GenAI podcast

In this episode of the GenAI podcast, Dale and Alan discuss the current state of AI, focusing on data limitations, the role of AI agents, and the implications of blockchain in project management. They explore the potential of AI in contract management, the future of job markets, and how AI could impact supply and demand dynamics. The conversation also touches on the pace of technological change and the challenges of adopting new technologies responsibly.TakeawaysThe podcast celebrates its 30th episode, marking a milestone.Concerns about diminishing returns in AI model training are prevalent.Model collapse is not a significant issue due to alternative data sources.AI agents currently lack the ability to make intuitive leaps like humans.Alignment in AI training is crucial for effective decision-making.Blockchain may not be the solution for contract management issues.AI could outperform human contract managers in many scenarios.The pace of change in AI adoption is controlled by human decisions.Increased AI capabilities could disrupt traditional job markets.The impact of AI on supply and demand dynamics is complex.Chapters00:00 Understanding AI Agents10:09 The Challenge of AI Alignment11:21 Blockchain and Project Management13:27 AI Agents vs. Blockchain Contracts15:41 The Future of Work and AI18:29 The Economics of AI in the Workforce23:34 The Art of Planning vs. Scheduling25:24 Teaching Planning: Breaking the Gatekeeping Barrier29:52 The Role of Technology in Planning31:03 AI and Power Generation: A New Era35:01 Market Dynamics and Future Predictions

In this episode of the GenAI Podcast, Dale and Alan discuss the latest developments in AI, including the release of GPT-5, the implications of open-source AI models, and the importance of security in AI development. They explore the concept of AI psychosis, the cognitive effects of interacting with AI, and the future of robotics in project delivery. The conversation also delves into the legal implications of AI, the role of humans in an AI-driven world, and philosophical considerations surrounding AI and reality.TakeawaysAI agents are becoming increasingly popular, with many startups emerging.Security risks in open-source AI models are a significant concern.The importance of secure design in AI development is often overlooked.Legal implications of AI usage are complex and multifaceted.AI psychosis is a growing phenomenon affecting people's perceptions of reality.Cognitive load is impacted by how we interact with AI.Robotics is set to revolutionize project delivery in construction.Humans will still play a crucial role in an AI-driven world.The future of AI and robotics presents both opportunities and challenges.Philosophical questions about AI and reality continue to evolve.Chapters00:00 Welcome and Reflections on Breaks02:32 The Rise of AI Agents03:04 Exploring GPT-5 and Its Reception04:38 Open Source AI Models and Security Risks07:39 The Importance of Security in AI Development09:05 Nationalism and Control in AI10:37 The Complexity of AI Regulation11:20 AI Psychosis: The Human-AI Relationship17:04 Cognitive Effects of AI Interaction21:15 Current News and Developments in AI23:15 Gossip and Drama in the Tech World24:08 The Rise of Robotics in Sports and Construction24:55 Advancements in Robotics and AI Integration31:04 The Future of Work: Human Roles in an Automated World36:58 The Philosophical Implications of AI and Robotics46:12 Embracing Technology for Positive Change

In this episode of the Gen AI podcast, the hosts discuss various topics related to AI, project management, and the evolving role of technology in the workplace. They share personal anecdotes, insights from recent events, and explore how AI is being integrated into organizational structures. The conversation highlights the importance of upskilling and adapting to new technologies, as well as the potential emotional and social implications of AI in the workforce. The episode concludes with a discussion on recent news in the AI space and the future of work.TakeawaysAI is becoming a critical team member in organizations.Project intelligence requires quick access to data and insights.Automation can significantly reduce the workload of employees.The perception of AI is shifting towards it being a collaborative partner.Upskilling is essential for adapting to AI technologies in the workplace.AI can enhance emotional intelligence in interactions.The future of work will involve more automation and AI integration.Education systems need to adapt to prepare students for an AI-driven world.The role of personal assistants is changing due to AI advancements.Curiosity about AI should be balanced with caution. Chapters00:00 Welcome Back and Personal Updates03:39 Project Intelligence Roundtable Insights06:40 AI Roles in Organizations09:05 Understanding Schedule Integrity11:40 Book Insights and Project Acceleration15:12 AI Day Highlights and Team Dynamics20:45 The Future of Knowledge Work and AI24:33 Education and Upskilling in AI26:44 Harnessing Technology for Real-World Solutions29:47 The Future of Work and Social Skills31:39 Evolving Skill Sets in a Changing Landscape34:26 Human Interaction vs. AI in the Workplace38:26 Recent Developments in AI and Quantum Computing

