Podcasts about probabilistic forecasting

Guests: Dr. Ilan Price, Senior Research Scientist, & Matt Willson, Research EngineerFrom the Euro to the GFS to the Canadian, there are multitudes of models that forecasters use to predict our daily weather. There are models for short-term severe forecasting, 10-day outlooks from your local news, and even models that predict our climate years into the future. As technology advances, so do all of these models and the technology we are focusing on today on Weather Geeks is AI. While it may seem like a buzzword these days, it can be used to enhance our industry and help us all reach our common goal: saving lives and property. We are thrilled to welcome Dr. Ilan Price to discuss GenCast, Google's weather forecasting model that is entirely powered by AI. How does it stack up to the models we know and love? The answer may surprise you…Chapters00:00 Introduction to AI in Weather Forecasting02:10 Meet the Experts: Ilan Price and Matthew Wilson06:34 Understanding GenCast: The AI Weather Model10:47 Machine Learning vs Traditional Forecasting13:22 Data Sources and Ethical Considerations15:10 Handling Extreme Weather Events21:15 Validation and Verification of GenCast23:26 Impact of GenCast on Weather ForecastingSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Female VC Lab Show Notes Episode Title and Number: CES2025: What's Next for Smart Cities - AI for Data, Planning, and Beyond Name of Session: What's Next for Smart Cities: AI for Data, Planning and Beyond Date and Time: Tuesday, January 7, 2025 at 3:00 PM Location: Las Vegas Convention Center North - N257 Session Description: The rise of AI-powered Smart Cities is significant. Learn from early adopters who have seen AI capabilities become notable force multipliers in our smartest cities.  Full Panel: David Shier, Managing Director, Visionary Future (Moderator)  Sheri Bachstein, CEO, The Weather Company Barbara Bickham, Founder & GP, Trailyn VC Nadia Hansen, Global Digital Transformation Executive, Salesforce Prachi Vakharia, ARPA-I: Strategic Advisor for Innovations & Infrastructure, USDOT Episode Summary: In this episode, we dive into the transformative potential of AI in developing smart cities, as discussed in a CES 2025 panel. The conversation covers aspects ranging from extreme weather prediction to citizen-centric services and the ethical implications of AI in urban governance. Key Points Discussed: The role of AI in predicting extreme weather and urban design Probabilistic forecasting and its benefits for emergency preparedness The concept of citizen-centric smart cities for enhanced public participation Challenges in data standardization and the importance of public-private partnerships Ethical considerations, including bias and privacy concerns in AI technologies Timecode Guide: 00:00:04 - Introduction to smart cities and AI 00:00:38 - Discussion about extreme weather prediction with AI 00:01:53 - Explanation of probabilistic forecasting 00:03:09 - Concept of citizen-centric smart cities 00:04:47 - Data challenges and public-private partnerships 00:08:09 - Ethics, transparency, and public education on AI 00:11:01 - Challenges with AI model sizes and limited data 00:17:40 - Privacy concerns in smart cities 00:18:45 - Ensuring AI doesn't perpetuate bias 00:20:02 - Discussion on potential job losses and new opportunities 00:21:09 - Misuse of AI by authoritarian governments 00:22:25 - Weather strategy in the era of climate change 00:25:27 - Collaboration and human-centered AI 00:27:45 - Future vision for smart cities Full Topic Guide: The Future of Smart Cities: Harnessing AI for a Better Urban Life Introduction: As we stand on the brink of an AI-driven transformation in urban living, the CES 2025 panel offers an enlightening glimpse into how next-gen technologies are being leveraged to create smarter, more resilient cities. Hosts Daniel and Barbara Bickham review these discussions, stressing the interplay of data, AI, and