Podcasts about iea

This is episode 36 of The League, hosts David Magid and Benoy Thanjan (aka The Solar Maverick) break down the biggest clean energy headlines of the week. They cover: TotalEnergies' $1.25B sale to KKR and what it signals about renewable asset valuations. The collapse of $24B in U.S. Hydrogen Hub contracts and the broader implications for hydrogen's future. The IEA's downgraded global renewable forecast—and why solar still leads the way. The growing opportunity in solar repowering, where upgrading aging assets can boost returns at a fraction of the cost. Host Bio: David Magid David Magid is a seasoned renewable energy executive with deep expertise in solar development, financing, and operations. He has worked across the clean energy value chain, leading teams that deliver distributed generation and community solar projects. David is widely recognized for his strategic insights on interconnection, market economics, and policy trends shaping the U.S. solar industry. Connect with David on LinkedIn: https://www.linkedin.com/in/davidmagid/   Host Bio: Benoy Thanjan Benoy Thanjan is the Founder and CEO of Reneu Energy, solar developer and consulting firm, and a strategic advisor to multiple cleantech startups. Over his career, Benoy has developed over 100 MWs of solar projects across the U.S., helped launch the first residential solar tax equity funds at Tesla, and brokered $45 million in Renewable Energy Credits (“REC”) transactions. Prior to founding Reneu Energy, Benoy was the Environmental Commodities Trader in Tesla's Project Finance Group, where he managed one of the largest environmental commodities portfolios. He originated REC trades and co-developed a monetization and hedging strategy with senior leadership to enter the East Coast market. As Vice President at Vanguard Energy Partners, Benoy crafted project finance solutions for commercial-scale solar portfolios. His role at Ridgewood Renewable Power, a private equity fund with 125 MWs of U.S. renewable assets, involved evaluating investment opportunities and maximizing returns. He also played a key role in the sale of the firm's renewable portfolio. Earlier in his career, Benoy worked in Energy Structured Finance at Deloitte & Touche and Financial Advisory Services at Ernst & Young, following an internship on the trading floor at D.E. Shaw & Co., a multi billion dollar hedge fund. Benoy holds an MBA in Finance from Rutgers University and a BS in Finance and Economics from NYU Stern, where he was an Alumni Scholar. Connect with Benoy on LinkedIn: https://www.linkedin.com/in/benoythanjan/ Learn more: https://reneuenergy.com   If you have any questions or comments, you can email us at info@reneuenergy.com.

Today we had the pleasure of hosting William Clouston, Party Leader of the Social Democratic Party (SDP) in the United Kingdom. William has served as Party Leader since 2018 and was re-elected in March 2020. He originally joined the SDP in 1982 and spent four years in the Conservative Party, becoming a District Councilor and serving on Tynedale Council. He holds both undergraduate and master's degrees in Urban Planning and Property Management. We became interested in connecting with William after reading the SDP's Energy Abundance paper published in September (linked here). Founded in 1981, the SDP is an economically left leaning and culturally traditional political party. Its flagship “Social Market” economic model views the private and public sectors not as opponents but as complementary parts of the same society. We were delighted to connect with William for an insightful discussion on the UK and Europe's energy policies and beyond. We covered a wide range of topics in our conversation, beginning with the purpose and motivation for writing Energy Abundance, including Britain's current energy crisis, marked by too little power, high costs, and overreliance on imports. William shares the history of the government's role in energy policy and the SDP's argument for a return to government-led energy development, starting with building gas and coal plants. He discusses reactions to the paper, the urgency of rebuilding domestic energy capacity, and the importance of distinguishing cost and value when considering investing $150 billion in grid stabilization and baseload generation. We compare the UK's energy landscape to Germany and the U.S., the risk of further productivity decline if energy issues persist, and public awareness of the energy crisis, which remains politically constrained by cultural and institutional apathy. We explore the SDP's economic and political philosophy, including the party's support for strategic trade protection and tariffs and its cultural traditionalism, emphasizing family as the foundation of society, nation-states, borders, and conventional values. We touch on how energy debates are often constrained by social norms, particularly around net zero, the SDP's 10-year energy plan proposing a state-run, vertically integrated utility, the UK's historical “dash for gas” and current overreliance on renewables, and the party's support for large-scale nuclear, favoring its “brute force” capacity and proven designs. We ended by asking William for his vision of the UK in ten years. We learned a lot and greatly appreciate William for sharing his deep knowledge of British politics, policies, and culture with us all. To start the show, Mike Bradley noted that the S&P 500 is up ~2% this week on better than expected quarterly results from the Big US Banks. AI & Electricity mania remain “the” key equity market drivers, which has also pushed the Consumer Discretionary, Technology & Utilities sectors higher this week. On the crude oil market front, WTI has sunk to ~$59/bbl, partly on the Gaza Peace Agreement but mainly due to growing concern with the 2026 global oil supply surplus. Both the IEA and OPEC published their monthly oil outlooks, with the IEA projecting a ~4mmbpd 2026 surplus, which is ridiculously higher than all other estimates. The reason oil prices seem to be moving lower this week (versus previous weeks) is because oil traders are pressing their bearish bets now that crude oil prices have finally broken to the downside. On the energy equity front, one of this week's biggest Energy/Electricity equity movers is Bloom Energy (up ~30%) on news Brookfield struck a $5B strategic partnership with Bloom to be their preferred fuel cell supplier at Brookfield's global AI factories. Q3 Energy results kick off this week with most investors expecting to hear a softening frac story but a scaling up of their power business. Most investors