In this episode of the GenAI podcast, Dale and Alan discuss the evolution of AI in project controls, focusing on the Model Context Protocol (MCP) and agent-to-agent communication. They explore the barriers to technology adoption, the importance of keeping up with rapid advancements, and the potential for AI to disrupt traditional industries. The conversation also touches on the rise of the gig economy and the implications of AI on social interactions and project management. Audience questions further enrich the discussion, highlighting the challenges and opportunities in the current landscape.TakeawaysThe Model Context Protocol (MCP) is crucial for AI agents.User experience (UX) is a significant barrier to AI adoption.Keeping up with technology is increasingly challenging.Organizational change is slower than innovation.AI is facilitating the rise of the gig economy.Disruption in traditional industries is likely to come from outside.AI agents can enhance social interactions.Cost estimating and legal fields are ripe for disruption.The future of project management is uncertain due to rapid changes.Education and leadership are key to technology adoption.Chapters01:25 Exploring AI and Project Controls05:14 Understanding Agent Protocols09:03 Adoption Barriers in AI Technology10:30 The Future of Work and AI Agents14:38 Organizational Change and Innovation19:05 The Rise of One-Person Companies22:56 AI's Impact on Society and Work26:45 The Role of Agents in Project Management30:33 Disruption in Cost Estimation and Legal Fields37:29 Audience Questions and Insights

In this episode of the Gen AI podcast, Dale and Greg discuss the evolving landscape of AI in project management, touching on themes of nationalism in AI development, current applications of AI, and the importance of integrated data sources. They explore the challenges of project reporting, the future of project management with AI, and the dynamics of workforce changes due to technology. The conversation emphasizes the need for experimentation in innovation and the impact of AI on modern economies, concluding with a reflection on the balance between technology and human interaction.Takeaways🌍 The industry is increasingly ready to adopt automation AI.🌍 Nationalism is influencing AI development and infrastructure.🌍 AI can significantly improve project management efficiency.🌍 Integrated data sources are crucial for project success.🌍 Project controls must evolve beyond mere reporting.🌍 AI can automate repetitive tasks in project management.🌍 Experimentation is key to innovation in organizations.🌍 The future of work will involve more AI applications.🌍 AI will change the dynamics of workforce roles.🌍 Technology adoption is becoming a necessity for project success.Chapters00:00 Introduction and Global AI Trends06:31 Nationalism in AI Development08:55 Current Applications of AI in Project Management18:35 The Future of Project Management and AI Integration27:47 Creating Organizational Clarity30:17 The Importance of Experimentation33:15 Innovation vs. Execution36:25 The Role of Technology in Business40:34 AI and the Future of Work43:32 Balancing Technology and Human Interaction46:21 Political Choices in Technological Advancement

In this episode of the Gen.ai podcast, the hosts delve into various themes surrounding AI, software development, and project management. They discuss the concept of 'vibe coding,' where developers may rely too heavily on AI, leading to potential laziness and quality issues. The conversation shifts to the dichotomy of AI usage, emphasizing the need for a balanced perspective rather than an all-or-nothing approach. The hosts advocate for open-mindedness in discussions about technology, highlighting the importance of strong opinions that are weakly held. They explore the differences between large language models and emerging large concept models, as well as the role of governments in AI development. The episode concludes with a focus on the future of AI in project controls, emphasizing the potential for prescriptive models and the opportunities that lie ahead.TakeawaysVibe coding can lead to laziness in software development.Strong opinions should be held weakly to allow for change.The future of projects is uncertain and cannot be predicted linearly.AI is a tool that can enhance productivity if used correctly.Governments are lagging behind in AI investment compared to private sectors.The global nature of AI innovation transcends national boundaries.Large concept models may represent the next breakthrough in AI.Exploring multiple scenarios in project management can lead to better outcomes.The act of data selection in analysis can manipulate results.Unknowns in projects present opportunities for innovation. Chapters01:24 The Concept of Vibe Coding08:40 AI: Dichotomies and Misconceptions16:01 Large Concept Models vs. Large Language Models21:10 The Future of AI Agents22:51 Geopolitical Competition in AI29:22 Project Controls and AI Integration46:32 The Future of Work with AI