human insight in shaping the future. AI in Predicting Extreme Weather: One of the most compelling highlights was the role of AI in weather prediction and urban planning. As climate change leads to unpredictable weather patterns, AI provides a way to prepare for unprecedented events. AI's capacity to analyze vast amounts of climate data allows for effective "what if" scenario modeling, enabling cities to design infrastructure that can withstand extreme conditions. For example, you might reinforce a seawall today based on AI predictions of future storms. Probabilistic Forecasting: Advancements in probabilistic forecasting were another exciting point discussed. Unlike traditional methods, probabilistic forecasting uses AI to run thousands of scenarios, providing a range of potential outcomes rather than a single prediction. This not only improves weather accuracy but also aids in emergency preparedness, allowing cities to allocate resources more efficiently and preempt disasters, thereby saving lives and reducing costs. Citizen-Centric Smart Cities: The concept of making cities more user-friendly for residents drew considerable attention. Imagine all city services being available through a single app—reporting potholes, paying taxes, or even participating in local governance through blockchain-enabled voting systems. This not only simplifies interactions with municipal services but also empowers citizens by giving them a direct say in urban management. Data Challenges and Public-Private Partnerships: However, the transition to smart cities is fraught with challenges, particularly in data management. Cities gather massive amounts of data, but these are often trapped in silos, hindering a comprehensive overview. Collaboration through public-private partnerships is vital here. Government bodies possess critical data, while private enterprises offer the technological expertise to process and utilize this information effectively. Examples like the Weather Company's collaborations with NOAA and NVIDIA highlight the potential of these partnerships. Ethical and Transparency Considerations: The panel stressed the ethical implications of integrating AI into city management. Trust and transparency are crucial for citizen buy-in. There needs to be a concerted effort to educate both government officials and the public on AI. Moreover, it's important to ensure that AI systems are fair and do not perpetuate existing biases. Implementing strong ethical guidelines and having diverse teams develop these technologies can mitigate potential risks. Privacy Concerns: With vast amounts of data being collected, privacy is a significant concern. Clear rules on data collection, use, and access are necessary to prevent misuse. Enabling citizens to control their data and ensuring transparency about how it is used are steps toward this goal. Conclusion: The future of smart cities depends not just on technological advancements but on collaborative, human-centered approaches. As we navigate this transformation, the focus must remain on using technology to enhance, not hinder, urban life. Notable Quotes from the Hosts: "It's about giving people the tools and the knowledge to be active participants in shaping the future of their cities." "We need to be mindful of the potential consequences of AI on jobs, privacy, and equality." Fun Facts or Interesting Tidbits: People were more interested in searching for inmates in jail rather than marriage licenses on the redesigned Clark County website. A project in Massachusetts involved transit maps from the 1970s, highlighting the need to update and digitize old data for modern use. Stay engaged with the conversation on how AI and technology are transforming our cities. Feel inspired? Share your ideas on how we can build a smarter, more inclusive future for our urban environments. Follow us on social media and subscribe to our newsletter for more updates and deep dives into the latest technological trends.

