AI Won't Fix Your Bad Data. It'll Expose It

Send us Fan MailSummaryProject Flux hosts James and Yoshi speak with Mark Farmer, founder and board executive of Kars Consultancy and author of the Modernise or Die review, about how AI could reshape construction and professional services. Farmer connects AI adoption to the industry's fragmented commercial model, workforce capacity and training, data governance, and the role of professional institutions.Key TopicsFarmer reflects on Modernise or Die, reaffirming offsite and pre-manufactured construction while wishing he had given greater attention to the commercial model that determines whether firms can invest.Fragmentation, volatile demand, subcontracting and short-term survival incentives make it difficult for construction businesses to invest in technology, equipment and workforce training.AI erodes professional-services information asymmetry, putting pressure on billable-hour and resource-based fees and increasing the importance of pricing around outcomes.Firms may retain differentiation in the expert judgment and high-value insight layered on top of widely available data; clients are already using AI for preliminary estimates.Fragmented supply chains create risks around data leakage, provenance and inconsistent security standards, especially as project information flows between microbusinesses.Farmer expects AI to help disintermediate project layers and transactional friction, enabling integrated delivery and potentially cheaper, better outcomes without simply cutting margins.AI could accelerate procurement and dynamic pricing, while also improving field-based construction, not just design and surveying.Automation threatens traditional junior training tasks; firms need accelerated, structured learning, mentoring and senior-junior conversations to build judgment.AI governance should keep outputs explainable and open to challenge; professional institutions should act as custodians of competence and maintain dynamic standards.Farmer predicts AI-driven changes to business models will be well underway by 2030, and shares plans to transition from CAST toward advisory and non-executive work during 2027.Chapters00:00 Mark Farmer’s career and the origins of Modernise or Die04:11 What the review missed: construction’s commercial model08:15 AI challenges the billable hour and resource-based fees13:04 Where expertise and data can still differentiate firms17:32 Data leakage across construction’s fragmented supply chain21:03 AI disintermediation and new project business models25:07 Why tendering blocks continuous improvement28:18 AI as the enabler for construction’s capacity challenge31:01 Keeping junior professionals learning as AI automates tasks36:27 Governance, professional competence and accountable AI42:22 Farmer’s 2030 prediction and the next career chapterLinks & StuffMark’s LinkedIn: https://www.linkedin.com/in/mark-farmer-35846212Cast Consultancy: https://www.cast-consultancy.com/https://www.constructionleadershipcouncil.co.uk/wp-content/uploads/2016/10/Farmer-Review.pdf‘Mapping the AI Landscape in the Built Environment’ https://www.ube.ac.uk/whats-happening/articles/befa-report-the-built-environment-sector-needs-responsible-ai-adoption/Support the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryVerdantix industry analyst Sophie Planken-Bichler joins Project Flux hosts James and Yoshi to examine why AI capability is advancing faster than adoption in construction and the wider AEC sector. They discuss AI literacy, trust, workforce concerns, data readiness and a practical roadmap for introducing AI responsibly, from choosing a focused use case to training teams and setting governance.Key TopicsSophie describes the widening gap between fast-moving AI technology and organizations still building data foundations, governance and practical literacy.AI agents are not one-size-fits-all: reliable results depend on suitable data, clear processes and an understanding of inputs and logic.Sophie estimates that 90% of firms currently using agents lack the data and processes to realize their full potential, with unreliable outputs risking long-term trust.Construction’s AI resistance is organizational as well as technical: traditional workflows, job-replacement fears, sensitive IP and uncertainty about where to start all matter.Near-term value may come from practical document retrieval and search, which can save time without the extensive data foundations advanced predictive use cases require.James, Yoshi and Sophie discuss spreading AI literacy throughout project delivery, including ways site diaries, voice notes and images might feed project data systems.Sophie recommends a three-step starting roadmap: define a narrow, measurable problem and baseline; train teams and set guardrails; clarify data needs, ownership and governance.An AI-use amnesty can help firms learn what tools staff already use and identify shadow AI without stigmatizing experimentation.Historical project data could become valuable intellectual property, but Sophie says current data organization is often too immature to make benchmarking practical.Sophie predicts AI will be a normal expectation in AEC by 2030, alongside more flexible systems and shared knowledge repositories, while privacy and quality safeguards remain essential.Chapters00:00 Sponsor: AI-powered insights from project data02:15 The widening gap between AI innovation and adoption04:40 Why AI agents need more than impressive outputs07:14 From AI