In this episode, Dale and Alan discuss the rapid evolution of AI models, the competitive landscape, and the implications of one-person companies in the tech industry. They explore the challenges and opportunities for entrepreneurs, the importance of understanding market demand, and the potential social consequences of a rise in solo entrepreneurship. The conversation also touches on the role of leadership in the age of AI and the need for a balance between technology and human involvement in governance. In this conversation, Dale and Alan explore the intersection of AI and various sectors, including politics, government efficiency, and the future of work. They discuss the implications of AI in elections, the challenges of remote work, and the advancements in quantum computing. The dialogue also addresses common misconceptions about AI and the ethical considerations surrounding its use in governance.Takeaways The AI market is becoming increasingly saturated and competitive. Understanding how to monetize an idea is crucial before quitting a job. The rise of one-person companies could lead to social challenges. Most entrepreneurs face significant risks and financial challenges. AI can enhance productivity, but it doesn't eliminate the need for human leadership. The demand for unique ideas is high, but so is the competition. Social media influences perceptions of entrepreneurship and success. Leadership qualities are still essential, even in a tech-driven world. The future of work will involve more roles, but also more competition. A balance between technology and human connection is necessary for societal well-being. AI can significantly impact political campaigns and elections. Consent is crucial when discussing AI's influence on decision-making. Government efficiency is a persistent issue that AI could help address. Ethical considerations are paramount in the deployment of AI in governance. Remote work has become a standard expectation for many roles. Hybrid work models may be the future of employment. Grok represents a significant advancement in AI technology. Quantum computing has the potential to revolutionize various industries. Misconceptions about AI can lead to unfair assessments of its capabilities. Engagement and feedback from listeners are essential for content improvement.Chapters00:00 Introduction and Podcast Dynamics00:58 AI Model Releases and Market Confusion02:55 The Competitive Landscape of AI Models05:48 Open Source Models and Hosting Solutions07:47 Advice for Entrepreneurs in AI09:46 The Rise of One-Person Companies13:05 Social Implications of One-Person Companies14:58 The Future of Work and AI's Role18:50 Leadership in the Age of AI22:51 The Role of Technology in Governance28:04 Navigating AI in Politics29:30 The Role of AI in Elections30:36 Government Efficiency and AI31:40 Ethics and AI in Governance33:08 Remote Work vs. Office Culture35:32 The Future of Work: Hybrid Models39:12 Exploring Grok and AI Developments43:50 Quantum Computing: The Next Frontier49:08 Debunking AI Myths and Misconceptions

In this episode, the hosts discuss the rapid commoditization of AI technologies, the implications for businesses, and the emergence of agentic AI. They explore the stages of technology commoditization, the differences between AI agents and agentic AI, and the importance of understanding one's core competencies in the face of evolving AI capabilities. The conversation also touches on practical tools and productivity hacks for leveraging AI effectively. Takeaways 🍕 AI is moving towards commoditization faster than any technology before. 🍕Understanding the stages of technology development is crucial for businesses. 🍕Agentic AI represents a new frontier in AI capabilities. 🍕Companies must focus on their core competencies and not get distracted by AI hype. 🍕The commoditization of AI will lead to increased competition and innovation. 🍕Businesses should consider the make-or-buy decision regarding AI solutions. 🍕Not all companies need to build their own AI; sometimes it's better to buy. 🍕The importance of modular experimentation with AI technologies. 🍕Productivity tools like Operator and Claude can enhance efficiency. 🍕In-person discussions can lead to richer conversations and insights. Chapters 00:00 Introduction and Context Setting 10:58 Understanding Commoditization in Technology 16:19 The Rise of Agentic AI 34:56 Implications for Businesses in AI Adoption

In this episode of the GenAI podcast, Dale and Alan discuss the recent emergence of DeepSeek, a Chinese AI company that has made headlines for its innovative models and the misinformation surrounding them. They delve into the specifics of DeepSeek's models, including V3 and R1, and explore the implications of open-source technology in AI. The conversation also touches on the impact of misinformation on the market, the significance of reinforcement learning, and the myths surrounding artificial general intelligence (AGI). Throughout the discussion, they emphasize the importance of understanding the technology and encourage listeners to engage with AI tools directly. Takeaways 👀 DeepSeek is a Chinese hedge fund's research team focused on generative AI. 👀 The company has released multiple models, including V3 and R1, which are significant in the AI landscape. 👀 Misinformation about DeepSeek's capabilities has led to market fluctuations. 👀 Open-source technology allows for greater collaboration and innovation in AI. 👀 The distillation process helps create smaller, more efficient models from larger ones. 👀 Reinforcement learning is being used in new ways to enhance AI reasoning capabilities. 