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In an interview with Conor Doherty, Joannes Vermorel, founder of Lokad, and Pierre Pinson, Chair of Data-centric Design Engineering at Imperial College London, discuss probabilistic forecasting and its applications in various fields. They emphasize the importance of understanding uncertainty in forecasting and the need for ongoing education in the area. All three agree that innovation happens faster than people can embrace it, and they encourage staying updated on new developments in the field and being prepared for the advancements yet to come.
00:00:00: Introduction of Pierre Pinson
00:01:25: Pierre Pinson’s background and his work in data-centric design engineering and forecasting.
00:02:20: How Pierre got into probabilistic forecasting and its applications in energy, logistics, and business analytics.
00:04:17: Assessing forecast quality, its importance in decision making, and how it connects with forecast value.
00:07:41: Initial reactions to probabilistic forecasting.
00:08:27: The problem of overconfidence.
00:10:00: Claude Bernard’s criticism of statistics and probabilities.
00:13:00: Determinism vs. stochastic behaviors in the world.
00:14:37: Bridging meteorology and business with probabilistic forecasting.
00:15:11: The importance of weather forecasting and cultural implications.
00:16:46: Explaining probabilities and understanding forecasts.
00:18:58: Challenges of information overload and decision-making.
00:20:31: Transforming probabilities into risk assessments.
00:22:14: Balancing automated decision-making and user trust.
00:23:36: Importance of meteorological forecasts in business and logistics.
00:25:01: Wind forecasts and their significance in the energy sector.
00:26:00: Weather data usage in power demand forecasting and supply chain situations.
00:30:25: Differences in applying probabilistic forecasting in meteorology and logistics contexts.
00:32:46: Discussing the challenges of translating complex probabilistic forecasts for clients.
00:33:32: Cost concerns of cloud computing and hosting large amounts of data.
00:35:02: Using two-dimensional histograms and their impact on memory and cost.
00:37:19: Teaching probabilistic forecasting and the challenges students face.
00:40:00: Making probabilistic forecasting easier and understanding model verification.
00:42:40: Inefficiency in process and transportation methods.
00:43:57: The challenge of removing uncertainties from the supply chain.
00:45:20: The cost of removing uncertainties and its impact on various industries.
00:47:00: The evolution of forecasting and its shift from applied mathematics to economics.
00:50:53: Convergence of different fields in forecasting and decision making under uncertainty.
00:52:30: Adapting the explanation of probabilistic forecasting for different backgrounds.
00:53:21: Applying probabilistic forecasting to various businesses and its benefits.
00:55:53: The appeal of visually interesting probabilistic forecasts and copyright infringement stories.
00:58:03: The limitations of pie charts in conveying information and their usage in pre-sale stages.
01:00:01: Embracing uncertainty in professional careers and understanding the probabilistic perspective.
01:02:23: Interdisciplinary approach and uncertainty in various industries.
01:04:27: Importance of education and how new generations impact the industry.
01:07:00: Probabilistic forecasting adoption curve in different fields.
01:08:33: Joannes’ view on a century-long time horizon for embracing uncertainty.
01:10:37: Challenges in adopting new ideas and the slow pace of change in some fields.
01:12:14: Importance of mathematics in forecasting technology.
01:13:26: Future advancements in forecasting science and technology.