Nate Kaemingk is Chief Forecaster for BetterForecasting.com, where he has built a financial forecasting AI for mid-market finance teams. Previously he has been a  Fractional CFO for two Montana based companies. Nate started his career as a mechanical engineer using inferential statistics to model chemical reactions in Diesel engines!  Later, during his MBA, he applied an inferential statistics background to forecasting and scenario analysis.  Nate has had the opportunity to apply these methods in roles with multiple Fortune 500 companies, including Cummins, and subsequently as CFO and Chief Forecaster at Better Forecasting.  Episode links: www.BetterForecasting.com Connect with Nate (LinkedIn) https://www.linkedin.com/in/nathankaemingk/ On this episode:  Probabilistic Forecasting, small (not big data) and inferential statistics  Rolling Forecasts vs Annual Budgets explained Importance of not skipping out on the fact you need to update your plan Why are we resistant to changing the budget? The advantages of a rolling forecast Using Leading Market Indicators  DSO (Day Sales Outstanding) as a powerful forecasting example How long range forecasting reveals structural issues in a business  Building a driver-based model – and why it's hard  Renting an RV and touring the country for 3 years Favorite Excel function

Tim Palmer is Royal Society Research Professor in Climate Physics at the University of Oxford, where he is a Senior Fellow at the Oxford Martin Institute and a Professorial Fellow at Jesus College. Tim works on the predictability and dynamics of weather and climate, including extreme events, and is well known within the field for developing probabilistic ensemble forecasting techniques. In this episode, Robinson and Tim discuss his recent book, The Primacy of Doubt: From Quantum Physics to Climate Change, How the Science of Uncertainty Can Help Us Understand Our Chaotic World (2022). More particularly, they talk about black holes and the holographic principle, the foundations of quantum mechanics, meteorology and probabilistic forecasting, chaos theory and consciousness, and the problem of climate change. The Primacy of Doubt: https://a.co/d/dL8JfTn OUTLINE 00:00 In This Episode… 00:37 Introduction 02:37 From Physics to Meteorology 13:17 Black Holes and the Holographic Principle 35:09 What Is the Butterfly Effect? 43:31 Why Is Weather Chaotic and What Can We Do About It? 01:09:34 Can Principles of Meteorology Be Applied to the Problems of Consciousness and Free Will? 01:30:55 Chaos Theory and Climate Change Robinson's Website: http://robinsonerhardt.com Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.  --- Support this podcast: https://podcasters.spotify.com/pod/show/robinson-erhardt/support

This episode features Troy Lightfoot who is a Business Agility Coach and Consultant as well as a Professional Kanban Trainer. The interview starts with a discussion about the basic differences between Scrum and Kanban and then digs into four of the metrics recommended in the Kanban Guide. We cover WIP, Throughput, Work Item Age, and Cycle Time, talking through what each of these is, the value these metrics provide, why they are so much more valuable than simply looking at something like velocity, and what these metrics can do to help you develop a better level of predicting when work is likely to finish and how they can show you and your team ways to identify and address the things that are holding you back from delivering value for your client. Troy also has a few ProKanban Certification classes coming up. In the back half of the interview, he explains what to expect if you sign up for a Professional Kanban 1 (PK1) Certification class or his Applying Metrics for Predictability (AMP) Certification class. Troy's Classes Professional Kanban 1 (PK1) Certification June 23-24, 2022 https://bit.ly/3HmV1Ug Applying Metrics for Predictability (AMP) Certification July 21-22, 2022 https://bit.ly/3zxZOk2 Links from the Podcast ProKanban.org https://prokanban.org The Kanban Guide https://kanbanguides.org My interview with Troy Magennis on Probabilistic Forecasting https://bit.ly/3tDUW9b My interview with Colleen Johnson on ProKanban and ProKanban Certification https://bit.ly/3NUN6Ac Actionable Agile Metrics for Predictability by Dan Vacanti https://amzn.to/3tAVeh7 When Will it Be Done by Dan Vacanti https://amzn.to/3NUjrqR Contacting Troy Email: troylightfoot@gmail.com

"What is probabilistic forecasting (and why is it better)?" Find out in this episode of Appfire Presents: The Best Project Portfolio Management Show by Appfire. Julia Wester talks with Appfire's own Kerry O'Shea Gorgone about probabilistic forecasting - what it is, why it's better for project outcomes, and how it works. Julia Wester is a co-founder of 55 Degrees, an outcome-focused product company. Julia's the product owner for their flagship product, ActionableAgile. Website: https://www.55degrees.se LinkedIn: https://www.linkedin.com/in/juliawester About The Show: The BEST Project Portfolio Management Show by Appfire covers everything you ever wanted to know about PPM by talking with project management experts who've seen it all. And every episode is 10 minutes or less, so you can get back to changing the world, one project at a time. Appfire.com

Dan and Prateek talk about forecasting in a probabilistic world. They demonstrate how to use Monte Carlo simulations to answer - "When will it be done?". How do we use what we know about the system to predict what we can get done using some probabilistic forecasting techniques. Note - Some parts of this podcast use visual aids. For the full experience, please refer to the Drunk Agile youtube channel - https://www.youtube.com/channel/UC758reHaPAeEixmCjWIbsOA

Scenario planning was first pioneered by Shell in the 1970's and since then has been promoted by consultancies worldwide as a powerful tool to help companies prepare for every eventuality. Here, we discuss the effectiveness of this approach and whether it can be replaced by alternative methods, such as probabilistic forecasting.