👀 The efficiency of AI models can lead to market growth and new applications. 👀 AGI remains a nebulous concept, and current models are not true AGI. 👀 Engagement with AI tools is crucial for understanding their capabilities and limitations. 👀 The conversation around AI is drawing more public interest and awareness. DeepSeek on HuggingFace: https://huggingface.co/deepseek-ai/DeepSeek-R1 Chapters 00:00 Breaking News: The Emergence of DeepSeek 01:36 Understanding DeepSeek: The Basics 06:29 DeepSeek's Models: V3 and R1 Explained 12:46 Misinformation and Market Impact 15:24 Open Source: What Does It Mean? 20:19 The Distillation Process and Model Performance 27:38 Reinforcement Learning: A New Approach in AI 28:26 Human-Centric Model Training 29:50 Reinforcement Learning Breakthroughs 31:45 DeepMind's Influence on AI Development 33:50 Efficiency Gains in AI Training 35:51 The Future of AI Agents 37:48 Concerns Over Data Privacy 39:36 Debunking AGI Myths 44:02 The Road to True AGI 46:21 The Emergence of Zero-Person Companies 51:19 Navigating the Landscape of AI Content 54:42 Final Thoughts on AI's Future Don’t Forget to Share & Subscribe! Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Alan kick off Season Two by discussing the recent 500 billion dollar investment in AI announced in the US and its implications for data centers and technology. They explore the role of government in these investments, the future of major players like Apple and Oracle, and the importance of efficiency metrics in AI. The conversation also touches on productivity tools and innovations that are emerging in the AI landscape, as well as the potential shift from point solutions to more integrated agentic behaviors in technology. Takeaways 🧌 The 500 billion dollar investment is primarily aimed at building data centers and small modular reactors. 🧌 NVIDIA is a major beneficiary of the current AI investment landscape. 🧌 Government involvement in AI investments may be more about propaganda than actual funding. 🧌Apple has a strong machine learning group but tends to be cautious in its market approach. 🧌Efficiency in AI is driven by both hardware advancements and algorithm improvements. 🧌The concept of tokens per dollar per watt is crucial for understanding AI efficiency. 🧌Self-improvement in AI models is a key area of research and development. 🧌Productivity tools like Napkin and Devon are changing how we approach tasks and projects. 🧌The future of AI may see a shift towards integrated solutions rather than point solutions. 🧌The rapid evolution of technology means that staying informed is essential for professionals. Chapters 00:00 Welcome to Season Two 03:02 The 500 Billion Dollar Announcement 11:05 The Role of Government in AI Investments 13:18 The Future of AI and Data Centers 21:14 Understanding Tokens and Efficiency in AI 27:53 The Potential of Self-Improving AI Models 33:44 Emerging Tools and Productivity Hacks 40:54 The Future of Point Solutions in AI Don’t Forget to Share & Subscribe! Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this Christmas special episode of the Gen AI podcast, the hosts reflect on the significant developments in AI over the past year, discussing trends, predictions, and the impact of AI agents and quantum computing on various industries. They explore the evolution of project controls and the future of work, emphasizing the need to embrace change and uncertainty as opportunities for growth. Takeaways 🤶 2023 has been a year of clarity in AI. 🤶 The emergence of AI agents will redefine job roles. 🤶 Quantum computing presents both opportunities and challenges. 🤶 The demand for data centers is increasing rapidly. 🤶 AI will change the way project controls are executed. 🤶 Embracing uncertainty can lead to significant opportunities. 🤶 The future of work will involve more AI integration. 🤶 Companies are beginning to see AI as a cost-saving measure. 🤶 The evolution of technology will drive societal change. 🤶 The importance of adapting to new technologies is crucial. Chapters 00:00 Christmas Special: Reflecting on the Journey 10:29 The Rise of Custom GPTs and AI Applications 21:30 The Intersection of AI and Robotics 28:15 Looking Ahead: The Future of AI and Society 34:15 The Shift in Project Controls 42:50 The Commoditization of Project Controls 48:56 The Mentality of Change and Opportunity Don’t Forget to Share & Subscribe! Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

🎙️ Welcome to Episode 19 of the Gen AI Podcast! Strap in, folks, because Dale and Greg are back from their whirlwind tour of global conferences, and they’re serving up insights hotter than your in-flight meal (assuming they didn’t run out of chicken). This week, we dive deep into the wild world of AI adoption in project management, the construction industry’s so-called productivity crisis, and, of course, a healthy dose of existential musing about human emotion and perception. 00:00 – Intro Dale and Greg catch up after their globetrotting adventures and reflect on the joys and perils of business travel. (Spoiler: Being home for Christmas wins every time.) 05:10 – Automation vs. Generation Greg breaks down AI for the everyday project professional: is it about automation or creation? Dale tries to simplify it with math, but Greg takes it a step deeper (cue existential dichotomy). 