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

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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