Oil and gas are back in the headlines. What does that mean for investors?In this episode, Bob and Ben join Ellis to unpack the latest reports from OPEC and the IEA, what they signal for fossil fuel investing, and how energy fits into a diversified portfolio. They also look at new data on investor sentiment regarding industrial and multifamily real estate. All of it points to where the smartest opportunities may be for investors today.Find out more about the Invest Like A Billionaire community at https://investlikeabillionaire.org/ And find out more about the podcast at https://www.thebillionairepodcast.com/

Carlos Nobre, um dos mais importantes cientistas do mundo na área do clima, é o convidado desta segunda-feira (13/10), do Roda Viva. Para o pesquisador sênior do Instituto de Estudos Avançados (IEA) da Universidade de São Paulo (USP), a COP30, em Belém, precisa ser a mais importante de todas as conferências do clima da ONU.Com apresentação de Vera Magalhães, o Roda Viva vai ar ao vivo, a partir das 22h, na TV Cultura, no site da emissora, no app Cultura Play, além de YouTube, X, TikTok e Facebook.

For the first time in history, wind and solar energy have generated more electricity than coal — marking a historic turning point for the world's power systems. New research from Ember and the IEA shows that renewable energy is now growing fast enough to meet nearly all global demand, driven largely by China and India. Join this channel for exclusive access and bonus content: https://www.youtube.com/channel/UCkbwLFZhawBqK2b9gW08z3g/join Five Minute News is an Evergreen Podcast, covering politics, inequality, health and climate - delivering independent, unbiased and essential news for the US and across the world. Visit us online at http://www.fiveminute.news Follow us on Bluesky https://bsky.app/profile/fiveminutenews.bsky.social Follow us on Instagram http://instagram.com/fiveminnews Support us on Patreon http://www.patreon.com/fiveminutenews You can subscribe to Five Minute News with your preferred podcast app, ask your smart speaker, or enable Five Minute News as your Amazon Alexa Flash Briefing skill. Please subscribe HERE https://www.youtube.com/channel/UCkbwLFZhawBqK2b9gW08z3g?sub_confirmation=1 CONTENT DISCLAIMER The views and opinions expressed on this channel are those of the guests and authors and do not necessarily reflect the official policy or position of Anthony Davis or Five Minute News LLC. Any content provided by our hosts, guests or authors are of their opinion and are not intended to malign any religion, ethnic group, club, organization, company, individual or anyone or anything, in line with the First Amendment right to free and protected speech. Learn more about your ad choices. Visit megaphone.fm/adchoices

Ifa Simmonds is an equestrian fitness and performance coach with over a decade of experience. He is the founder of the Equestrian Fitness Academy (EFA), created to help riders build strong, balanced bodies in and out of the saddle. He helps equestrians improve core strength, balance, and mobility through functional, rider-specific fitness programs. At the core of his training process are four key pillars: stability, suppleness, strength, and stamina. Each pillar is designed to enhance a rider's fitness, position, and communication in the saddle. From trail riders to top-level competitors and coaches, he works across English and Western disciplines, including dressage, eventing, reining, hunter/jumper, and western pleasure. Drawing on certifications in functional fitness, yoga, and Pilates, he weaves these disciplines into EFA to help riders move with greater strength, fluidity, and purpose. A sought-after clinician, writer, and presenter, he shares his expertise with equestrian organizations worldwide and has been featured on platforms like IEA and IHSA. Website: https://ifafit.com/ Contact Ifa today!   