excitement to skepticism in AEC09:10 What an industry analyst sees across the market11:10 Shared priorities: skills, productivity, profitability, and quality14:13 Why organizational change and job fears slow adoption17:07 Upskilling without forcing people or leaving them behind21:24 Trust, security, and the risk of expensive AI mistakes24:16 Why AI literacy needs to reach project sites27:28 Turning site diaries and safety guidance into AI workflows30:35 A three-step, 12-month roadmap for construction AI32:20 Shadow AI amnesties and finding out what teams already use33:20 Data foundations, historical records, and the right questions38:34 Sophie’s journalism counterfactual and 2030 prediction42:25 Where to find Sophie and VerdantixLinks & StuffSophie's LinkedIn: https://www.linkedin.com/in/sophie-planken-bichler-618880196/Verdantix: https://www.verdantix.com/Free webinars and blogs (Insights): https://www.verdantix.com/insightsFree research (Vantage): https://www.verdantix.com/vantageSupport the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryProject Flux hosts James and Yoshi speak with Yichuan Zhang, CEO and co-founder of Boltsbit, about general learning intelligence and his vision for AGI 2.0. Zhang explains why intelligence should be measured by the ability to learn, how contextual data and ongoing feedback could enable more adaptive AI, and how Boltsbit combines task modes with continuously learning models.Key TopicsYichuan Zhang traces his path from software engineering and AI research in Edinburgh and Cambridge to Google and founding Boltsbit in 2020.He connects Boltzmann machines and the unification of learning and thinking to later deep learning breakthroughs, including AlexNet and generative language models.Zhang distinguishes three learning capabilities: memory and retrieval, learning patterns from examples, and creating from instructions; he argues today’s AI still has room to improve at learning from examples.He describes AlphaGo Zero as evidence that AI can produce discoveries beyond its training examples when supported by sufficient compute and data.His Infinity Parameter LMs paper explores dynamically changing model parameters and generating new experts as a model produces tokens; he frames it as an early step toward general learning intelligence.Zhang argues data is use-case-specific and contextual, and that intelligence should be judged by the speed and capability of learning rather than stored knowledge or current skills.Boltsbit offers general chat, widget creation, document work, and coding modes, with a learning console for users to guide what the agent learns and how it responds.He describes Boltsbit’s approach as combining open-source models and applying continuous fine-tuning, while favoring models of roughly 40 billion parameters or fewer for practical hosting.Zhang argues organizations should build control and adaptability around AI rather than rely entirely on rented intelligence, and predicts model training will become cheaper while valuable domain data remains differentiating.On the future of AI, Zhang says people will still supply judgment and approval, even as AI makes building and deploying models much more accessible.Chapters00:00 Meet Yichuan Zhang: from AI research to Boltsbit03:46 Hinton, Boltzmann machines, and deep learning’s rise08:05 Three kinds of learning and what AI still lacks11:01 AlphaGo Zero and AI’s capacity for novel discoveries12:46 Dynamic experts and the Infinity Parameter LMs paper16:54 AGI 2.0: measuring intelligence by learning speed18:12 Why data needs context, not just scale22:04 General learning intelligence and human experience26:23 Why world models do not solve contextual learning28:46 Boltsbit’s four modes and continuous learning32:15 Feedback, enterprise workflows, and model choices36:00 Small models, AI ownership, and the cost of renting40:07 What may change by 2030, and where human judgment stays44:21 Open-source models, training, and the closing conversationLinks & Stuff🔗 Yichuan on LinkedIn: www.linkedin.comhttps://www.linkedin.com/in/dr-yichuan-zhang-bz1886🏢 Boltzbit:https://boltzbit.com/www.linkedin.com/company/boltzbitSupport the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryDino Ravnic, CEO of GIS Cloud, shares insights on the evolution of geospatial information systems, the impact of AI, and the future of GIS technology. Discover how democratizing GIS through cloud and AI is transforming industries and enabling new possibilities.Key TopicsThe evolution of GIS from traditional mapping to cloud-based systemsHow AI and MCPs are transforming geospatial data analysisThe role of digital twins in infrastructure and urban planningDemocratization of GIS through cloud technology and AIFuture trends in geospatial information systems and industry applicationsChapters00:00 Introduction to Dino Ravnic and GIS Cloud04:04 Google Maps as a foundation for GIS democratization05:51 The role of AI in making GIS accessible to non-specialists08:10 Future trends: AI, digital twins, and world models10:04 Ensuring deterministic systems and avoiding hallucinations11:58 The evolution of MCPs and system integration13:58 Controlling AI tools and data security in GIS15:58 Testing and refining AI models for GIS applications17:54 Career shifts in GIS roles due to AI advancements20:08 GIS in the context of digital twins and robotics21:56 Preparing for the future of GIS and AI integration24:00 The importance of data control and AI safety26:01 Croatia's tech