief History of Machine Learning & using Prof Pagnucco's wide & deep knowledge of the field - I asked him a couple of ML questions covering topics including Expert Systems, Bayesian Methods, Causal Inference, the Millennium Prize and the future of ML.

Machine learning promises to change many industries, but with these changes come dangerous new risks. Join Jim and Wes as they explore some of the surprising ways bias can creep in and the serious consequences of ignoring these problems.

Science gives merit! It's not as easy as you think, manifestation takes time and effort.Every thought you have sends out into the world a very distinctive frequency. The frequency of your thought becomes a kind of magnet that tends to attract similar frequencies that match that thought. This frequency is known as a wave of energy. It's a vibrational energy that draws to it similar energies that match its frequency.Want to know how to optimise your brain?FOLLOW ME ONLINE HEREInstagram: www.instagram.com/_thediamond...Facebook: www.facebook.com/neuroathleti...Website: www.thediamondboss.comWebsite 2: www.neuroathletics.com.au______REFERENCES:Ultsch, A. (1991a), The Integration of Neuronal Networks with Expert Systems, Proceedings Workshop on Industrial Applications of Neural Networks, Ascona, Vol III, 3–7.

The impacts of Artificial Intelligence and Machine Learning, and related technologies of Expert Systems and Neural Networks, on the geospatial industry and society (on our 12th Anniversary)

Neota Logic applications deliver utilizes their advanced Artificial Intelligence platform, consulting knowledge, and custom expert systems to help businesses grow and develop in a smart, strategic manner. Neota Logic applications provides utilize rules, reasoning, resolution management & document automation, among other technology. Matthew Gillis, President of Neota Logic, explains how their system empowers non-programmers to quickly and easily create & deploy rules-based applications. These easy-to-maintain apps deliver improve business process, reduce risk and ensure compliance. Neota Logic applications generally focus on 3 types; Analysis & Advice, Intake Assessment and Document Automation. Intake Assessment guide users through complex fact-collecting & subsequent analysis. To learn more about these exciting applications listen to the podcast and make sure to subscribe, share and review.

Steven bought his first stock at the age of 14 and the rest was history. He lives in the small working class town of Russellville, Arkansas with his wife and 2 kids. Steven has a background in Economics and Finance and worked for one of the largest investment firms in the U.S for 6 years. He has established The Trader's Plan as a distinctively unique ETF & Growth stock newsletter that focuses on trends in the market indices. Being a former Financial Advisor at a large broker dealer (and watching portfolios crash in 2008) forced Steven to abandon "buy & hold" and create a simple ETF strategy that has averaged 21.49% per year since 2007 that anyone can follow. Key Takeaways: [1:35] How Jason got started in real estate investing [5:15] How Jason got started investing in real estate markets he didn't live in [7:50] Whether Jason's willing to look at distressed properties and why the USA is the best real estate market in the world [10:50] The mistakes Jason sees investors making when they get started [15:10] One of Jason's favorite deals [17:10] Books Jason has read that are helpful, and how to educate yourself Website: www.thetradersplan.com

Sramana Mitra is the founder of One Million by One Million (IM/IM), the world's first and only global virtual incubator/accelerator with a goal to help a million entrepreneurs globally to reach a million dollars in annual revenue, building a $1 trillion in global GDP and creating 10 million jobs. Sramana founded three companies: Dais (off-shore software services), Intarka (sales Lead generation and qualification Software; VC: NEA) and Uuma (online personalized store for selling clothes using Expert Systems software; VC: Redwood). Two of these were acquired, while the third received an acquisition offer from Ralph Lauren. Sramana has consulted with over 80 companies - everybody from SAP to Best Buy. Sramana has authored Entrepreneur Journeys, a series of 12 books focused on demystifying entrepreneurship. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/theindustryshow/support