Guest Name : Joannes Vermorel, CEO & Founder at Lokad. Language : English, Publication date: Feb, 18. 2020 Joannes is the CEO and founder at Lokad. Prior to that, he was teaching software engineering and cloud computing at the Computer Science Department of the École normale supérieure of Paris. Lokad was created in Paris in 2008 as a software company with a strong technological and mathematical core. The goal was to bring state-of-the-art technology and science to supply chains: they were among the very early adopters of cloud computing, and today they keep the same spirit with deep learning. Visit more on : www.lokad.com Connect him on Linkedin: https://www.linkedin.com/in/vermorel/ Highlighted: What's the essential meaning of the probabilistic forecasting ? What does it make special compared to traditional forecasting ? How we can use the method in improving supply chain operations and processes ? The development of tech. like AI, Blockchain etc. and their influence to the way of doing a forecasting. --- Send in a voice message: https://anchor.fm/bicarasupplychain/message

Read the full Show Notes and search through the world’s largest audio library on Scrum directly on the Scrum Master Toolbox Podcast website.  You only know a good team when they are under pressure. It’s easy to “follow the process” if you have a lot of time, and little pressure. However, as a Scrum Master, you know you’ve done good work when the team sticks to the process (and even improves it) when they are under pressure. I advocate using self-imposed pressure to get better, I’ve written and recorded a video about that based on my own experience as a runner. The same is true in your work as a Scrum Master!  Featured Book of the Week: Agile Actionable Metrics For Predictability by Dan Vacanti In Agile Actionable Metrics For Predictability by Dan Vacanti, Darren found the inspiration to start using and learning from metrics. It also got Darren started on Probabilistic Forecasting, a method he uses regularly.  In this segment, we also refer to Agile Retrospectives by Esther Derby and Diana Larsen, and to Scrum Mastery, but Geoff Watts. Both Diana Larsen and Geoff Watts have been guests here on the Scrum Master Toolbox podcast.    About Darren Smith Darren, aka the Naked Scrum Master, has been helping teams and organizations be better than they were by exposing dysfunction and helping people to remove obstacles from their path so they can be happier and more fulfilled in their working lives. You can link with Darren Smith on LinkedIn and connect with Darren Smith on Twitter.   

In this episode of SoundNotes, we tackle the question of whether or not it's a good idea for the Development Team to limit the size of work brought into a Sprint. Many teams consider this to be a valuable practice during Sprint Planning or when creating a Definition of Ready. The goal is to make sure that the Development Team is not committing work into a Sprint that they cannot complete during the course of a Sprint. This often shows up as something like “Nothing bigger than an 8” (for teams using Fibonacci to estimate User Story Points). While this practice can be valuable for the Development Team, it also has an impact on the Product Owner and how they prepare work for Sprint Planning. During the podcast, LeadingAgile SVP and Executive Consultant, Scott Sehlhorst and Senior Consultant Andrew Young talk with Dave about whether or not this practice actually helps and how it can become an impediment for the Product Owner who is trying to plan out work for the Release. Note from Dave:  This conversation was very impactful for me in terms of how I think about “ready” and how I think about the work done by the PO in getting ready for the Sprint. Limiting the size of work brought into a Sprint has always been something I have advocated for because I think it helps the Development Team, but I’ve never taken the time to think about how it might create challenges for the PO, who may be far more concerned about the Release than the Sprint. Links from the Podcast Ron Jeffries on Story Points and Ideal Time https://ronjeffries.com/articles/019-01ff/story-points/Index.html Mike Cohn on Story Points https://www.mountaingoatsoftware.com/blog/what-are-story-points Kenny Rubin on Definition of Ready https://innolution.com/blog/definition-of-ready Why We Use Fibonacci Number to Estimate Story Points (Jeff Sutherland) https://www.scruminc.com/why-do-we-use-fibonacci-numbers-to-estimate-user-stories/ Probabilistic Forecasting Interview with Troy Lightfoot https://www.projectmanagement.com/blog-post/54062/Probabilistic-Forecasting-with-Troy-Lightfoot No BS Estimation Cards https://estimation.lunarlogic.io   Contacting Scott Sehlhorst LeadingAgile: https://www.leadingagile.com/guides/scott-sehlhorst/ Twitter: https://twitter.com/sehlhorst LinkedIn: https://www.linkedin.com/in/sehlhorst/ Blog: http://tynerblain.com/blog/ Contacting Andrew Young LeadingAgile: https://www.leadingagile.com/guides/andrew-young/ LinkedIn: https://www.linkedin.com/in/atyoung/ Twitter: https://twitter.com/exclamation101 Email: andrew.young@leadingagile.com Contacting Dave Prior If you’d like to contact Dave you can reach him at: LeadingAgile: https://www.leadingagile.com/guides/dave-prior/ LinkedIn: https://www.linkedin.com/in/mrsungo Twitter: https://twitter.com/mrsungo Email: dave.prior@leadingagile.com If you have a question you’d like to submit for an upcoming podcast, please send them to dave.prior@leadingagile.com And if you're interested in taking one of our upcoming Certified ScrumMaster or Certified Scrum Product Owner classes, you can find all the details at https://www.leadingagile.com/our-gear/training/