ecosystem and global software development28:06 The rapid acceleration of AI and its implications30:00 Predictions for the next 20 years of AI and GIS31:57 Diffusion of spatial information in society34:02 Economic considerations: tokenization and AI costs36:06 Best practices for AI-enabled GIS and future readiness37:56 Personal recommendations and insights from Dino Ravnic39:54 Special offer: 90-day free access to GIS Cloud AILinks & StuffLinkedIn: https://www.linkedin.com/in/dinoravnic/GIS Cloud: https://www.giscloud.com/⭐ LISTENER OFFERFor new GIS Cloud signups:Get an extended 90-day free trial of GIS Cloud AI.The first 25 companies will receive a free 45-minute AI mapping setup session with the GIS Cloud team. They will help you upload your project data and get your first AI-ready map running.How to Redeem:Sign up at: giscloud.comEmail [email protected] with FLUX in the subject line.Send the email from the same email address you used to sign up.GIS Cloud will extend your trial and arrange your free setup session.YouTube:▶️ Watch the full episode on YouTube;Episode Link: https://youtu.be/eZmAPa9w6d8Newsletter: https://projectflux.ai/?utm_source=buzzsprout&utm_medium=podcast&utm_campaign=dino_ravnic"Support the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryIn this episode, we explore the latest developments in AI, including OpenAI's DOTS, persistent agents, model releases, and the implications for various industries. We discuss the convergence of AI tools, ethical considerations, and future trends shaping the AI landscape.Key TopicsOpenAI DOTS and persistent agentsConvergence of AI tools and platformsImplications of AI model releases for industriesEthical and safety considerations in AI deploymentAI pricing strategies and market competitionAI in healthcare and government systemsFuture trends in AI development and regulationChapters00:00 Introduction to AI developments and episode overview02:44 OpenAI DOTS: An always-on, customizable agent06:26 Convergence of AI platforms and user interfaces12:25 Building personalized harnesses for AI models15:10 Balancing persistence and obedience in AI agents22:56 Video generation and the Turing test threshold26:33 AI security breaches in government systems34:21 Market dynamics: AI pricing and competition44:36 AI in critical infrastructure and safety concerns49:55 AI's impact on industry jobs and responsibilities54:11 The importance of human-AI collaboration and learningSupport the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryIn this episode, Robert Maxwell discusses the evolving landscape of cybersecurity, AI's role in security, and the importance of management education in adopting new technologies. He shares insights from his book and experiences, emphasizing continuous review and collaboration to mitigate risks.Key TopicsCybersecurity challenges with AIThe Australian government hack and lessons learnedThe importance of management education in tech adoptionThe evolving threat landscape due to AIStrategies for effective cyber defense and regulationThe role of legislation and industry collaborationThe impact of AI on job security and skillsThe importance of continuous review and thinking in AI projectsChapters00:00 Introduction and episode overview02:30 Robert Maxwell's background and journey into cybersecurity04:23 The challenges of AI adoption and management's role05:41 Cybersecurity vulnerabilities and the evolving threat landscape06:45 The Australian government hack and lessons for organizations07:36 The need for regulation and industry collaboration11:44 Key ideas from Robert Maxwell's book on cyber vulnerability12:49 The importance of focused AI projects and avoiding AI washing14:06 Shadow AI and unapproved tool usage in organizations15:27 First steps for SME owners to prevent shadow AI proliferation19:47 The four steps: outcome, technology, people, data24:37 Managing change and avoiding analysis paralysis26:21 Cybersecurity in the age of AI and increasing attack surface36:50 Global approaches to AI regulation and enforcement37:48 Predictions for AI development and risks in the next six months40:04 The importance of AI literacy for individuals and organizations41:00 Where to find Robert Maxwell and his workLinks & StuffLinkedIn: https://www.linkedin.com/in/robert-maxwell-tgt/Support the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryIn this episode, Sam Rees, CEO of Hopper, discusses how AI is transforming data management in the construction and infrastructure industries. They explore the challenges of adoption, the potential of AI to revolutionize workflows, and the future of digital transformation.Key TopicsAI-driven data structuring in constructionChallenges of AI adoption in industryThe evolution of digital transformationCase study: AI improving asset managementFuture trends in construction data managementChapters00:00 Introduction and episode overview00:20 Sam Rees' background and Hopper's mission00:41 Challenges in AI adoption and industry skepticism00:59 The core problem Hopper aims to solve01:11 The evolution of data structuring in construction01:34 Case study: Asset life cycle analysis at an airport01:48 AI's role in speeding up data processing02:13 The importance of domain expertise in AI applications02:37 Future of AI and digital transformation in constructionLinks & StuffSam Rees LinkedIn: https://www.linkedin.com/in/sam-rees-9062487a/Company: https://hoppa.ai/Movar Reply: https://movar.group/PM Global Management: https://www.globalprojectleader.co.uk/Support