11:50 – Planes, Pilots, and AI Pals Would you board a pilotless plane? Dale’s audience poll reveals trust issues with AI—even though it flies better than your average junior planner. 16:30 – Perception in Project Management Whoever controls the narrative controls the room. Dale and Greg unpack why perception shapes project success more than hard data ever will. 24:00 – Misconceptions About the Construction Industry Is construction really broken? Greg debunks two big myths: "Most projects fail." "Construction productivity hasn’t improved in decades." (Also featuring chocolate and death—stay tuned for the correlation!) 33:00 – Selling Project Controls: Safety and Comfort Greg explains how great project controls create emotional safety, comfort, and a dash of excitement for stakeholders. And no, it’s not about the size of your PMO team; it’s about the value of your insights. 40:20 – Addictive AI and Virtual Companions Consumer AI is getting personal—sometimes a little too personal. Greg explores how addictive design might shape the next wave of AI interactions (including virtual "companions"). 49:10 – The Year in Review Dale and Greg reflect on their first year of podcasting, the experiment of zero guests, and their plans to close the year strong with Episode 20. Will they finally get all four hosts together? (Probably not.) 51:30 – Greg’s Closing Thoughts A heartfelt thank-you to listeners for joining this pub chat with mics. Cheers to more debates, discussions, and maybe even some guests in the new year! Listener Challenge Think we’re wrong? Tell us! Dale and Greg love a good debate—especially if it involves whiskey and arguments about project controls. Don’t Forget to Share & Subscribe! We’re wrapping up the year soon with our 20th episode—help us go out with a bang (or at least more downloads than Greg’s frequent flyer miles). Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Alan reflect on the journey of the GenAI podcast and the progress of AI and tech. They discuss the current status of the AI market and the jitteriness of investors. Alan shares his opinion on the unrealistic expectations and impatience in the market. They also explore the lag in upskilling and adoption of AI, comparing it to the early days of the internet. They discuss the future delivery of AI as a product and the potential decline of software as a service (SaaS) in favor of AI interfaces that reduce friction. The conversation explores the future of user interfaces and the potential impact of AI on software as a service (SaaS) products. The speakers discuss the increasing importance of email and the desire for more efficient interfaces. They consider the possibility of moving away from visual interfaces and relying more on voice interactions. They also discuss the potential for AI-powered assistants to replace traditional user interfaces in SaaS products, using Procore as an example. The conversation highlights the importance of time and patience in the development and adoption of AI technology. Takeaways The AI market is experiencing jitteriness and unrealistic expectations from investors, leading to volatile stock prices. The adoption of AI is a long process, similar to the early days of the internet, and requires patience and time for upskilling. Software as a service (SaaS) may decline as AI interfaces that reduce friction become more prevalent. AI will be delivered as a product through interfaces that allow users to interact with AI systems using natural language or voice commands. Email continues to be important and there is a desire for more efficient interfaces. Voice interactions may become more prevalent, reducing the need for visual interfaces. AI-powered assistants have the potential to replace traditional user interfaces in SaaS products. The development and adoption of AI technology require time and patience. Chapters 00:00 Introduction and Reflection on the Podcast Journey 02:13 The Jitteriness of the AI Market 04:33 The Lag in Upskilling and Adoption of AI 09:14 The Demise of Software as a Service (SaaS) 12:04 The Future of AI Delivery: Voice Commands 25:11 The Importance of Email and Desire for Efficient Interfaces 28:35 Redefining Software as a Service 33:22 The Future of User Interfaces 35:18 Adoption of AI and the Need for Patience Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Alan discuss the application of AI in engineering design. They explore the idea of a roadmap for AI in design, from AI-aided design to autonomous agents creating designs. They also discuss the need for healthy data for AI to consume in order to produce accurate and reliable designs. The conversation touches on the role of humans in the design process and the importance of responsible engineers. They also speculate on the potential future of AI in engineering design, including AI agents controlling robots on construction sites. In this conversation, Alan and Dale discuss the use of blockchain technology in design and the potential threats it poses. They also explore the concept of predetermined outcomes and the role of AI in the design process. They discuss the idea of AI replacing human jobs, particularly in project controls, and the need for humans to find new roles and add value. They emphasize the importance of critical thinking and curiosity in embracing AI and encourage listeners to share their perspectives and challenge others in a respectful manner. Takeaways 🍣 AI is being taken seriously by governing bodies in engineering, with organizations and associations focusing on AI in design. 