Carrier, the company that invented air conditioning, is now adding batteries to its HVAC systems to help stabilize the grid. James compares clean energy progress in Heilongjiang, China, to the situation in Saskatchewan, Canada, where coal is sticking around until 2050. Meanwhile, developing nations may be scaling back their attendance at COP30 in Brazil due to soaring hotel prices in the Amazon. Join us for free on Patreon for addional content like the hydrogen letter correcting us. We also dig into listener mail, including a detailed correction on hydrogen vs. SMR math, new EV charging options from Grizzl-E, heat pump dryer experiences, Scandinavian crime drama recommendations, and whether James should just fill his house with snake plants instead of an air purifier. Plus, Glenn Wright weighs in on forests, carbon sinks, and net-zero. In the Lightning Round: U.S. nuclear license extensions in Wisconsin France planning a 1.5 GW offshore wind farm The U.S. DOE reportedly banning “climate change” from its vocabulary Renewables beating new nuclear ten to one for climate mitigation China's clean energy dominance in solar, batteries, and wind Morocco sending solar power to Germany Europe backing African renewables A new sodium-ion battery installation in Switzerland And just how many solar panels China installs every second Links to stories we covered: Carrier batteries for air conditioners (Canary Media): https://www.canarymedia.com/articles/batteries/carrier-air-conditioning-help-grid Heilongjiang clean energy projects (China green hydrogen & e-methanol): https://www.bloomberg.com/news/articles/2025-09-29/nations-rethink-plans-for-brazil-climate-summit-as-costs-soar?srnd=phx-green COP30 hotel crunch (Bloomberg): https://www.bloomberg.com/news/articles/2025-09-29/nations-rethink-plans-for-brazil-climate-summit-as-costs-soar?srnd=phx-green Grizzl-E EV Club: https://grizzl-e.com/ca/ | https://club.grizzl-e.com/ | https://youtu.be/SH7fItzcFbQ Antarctica wind project: https://www.antarctica.gov.au/antarctic-operations/stations-and-field-locations/amenities-and-operations/renewable-energy/wind-power IEA on rising AC demand: https://iea.li/48AjJAc Morocco–Germany undersea solar cable (CleanTechnica): https://cleantechnica.com EU renewables in Africa (Bloomberg): https://bloomberg.com

According to the IEA’s 2025 Global Methane Tracker, methane is responsible for around 30% of the current rise in global temperature. Mitigating methane, which has more than 80x the warming potential of CO2 over a 20-year period, is critical to addressing climate change. In this episode of ESG Currents, Bloomberg Intelligence’s director of ESG research Eric Kane speaks with Olya Irzak, founder and CEO of Frost Methane, about the company’s efforts to destroy, valorize and measure emissions from manure ponds and other sources. They also talk about the volatility of voluntary carbon markets, raising capital, the current climate policy landscape and more.See omnystudio.com/listener for privacy information.

This weekend's KE Report show dives deep into two key corners of the commodities market. In the first half, Matt Geiger breaks down precious metals sentiment post-Beaver Creek and where copper could be the next big mover. In the second half, Dan Steffens highlights why select oil and gas names remain undervalued despite a flat pricing environment. Segment 1 & 2 - Managing Partner Matt Geiger of MJG Capital joins to discuss Beaver Creek's upbeat sentiment and why he sees precious metals in the “middle innings,” expecting near-term consolidation in gold/silver while turning bullish on copper given supply disruptions and an extreme copper-to-gold disconnect. He also weighs in on the Elemental Altus–EMX royalty merger and Tether's role, majors like Centerra taking stakes in juniors, and his playbook of favoring early-stage copper names, taking profits into hype, raising cash, and redeploying into high-quality pullbacks. Click here to visit the MJG Capital website to learn more about Matt's fund   Segment 3 & 4 - Dan Steffens, president of the Energy Prospectus Group, argues that even with range-bound oil and gas prices, geopolitical risks and the IEA's shifting outlook keep supply tight. He highlights company-specific catalysts - Crescent Energy's merger and hedges, Diamondback's gas-to-power/AI plans (and Viper Energy), Devon's buybacks, and dividend-rich Northern Oil & Gas - while favoring natural-gas-weighted names ahead of rising LNG demand, a possible La Niña winter, and increased year-end M&A. Click here to visit the Energy Prospectus Group website for more energy market and stock analysis   If you enjoy the show, be sure to subscribe to our podcast feed (KER Podcast), YouTube channel, and follow us on X for more market commentary and company interviews. Don't forget to subscribe and leave us a review!   For more market commentary & interview summaries, subscribe to our Substacks: The KE Report: https://kereport.substack.com/ Shad's resource market commentary: https://excelsiorprosperity.substack.com/   Investment disclaimer: This content is for informational and educational purposes only and does not constitute investment advice, an offer, or a solicitation to buy or sell any security. Investing in equities and commodities involves risk, including the possible loss of principal. Do your own research and consult a licensed financial advisor before making any investment decisions. Guests may own shares in companies mentioned.