the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryIn this episode, Itai Green discusses the urgency of innovation in the fast-paced world of technology, the importance of engaging with startups, and how organizations can adapt to AI-driven change to stay relevant.Key TopicsThe importance of rapid innovation in today's ecosystemHow organizations can effectively engage with startupsThe impact of AI on organizational structure and strategyStrategies for managing change and fostering agilityThe role of leadership in driving innovation and speedChapters00:00 Introduction and guest overview03:52 Case study: Salesforce's rapid adaptation04:58 The rise of AI tools like Wix and Base 4406:30 The future of organizations in an AI-driven world07:02 The challenge of organizational inertia and culture08:22 The importance of understanding and engaging with the ecosystem12:03 The difference in innovation dynamics between startups and large corporations14:02 The value of maintaining startup culture within large companies16:33 Changing KPIs and management mindset for innovation18:00 How to start engaging with startups and new technologies22:18 The pilot process and investment opportunities27:52 The importance of leadership engagement in innovation30:02 Managing bureaucracy and accelerating adoption32:56 The importance of being aware of emerging solutions35:58 The future of industry and the importance of ecosystem awareness37:50 The most impactful non-AI technologies seen in startups38:38 Alternative careers: Math teaching and lifelong learning39:06 The role of foundational knowledge in a world of AI40:16 The rapid pace of AI development and future outlook41:07 Closing thoughts and how to connect with Itai GreenLinks & StuffLinkedIn: https://www.linkedin.com/in/itaigreen/Book: Innovation or Elimination: WINNING in a World of Constant Changehttps://www.amazon.com/Innovation-Elimination-Winning-Constant-Change-ebook/dp/B0F1M7RC65Support the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryIn this episode, we explore the rapid advancements in AI, its implications for jobs, project delivery, and the ethical considerations surrounding emerging models like Astra and Gemini. We discuss how AI is transforming industries and what the future might hold.Key TopicsAI model advancements from Astra, Gemini, and othersImplications of AI on jobs and the economyThe technical evolution of large language models and their capabilitiesEthical considerations and safety in AI developmentThe impact of AI on project delivery and construction industryChapters00:00 Introduction to the AI landscape and recent developments01:57 AI's impact on cybersecurity and economic models03:52 The evolution of AI models and their capabilities06:46 The debate on AI hype versus reality10:02 Job displacement, diffusion, and the doomsday scenarios14:48 The importance of AI alignment and value systems19:55 Project delivery, automation, and decision-making bottlenecks25:01 The future of AI models: Astra, Gemini, and emerging capabilities29:52 Model efficiency, token usage, and recursive self-improvement34:56 The role of browser use, agent swarms, and hacking incidents40:02 The ethical and societal implications of AI advancements45:11 AI in construction: design, automation, and project management49:00 Summary, future outlook, and closing remarksSupport the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

Send us Fan MailSummaryIn this episode of Project Flux, James and Yoshi talk with Chris de Gruben about AI, automation, AGI, the future of work, and its impact on property and professional services. If you want to understand how AI could reshape your career and what skills will matter next, this conversation is worth a listen.Key TopicsAI's role in military and warfareImpact of AI on jobs and industryAI regulation and ethical considerationsDevelopment of AGI and superintelligenceGlobal AI strategies and cultural differencesAI's influence on property and real estateEducation and AI literacy for the futureAI's economic and geopolitical implicationsChapters00:00 Introduction and guest overview03:16 Autonomous systems and AI in military operations06:26 Regional AI strategies: Middle East and cultural differences10:28 Future job roles and AI-driven job transformation14:13 Training future surveyors and AI skills18:08 Transforming consulting and transformation projects21:22 The speed of AI adoption and technological progress25:17 Global disparities and AI's geopolitical impact30:35 Tools for AI compliance and standards enforcement35:10 Defining AGI and superintelligence38:36 Physical hardware and AI embodiment42:39 Synthetic data and AI training challenges43:15 Fragmentation and shadow AI risks44:30 Brand, reputation, and trust in AI-driven industry45:14 Risks of AI mishandling and data leaks46:17 Societal resistance and AI backlash47:24 The future of human-driven services and AI coexistence48:39 Preparing for AI: education and soft skills49:03 Surveying and AI: future skills and roles49:53 Closing remarks and future outlookLinks & StuffLinkedIn: https://www.linkedin.com/in/degruben/Sponsored By:  morta.ioSupport the showSubscribe to the Project Flux Newsletter!All our podcasts commentate on the weeks hottest news brought to you by the Project Flux Newsletter! Get a step ahead on the world of AI and tech, subscribe and get the weekly newsletter to your inbox every Monday!Sign Up to Newsletter Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.