🍣 A roadmap for AI in design could involve transitioning from AI-aided design to autonomous agents creating designs. 🍣 Healthy data is crucial for AI to produce accurate and reliable designs. 🍣 The role of humans, particularly responsible engineers, will still be important in the design process. 🍣 The future of AI in engineering design could involve AI agents controlling robots on construction sites. The use of blockchain technology in design raises concerns about accessibility and security. 🍣 AI can assist in predicting and optimizing outcomes in the design process. 🍣 Humans play a crucial role in setting goals and determining the intent of AI optimization. 🍣 AI has the potential to replace repetitive and mundane tasks in project controls, allowing professionals to focus on value-added decision-making. 🍣 Embracing AI requires critical thinking, curiosity, and a willingness to challenge existing beliefs and practices. 🍣 Spreading awareness and engaging in discussions about AI can help drive change and adoption in the workplace. Chapters 02:08 The Importance of AI in Engineering Design 04:53 The Need for Healthy Data in AI-Assisted Design 07:55 The Future of AI in Engineering Design: AI Agents and Robotics 15:40 AI in the Delivery Phase 21:45 The Role of Responsibility in AI-Designed Projects 23:31 Blockchain Technology in Design 26:28 AI's Role in the Design Process 28:08 Predetermined Outcomes 30:37 AI as a Companion in Professional Roles 32:30 Embracing AI and Spreading Awareness Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale, Greg, and Alan discuss the importance of defining terms and understanding terminology in the context of AI. They emphasize the need for clear and simple definitions that are exclusionary and quantifiable. They also explore the challenges of defining subjective terms like 'good AI' and the importance of critical thinking and seeking diverse sources of information. The conversation highlights the need to adapt and diversify skills in the face of AI's impact on various industries and professions. Takeaways 🍣 Clear and simple definitions are crucial for effective communication and understanding in the field of AI. 🍣 Subjective terms like 'good AI' require context and agreement among stakeholders. 🍣 Critical thinking and seeking diverse sources of information are essential for forming well-informed opinions about AI. 🍣 Adapting and diversifying skills is important to stay ahead in the changing landscape of AI and its impact on industries and professions. Chapters 01:29 Toying with Character AI and Feedback on Governance as a Service 06:38 The Ambiguity of Definitions and Opinions on AI 09:33 The Importance of Critical Thinking and Seeking Diverse Sources 18:13 Preparing for the Potential Impact of AI on Careers and Industries 29:48 The Uncertainty of Predicting the Future of AI 39:12 Diversifying Sources of Information and Adapting to Change Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Greg discuss the concept of governance as a service (GAAS) and its potential impact on the industry. They explore the automation, predictive AI, and generative AI features of Nodes and Links and other tools, highlighting the benefits of these tools in simplifying processes, improving risk assessment, and enhancing productivity. They also touch on the challenges of defining and measuring culture in the context of AI. Overall, the conversation emphasizes the importance of specificity and tailoring AI solutions to meet the unique needs of different industries and organizations. Takeaways 🥯 Governance As A Service (GAAS) is an emerging concept that aims to automate and streamline reporting, analytics, and decision-making processes in organizations. 🥯 Nodes and Links, a project management platform, offers automation, predictive AI, and generative AI features to simplify processes, improve risk assessment, and enhance productivity. 🥯 Defining and measuring culture in the context of AI is a complex challenge that requires considering the decisions people make on a day-to-day basis. 🥯 AI solutions should be tailored to meet the specific needs of different industries and organizations, taking into account the unique challenges and requirements they face. 🥯 While true general artificial intelligence (AGI) may not exist in the near future, AI technologies can still provide significant value by automating tasks, providing insights, and improving decision-making processes. Chapters 02:37 Self-Service Reporting and the Future of the Industry 10:01 Benefits of Governance as a Service (GaaS) 18:22 The Importance of Guide Rails and Speed Bumps in Governance 22:00 Challenges in Venturing into New Markets 24:50 The Risk of Fake Checks and Online Banking 28:50 Defining Governance as a Service (GaaS) 31:25 GaaS: Making Lives Easier on Projects 33:43 The Limitations of General Artificial Intelligence (AGI) 37:48 Automation in GaaS 40:44 The Difference Between GaaS and ChatGPT 43:54 The Future of AGI and Human Rights Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Alan