Trying to figure out when you will be ready to ship is incredibly challenging. Many Scrum teams track historic velocity, or story points completed in a Sprint, and then use the average number of points completed per Sprint as a way of making an educated guess as to when they could deliver when they’d expect to deliver a certain number of story points in the future. There are, however, many who feel that this approach is no better than just making a completely random guess, and there is evidence to support the value in taking a different approach. In this episode of The Reluctant Agilist, Troy Lightfoot explains his approach to Probabilistic Forecasting, what it is, why it matters, and how it is a better way of planning than using a more traditional approach. Books Recommended In the Podcast: Actionable Agile Metrics for Predictability - Dan Vacanti https://amzn.to/2HT1zfe When will it be done? - Dan Vacanti https://leanpub.com/whenwillitbedone Principle of Product of Development Flow - Don Reinterson https://amzn.to/2M989DD Tools mentioned in the podcast: Throughput and cycle time calculator:  http://focusedobjective.com/free-tools-resources/ Actionable Agile http://actionableagile.com Agile Uprising Agile Uprising http://agileuprising.com Contacting Troy Twitter: https://twitter.com/g4stroy Web: http://agileuprising.com/bod/troy-lightfoot/ http://www.cookingandketones.com

Optimizing supply chains relies on having insights about the future. Classic forecasts dismiss uncertainty entirely, and assume that the forecast is perfectly known. In contrast, probabilistic forecasts embrace uncertainty, and reflect that supply chain optimization should remain robust when faced with unexpected events.

Audio clip: Adobe Flash Player (version 9 or above) is required to play this audio clip. Download the latest version here. You also need to have JavaScript enabled in your browser.AudioPlayer.embed("audioplayer_50", {soundFile:"http%3A%2F%2Fsupplychaininsights.com%2Fwp-content%2Fuploads%2Fpodcasts%2FProbabilistic_Forecasting_with_Antony_Nardozza-episode_216.mp3"}); An interview with Antony Nardozza, Material Manager of Spairliners (Lufthansa / Air France JV). He oversees the investment and divestment of a $200 million inventory. In this interview Antony shares his rationale for the selection and implementation of probabilistic forecasting as an inventory and customer satisfaction technique. Straight Talk With Supply Chain Insights – Podcast episode #216  

Audio clip: Adobe Flash Player (version 9 or above) is required to play this audio clip. Download the latest version here. You also need to have JavaScript enabled in your browser.AudioPlayer.embed("audioplayer_68", {soundFile:"http%3A%2F%2Fsupplychaininsights.com%2Fwp-content%2Fuploads%2Fpodcasts%2FProbabilistic_Forecasting_with_Joannes_Vermorel_of_Lokad-episode_207.mp3"}); The world is uncertain; yet, in today’s supply chain planning systems, we attempt to make demand certain when we know that it is not. In this podcast Lora Cecere, Founder of Supply Chain Insights, interviews Joannès Vermorel, founder of Lokad, to understand probabilistic forecasting approaches and how it can be applied to intermittent demand patterns. Straight Talk With Supply Chain Insights – Podcast episode #207

Fri, 30 Jul 2010 12:00:00 +0100 https://edoc.ub.uni-muenchen.de/12016/ https://edoc.ub.uni-muenchen.de/12016/1/kober_kirstin.pdf Kober, Kirstin