WATCH the video on Substack by clicking the play button above or on YouTube (here).STREAM audio only on Apple Podcasts (here), Spotify (here), or your favorite podcast player app.We have started a heavy Fall travel schedule, with our annual talk at the Oxford Energy Seminar last week and a corporate event in the Rocky Mountains this past week. We wanted to provide a trio of “long-takes” that are jumping out at us: (1) a burst in energy policy rationality and normalization that is being seen from three areas that were previously all in in "The Energy Transition"--California, Canada, and the IEA. (2) we continue to see mounting evidence that fears of an "oil glut" are way overdone, though we likely still need to get through potential shoulder month, seasonal softness over the next 4-8 weeks. Regardless, we believe we are in a bottoming phase for oil-leveraged energy equities which have been very out of favor. (3) A reminder that it is the outlook for returns and growth, not “peak demand” or “oil glut” narratives the IEA or Street analysts, that will drive energy equities.

In this episode of the Energy Newsbeat Daily Standup - Weekly Recap, Stu Turley and Michael Tanner break down a pivotal week in energy and markets. The U.S. power grid is strained by AI, EVs, and aging infrastructure—creating big opportunities in battery storage, microgrids, and SMRs. A $14 trillion stock rally now hinges on a likely 25bps Fed rate cut, which could ease borrowing for energy investments. The IEA is walking back its peak oil claims under pressure, acknowledging oil and gas demand will grow for decades. Natural gas is set to dominate U.S., China, and India's energy mix by 2050, while LNG exports are poised to double. But rising global decline rates mean trillions in capex are needed just to stay even—highlighting massive investment potential in U.S. energy infrastructure.Subscribe to Our Substack For Daily InsightsWant to Add Oil & Gas To Your Portfolio? Fill Out Our Oil & Gas Portfolio SurveyNeed Power For Your Data Center, Hospital, or Business?Follow Stuart On LinkedIn: https://www.linkedin.com/in/stuturley/ and Twitter: https://twitter.com/STUARTTURLEY16Follow Michael On LinkedIn: https://www.linkedin.com/in/michaelta... and Twitter: https://twitter.com/mtanner_1Timestamps:00:00 - Intro01:14 - America's Grid is Nearing Its Breaking Point05:38 - $14 Trillion Stock Rally Expects a Fed Cut: What Happens If They Only Get a Quarter Point?10:36 - IEA Prepares to Walk Back Predictions of Peak Oil and Gas Demand13:39 - Fed cuts rates by 0.25% after flagging risks from softening labor marketNatural Gas to Absolutely Dominate U.S., China and India's Energy Mix by 205021:36 - Global Oil and Gas Field Decline Rates Are Increasing, IEA Says – Trillions of dollars needed just to meet decline curves.25:04 - OutroLinks to articles discussed:America's Grid is Nearing Its Breaking Point$14 Trillion Stock Rally Expects a Fed Cut: What Happens If They Only Get a Quarter Point?IEA Prepares to Walk Back Predictions of Peak Oil and Gas DemandFed cuts rates by 0.25% after flagging risks from softening labor marketNatural Gas to Absolutely Dominate U.S., China and India's Energy Mix by 2050Global Oil and Gas Field Decline Rates Are Increasing, IEA Says – Trillions of dollars needed just to meet decline curves.