Why are people so fired up about a computer winning yet another game? Whether it's checkers, chess, Jeopardy, or the ancient Chinese game of Go, we get excited about the potential for more when we see computers beat humans. But then nothing "big" -- in terms of generalized artificial intelligence -- seems to happen after that burst of excitement. Now, with the excitement (and other emotions) around Google DeepMind's "AlphaGo" using machine learning and other techniques to beat one of the world's top Go players, Lee Sodol, in Korea ... it's like the dream of the 1990s (and 1980s, and 1970s, and 1960s) is alive in Seoul right now. Is this time different? How do we know? a16z's head of research and deal team Frank Chen and board partner Steven Sinofsky -- who both suffered through the last “AI winter” -- share how everything old is new again; the triumph of data over algorithms; and the evergreen battle between purist vs. "practical" approaches. Ultimately, it's about how innovation in general plays out, at a scale both grand (cycles and gestation periods) and mundane (sometimes, the only way to make a product work is to hack together the old, the new, and everything in between). NOTE: The Super Mario World video referenced in this podcast is at https://www.youtube.com/watch?v=qv6UVOQ0F44

In this episode we were joined by Simon Murdoch, Founder of early stage European technology VC, Episode 1. Simon discusses his background and experience that led him to becoming an entrepreneur and later an investor at Episode1, what he brings to the companies he works with, and insights into what he looks for in founders. Simon sold his first company BookPages to Amazon in 1998 after which he reported to Jeff Bezos as VP Europe of Amazon.com. In early 2000, Simon founded and ran Chase Episode 1, an early stage European technology VC fund backed by JP Morgan Chase. The fund made over 3x return after all fees and carry. Chase Episode 1 included investments in BetFair (IPO 2010) and ScanSafe (sold to Cisco 2009). After the fund Simon became a full-time angel investor. His angel portfolio includes/included investments in Shazam, Zoopla (IPO 2014), LoveFilm (sold to Amazon 2011), Shutl (sold to eBay 2013), and Natural Motion (sold to Zynga 2014). In addition, from 2010 to 2012, Simon worked at Octopus Ventures in portfolio development. Simon has a BA in Physics from Cambridge and a PhD in Computer Science and Expert Systems.

We consider a block-stacking program, which can answer questions about its own behavior, and then identify an animal given a list of its characteristics. Finally, we discuss how to extract knowledge from an expert, using the example of bagging groceries.

Knowledge management helps organizations remain vital while expert systems make key knowledge available to a wider audience.

IBM has recently announced new integrated optimized systems. Migrate existing supported applications into these systems with ease. The migration expertise built into these systems involves understanding the design of the existing application, encapsulating its configuration and data into a package, and then importing that package into the environment. You are not required to separately buy, install, and configure a separate migration tool, saving you time and increasing the quality of your deployed applications. Steve Weaver and Robbie Minshall, speakers.

The time has come for a new class of systems: systems with integrated expertise that combine the flexibility of a general purpose system, the elasticity of cloud and the simplicity of an appliance, namely IBM's Expert Integrated Systems. Randy Newell and Steve Weaver discuss the application development solutions that complement Expert Integrated Systems, including IBM's collaborative application lifecycle management solution to help you deliver quality software and services faster through better team collaboration, automation and governance across platforms.

Callum McHarrie and Gavin McQuistin complete our General Purpose Packages Podcasts. Their Podcast contains information about Graphics, Desktop Publishing, Presentation and Multimedia and Expert Systems. Copyright info: "This Podcast uses the following sound files from Freesound (http://www.freesound.org): # 21159_djgriffin_FAT_BREAK_HATS_ACID by dj griffin"

Fri, 1 Jan 1988 12:00:00 +0100 http://epub.ub.uni-muenchen.de/4917/ http://epub.ub.uni-muenchen.de/4917/1/4917.pdf Philipps, Lothar Philipps, Lothar (1988): A Dichotomic Database of Legal Topoi. In: Fiedler, Herbert (Hrsg.), Expert Systems in Law: Impacts on legal theory and computer law. Bd. 4, Neue Methoden im Recht. Attempto-Verl.: Tübingen, pp. 43-46. Jura

Carneros explains Expert Systems and why CCP might have wanted them. Support this podcast: https://anchor.fm/talking-in-stations/supportSupport this podcast at — https://redcircle.com/talking-in-stations/donations