discuss the recent AI Day from nPlan and the highlights of the event. They focus on GraphGen, a model that enables self-serve reporting in the construction and projects world. They also talk about Auto Report, which automates the process of creating lengthy reports, and Agent Barry, which can interact with different tools and generate reports. They explore the future of reporting, the role of AI in improving project outcomes, and the challenges of data sharing and controlling the narrative. They explore the idea of boundaries and silos in data sharing, highlighting the need to respect legal boundaries and competitive advantages. They also discuss the potential of peer-to-peer data networking, where access to data is shared without sharing the actual data. The conversation then shifts to the topic of GraphGen and its application in project planning and scheduling. They discuss the practicalities of using GraphGen, including the input process and the iterative nature of generating schedules. They also touch on the validation of schedules and the inclusion of different scheduling methodologies. The conversation concludes with a discussion on the limitations of data sets and the importance of feedback and improvement in AI models. Takeaways 🧻 GraphGen is a model that enables self-serve reporting in the construction and projects world. 🧻 Auto Report automates the process of creating lengthy reports, saving time for practitioners. 🧻 Agent Barry can interact with different tools and generate reports, providing a more efficient way of reporting. 🧻 The future of reporting may involve agent-to-agent communication, where reports are packets of information exchanged between agents. 🧻 AI has the potential to improve project outcomes, but controlling the narrative and data sharing remain challenges. Data sharing involves respecting legal boundaries and competitive advantages. 🧻 Peer-to-peer data networking allows for sharing access to data without sharing the actual data. 🧻 GraphGen can be used for project planning and scheduling, with an iterative process for generating schedules. 🧻 Validation of schedules is important, and feedback is crucial for improving AI models. Chapters 01:54 Enplan's AI Day: Introducing GraphGen and Auto Report 21:59 Challenges of Data Sharing in the Construction Industry 28:26 Data Sharing and Boundaries 30:00 Exploring Peer-to-Peer Data Networking 32:26 Automating Project Scheduling with GraphGen 34:11 The Practicalities of Using GraphGen 39:50 Validating and Adjusting Generated Schedules 53:57 GPT-4.0 and Hallucinations Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Alan discuss the recent partnership between Apple and OpenAI and speculate on its potential impact. They explore the idea of a virtual assistant that can perform various tasks and how it could enhance daily life. However, they struggle to find a specific use case for the construction project management industry. They also touch on the future direction of Apple and Google in the AI space and discuss their personal preferences for operating systems. In this conversation, Alan and Dale discuss the potential impact of Apple and OpenAI's collaboration on the general public, as well as the construction industry. They explore the concept of vendor lock-in and the integration of different platforms and tools. They also speculate on the future of voice-controlled devices and the role of AI assistants in improving productivity. The conversation ends with a playful discussion about planning for future podcast episodes. Takeaways 🔮 The partnership between Apple and OpenAI could lead to the development of a virtual assistant that can perform various tasks and enhance daily life. 🔮 It is unclear how this partnership will specifically impact the construction project management industry. 🔮 Apple's AI lab is likely to continue its work and may incorporate OpenAI's technology into its products. 🔮 Google has also been making advancements in AI, but it is unclear how it will respond to Apple's partnership with OpenAI. 🔮 The future direction of virtual assistants is likely to involve more proactive and automated actions. 🔮 Personal preferences for operating systems vary, but many people use a combination of different platforms depending on their needs. The collaboration between Apple and OpenAI has the potential to be a game-changer for the general public, although its specific impact on the construction industry is yet to be determined. 🔮 Vendor lock-in is a strategy employed by big tech companies like Microsoft and Apple to keep users within their ecosystems, offering a wide range of integrated tools and services. 🔮 Integration between different platforms and tools is becoming less of an issue, allowing for greater flexibility and productivity. 🔮 Voice-controlled devices and AI assistants have the potential to revolutionize the way we interact with technology and improve productivity. 🔮 Planning and speculating about future developments can be an exciting and fun part of podcasting. Chapters 07:53 Exploring the Future of AI Assistants 09:35 The Evolution of AI: From Assistants to Agents 13:12 Apple's Strategy and Next Steps 16:00 Implications for the Construction Industry 21:33 Developers' Choice of Operating Systems 23:35 The Apple-OpenAI Collaboration: A Game Changer in AI? 29:02 Vendor Lock-In: Strategies and Implications 33:33 AI in the Construction Industry: Enhancing Productivity 38:12 Seamless Integration: The Key to Efficiency 41:50 The Future of Voice Assistants: Conversational AI 45:46 Planning for the Next Episode: Crystal Ball Gazing Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