The BoC and the Fed both cut rates this week, signalling more easing ahead. Housing troubles persist. Federal budget gets delayed. China coal consumption hits record highs. IEA revises oil demand higher. Join The Loonie Hour and the Canadian Real Estate Investor Podcast live in Vancouver on October 21st! Get your tickets here! https://www.eventbrite.ca/e/canadian-real-estate-global-macro-tickets-1716213644209?aff=LoonieStart an investment portfolio that's built to perform with Neighbourhood Holdings. Visit https://www.neighbourhoodholdings.com/looniehour to learn more!Check out the Saretsky Group Real Estate Services: https://www.saretskygroup.com/

Enerji Günlüğü Haber Bülteni:Türkiye'nin ve Dünyanın Enerji Gündemienerjigunlugu.net

In this episode of The Hydrogen Podcast, we spotlight the technologies and market forces shaping hydrogen's future.

In this episode, Argus' Waldemar Jaszczyk discusses the future of clean cooking access in Africa with Daniel Wetzel, the head of the Tracking Sustainable Transitions Unit at the International Energy Agency. Daniel joins to take stock of the progress achieved since last year's summit on the issue, during which $2.2bn in public and private funding was pledged until 2030. Building on recent success, Daniel outlines the IEA's newly released roadmap for all African countries to reach universal access to clean cooking by 2040, describing LPG as the “workhorse” of the move away from harmful traditional cooking fuels such as wood, charcoal, and kerosene. 

Enerji Günlüğü Haber Bülteni:Türkiye'nin ve Dünyanın Enerji Gündemienerjigunlugu.net

We have seen some spectacular revisions in economic data over the past couple of years. We've seen it in labor data, gross domestic product, inflation. These revisions are continuing to come. This time it's in the oil markets. The narratives are failing to explain what's happening behind the scenes. On top of that, the numbers are just plain wrong. For example US growth in oil demand was underestimated by a factor of 4 by the IEA. Mexico's oil consumption has been under-reported by 100,000 barrels a day for the last five years. The US oil consumption was off by 350 million barrels in the last 3 years. These are not small inaccuracies. Yet futures prices are being determined by these narratives. ---------------**Real Estate Espresso Podcast:** Spotify: [The Real Estate Espresso Podcast](https://open.spotify.com/show/3GvtwRmTq4r3es8cbw8jW0?si=c75ea506a6694ef1)   iTunes: [The Real Estate Espresso Podcast](https://podcasts.apple.com/ca/podcast/the-real-estate-espresso-podcast/id1340482613)   Website: [www.victorjm.com](http://www.victorjm.com)   LinkedIn: [Victor Menasce](http://www.linkedin.com/in/vmenasce)   YouTube: [The Real Estate Espresso Podcast](http://www.youtube.com/@victorjmenasce6734)   Facebook: [www.facebook.com/realestateespresso](http://www.facebook.com/realestateespresso)   Email: [podcast@victorjm.com](mailto:podcast@victorjm.com)  **Y Street Capital:** Website: [www.ystreetcapital.com](http://www.ystreetcapital.com)   Facebook: [www.facebook.com/YStreetCapital](https://www.facebook.com/YStreetCapital)   Instagram: [@ystreetcapital](http://www.instagram.com/ystreetcapital)  

Recent geopolitical events, including the Israeli attack on Doha and Russian drones entering Polish airspace, have influenced energy markets. On the other hand, the International Energy Agency's (IEA) latest report suggest a potential surplus. Please note: this podcast is provided for information purposes only and should not be construed as an offer, or a solicitation of an offer, to buy or sell financial instruments. This podcast does not constitute a personal recommendation and is not investment advice. Investec

In this episode of Energy Newsbeat Daily Standup, hosts Stuart Turley and Michael Tanner unpack why America's aging grid nearing collapse is actually great news for savvy investors. They explore the rising strain from AI, EVs, and outdated infrastructure, while spotlighting trillion-dollar opportunities in behind-the-meter tech like battery storage and microgrids. The duo also breaks down Fed rate cut expectations, California's pipeline mess, the IEA's retreat on peak oil forecasts, and global energy policy contradictions from Brussels to Beijing. Energy markets are shifting—this episode tells you where the smart money's headed.Subscribe to Our Substack For Daily InsightsWant to Add Oil & Gas To Your Portfolio? Fill Out Our Oil & Gas Portfolio SurveyNeed Power For Your Data Center, Hospital, or Business?Follow Stuart On LinkedIn: https://www.linkedin.com/in/stuturley/ and Twitter: https://twitter.com/STUARTTURLEY16Follow Michael On LinkedIn: https://www.linkedin.com/in/michaelta... and Twitter: https://twitter.com/mtanner_1Timestamps:00:00 - Intro00:14 - America's Grid is Nearing Its Breaking Point04:38 - $14 Trillion Stock Rally Expects a Fed Cut: What Happens If They Only Get a Quarter Point?09:37 - California Legislators Strike Last-Minute Deal to Help Oil Industry but Limit Offshore Drilling11:49 - US urges EU to ditch Russian oil and gas faster13:09 - IEA Prepares to Walk Back Predictions of Peak Oil and Gas Demand16:12 - USA EIA Reveals Latest Brent Oil Price Forecast22:08 - Markets Update23:56 - Rig Count Update23:58. - Frac Count Update25:18 - OutroLinks to articles discussed:America's Grid is Nearing Its Breaking Point$14 Trillion Stock Rally Expects a Fed Cut: What Happens If They Only Get a Quarter Point?California Legislators Strike Last-Minute Deal to Help Oil Industry but Limit Offshore DrillingUS urges EU to ditch Russian oil and gas fasterIEA Prepares to Walk Back Predictions of Peak Oil and Gas DemandUSA EIA Reveals Latest Brent Oil Price Forecast

WATCH the video on Substack by clicking the play button above or on YouTube (here).STREAM audio only on Apple Podcasts (here), Spotify (here), or your favorite podcast player app.As all of you that have been watching our video podcasts or reading our posts over the years by now surely know, our focus at Super-Spiked and at Veriten has been on the long-term outlook for the energy sector, not the shorter-term oil price guessing game. But in recent weeks, we have not been able to resist weighing in on what we think is an excessively bearish consensus view of oil prices—the perceived massive oil glut—that has been weighing heavily on energy equity sentiment since the early April so-called "Liberation Day" tariff announcements that coincided with OPEC+ accelerating the unwind of a series of voluntary production cuts. That double whammy has driven an overwhelming consensus sentiment to be bearish oil demand while also assuming a surge in both non-OPEC and OPEC crude supply would drive oil prices to $50 or lower in 2025. But we are now 5.5 months past that early April bearish shift, and crude oil prices, at least so far, are proving far more resilient than expected even as OPEC+ has made incremental moves to unwind production cuts. Last week in a written post (here), we linked the excessive bearish near-term sentiment to a similar overhang that exists on the long-term oil view, where there is still a lingering let's call it a "net zero world" overhang that crude oil demand will peak in coming years or at best have minimal growth. We have observed that using OPEC Research analyses, rather than the IEA as a baseline, shows far less cyclical or structural crude oil oversupply. Yes, there is a still some softness that might be expected for coming months, but nothing like the "oil glut" that everyone fears.This week we follow up on last week's written post on this topic to set the record straight on a couple of items, address pushbacks to our pushback to anti-oil and gas macro biases in short-term analyses, and raise some new points on the near- and long-term oil macro outlook. There are 4 major areas we will discuss: (1) how we are thinking about OPEC+'s quota unwind; (2) China oil demand; (3) the role of US shale going forward; and (4) is there any chance the oil glut bears could still be proven correct.

APAC stocks followed suit to the mixed performance stateside, where the S&P 500 and Nasdaq printed fresh record highs.US President Trump's administration appealed the court ruling blocking the removal of Fed Governor Cook.US Senate Republicans are aiming to confirm President Trump's temporary Federal Reserve pick Stephen Miran as soon as Monday, according to Politico, citing two sourcesEU is reportedly very unlikely to impose crippling tariffs on India or China, the main buyers of Russian oil, as US President Trump urged the bloc to do so, according to Reuters citing EU sources.European equity futures indicate a flat cash market open with Euro Stoxx 50 futures U/C after the cash market closed with losses of 0.1% on Wednesday.Looking ahead, highlights include US CPI (Aug) & Jobless Claims, ECB Policy Announcement & Press Conference, CBRT Announcement, IEA & OPEC Monthly Report, Supply from Italy and the US, and Earnings from Adobe.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