[Apologies for some echo during this episode] In this episode, Dale and Greg discuss the current state of AI and its impact on various industries, including project management. They explore the concept of the prophet era in AI, where companies are no longer questioning if AI will affect them, but rather how and when. They also touch on the debate between open source and closed source large language models (LLMs) and the role of wearables and augmented reality in project delivery. The conversation emphasizes the importance of writing down thoughts, engaging in open debate, and adopting a curious mindset to stay relevant in the evolving tech landscape. Takeaways We are currently in the prophet era of AI, where companies are no longer questioning if AI will affect them, but rather how and when. The debate between open source and closed source large language models (LLMs) continues, with the understanding that building LLMs from scratch is not feasible for most organizations. Wearables and augmented reality have the potential to enhance project delivery, but their adoption and impact will vary depending on specific use cases and industries. Writing down thoughts and engaging in open debate are valuable practices for solidifying ideas and gaining different perspectives in the evolving tech landscape. Adopting a curious mindset and asking questions about unfamiliar topics can help individuals stay relevant and informed in the face of technological advancements. Chapters 03:19 The Impact of AI on Decision Making 06:37 The Role of Large Language Models in Project Delivery 09:18 Challenges and Opportunities in AI for Project Management 12:19 The Future of Automation in Project Management 26:29 The Make-or-Buy Decision in AI and Software Companies 29:31 The Role of Domain Experience in Project Delivery 36:45 The Potential of AR in Construction Delivery Subscribe on YouTube and follow us on Spotify: 🐧 YouTube: www.youtube.com/@GenAIPodcast 🐧 Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 🐧 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork

In this episode, Dale and Alan discuss the latest release from ChatGPT, focusing on the hype around GPT-4.0 and its real-time voice generation capabilities. They explore the potential impact of voice UX and the use of different languages and domains. The conversation also touches on the fear factor associated with artificial intelligence and the concept of prompt engineering in generating high-quality responses from language models. In this conversation, Alan and Dale discuss prompt engineering and evaluation in AI models. They explore the importance of system prompts and prompt rewriting in improving the quality of AI responses. They also delve into the challenges of evaluating open-ended questions and the role of agents in decision-making. The conversation highlights the need for AI to go beyond providing information and focus on taking action. They emphasize the importance of bridging the gap between information and decision-making to achieve better outcomes. Takeaways GPT-4.0 is generating a lot of hype, especially due to its real-time voice generation capabilities. Voice UX has the potential to revolutionize user interfaces, especially for individuals with impairments. The fear factor associated with artificial intelligence often stems from the idea of superintelligence and domination. Prompt engineering is a discipline that focuses on structuring questions to language models to improve the quality of responses. Prompt engineering involves creating system prompts that instruct AI models on how to behave and respond. Prompt rewriting is a technique that involves expanding a vague question or prompt to provide more context and improve the AI's response. Evaluating the quality of AI outputs is challenging, especially for open-ended questions. Techniques like reinforcement learning with human feedback can help collect data for evaluation. AI agents that can take action and perform tasks are more valuable than those that only provide information. The speed of information is important, but the gap between information and decision-making is crucial. AI can help bridge this gap by providing rich information and simulating future outcomes. Chapters 00:00 Introduction and Hype Around GPT-4.0 03:00 Voice UX and Multilingual Capabilities 08:26 Understanding the Fear Factor in AI 27:18 Prompt Engineering and System Prompts 28:12 Prompt Rewriting for Improved Responses 29:02 Challenges in Evaluating Open-Ended Questions 35:18 The Role of AI Agents in Decision-Making 47:29 Bridging the Gap Between Information and Decision-Making Subscribe on YouTube and follow us on Spotify: YouTube: www.youtube.com/@GenAIPodcast Spotify: https://open.spotify.com/show/7vj7VdckiifSuyVc9EV0SB?si=078f3747c26e4d61 Connect with us on LinkedIn: https://www.linkedin.com/company/gen-ai-podcast #AI #ProjectManagement #Technology #Innovation #FutureOfWork