According to the International Energy Agency's (IEA) World Outlook, the clean energy transition and the rise of electric vehicles (EVs) could lead global demand for fossil fuels to peak before 2030. As nations worldwide shift away from fossil-fuelled engines and towards an electric future, automakers are making a shift of their own, starting with their machine setups. Here, Swetapadma Mohanty, Senior Development Engineer, Gear Machining at Sandvik Coromant, explores the machining methods that will prove key to the automotive industry's electric future. Another prediction made by the IEA is that, by 2030, the global electric car stock will expand to almost 350 million vehicles. That's more than 60% of vehicles sold. To accommodate the rise in EVs, automakers are turning to alternative machining methods. One such method is power skiving. Common gear machining challenges Before diving into power skiving and its machining considerations, let's think about the common challenges associated with gear machining. The machining of gears for internal combustion engine (ICE) vehicles and EVs can differ in certain aspects due to the distinct characteristics and requirements of these two types of vehicles. For instance, while ICE vehicles often have complex multi-speed transmissions to optimise power delivery, EVs typically have a single-speed or limited number of fixed gear ratios. Other distinguishing features include torque characteristics, noise and vibration considerations and weight and size constraints. Machining gears, for any vehicle type, presents several machining challenges. To ensure proper meshing and transmission accuracy, gears require tight tolerances with high machining precision. Gears must also be designed to minimise noise and vibrations during operation in order to maintain batch consistency and ensure tool maintenance is key to achieving high production volumes. Popular gear machining methods include hobbing, milling, shaping and broaching. However, these methods often have limitations such as lower flexibility in handling various gear types, longer cycle times and challenges with specific gear geometries. Hobbing is particularly popular for cutting spur and helical gears and is most suited to smaller production runs and for producing gears with various tooth profiles. For mass production, gear shaping is a preferred method as it can achieve high dimensional accuracy in shorter cycle times. But these machining methods are incredibly specialist. Broaching and hobbing, for instance, must be carried out on a specialist machine, with a totally different machine required for shaping. Then there are all the other steps required for successful gear production — milling, turning, finishing, quality inspection and so on. What does that mean for manufacturers? Multiple machines set ups, limited flexibility, lengthened lead times and a costly machining process can all be consequences of a gear machining process that's not catered to our increasingly electrified world. Enter power skiving. If we're to get 350 million EVs on our roads by 2030, automakers must turn to machining methods that can accommodate. This is where power skiving comes into play. As a continuous process that uses a specialised cutting tool to remove material from a gear blank, power skiving boasts several benefits over traditional methods like hobbing and shaping. First, power skiving typically provides higher precision and tighter tolerances compared to traditional process. It's well-suited for producing gears with complex profiles, including helical gears and non-standard shapes. Traditional process may have limitations in achieving intricate tooth forms, especially when dealing with high helix angles or specific gear geometries. Generally, power skiving is faster than traditional gear machining processes and, as it removes only the necessary material to form the gear teeth, the waste produced is minimal. A core driver for its use in EV production is power skiving's flexibility — it's suitable for various gear applications, including those with specific performance requirements. Manufacturers can therefore adapt to different gear types more easily than they can with traditional machining methods. With reduced set ups in multitask machines with power skiving, higher quality can be reached. Crucially, power skiving is performed on a multitask machine. Performing multiple activities on a single machine will reduce set up times, improve accuracy, increase throughput and streamline programming. For those currently using multiple machines to execute traditional gear machining methods, however, upgrading to a multitask machine for power skiving requires some investment. It will be up to manufacturers to weigh up the pros and cons of their machining set-up, but there's one thing we cannot deny — the pace of electrification isn't going to slow down. To compete in an evolving, competitive market, flexibility, adaptability and process efficiency will be fundamental. Tool selection If power skiving is the right machining method for automotive's future — what are the right tool choices? Let's start with the gear milling tools themselves. Tools should have tight tolerances to ensure accurate machining and to produce gears with uniform quality. A good gear milling tool should also be heat-resistant to maintain its cutting performance and prevent premature wear, with a design that facilitates proper chip evacuation to ensure smooth cutting operations. The CoroMill®178 and CoroMill®180 family of gear milling tools meets those expectations. For internal and external gears, capable of machining both cylindrical spur and helical gears from roughing to finishing, CoroMill® 178 is a key part of a successful power skiving setup. It is best used in applications where high-volume, high-rpm machining with long tool life is required, while CoroMill® 180 is ideal for general use on shoulders or small diameters. These tools offer the highest tool accuracy, regarding run-out and pitch, compared with indexable tools, providing a superior finishing profile of the gear and spline. In one customer success case, by replacing a traditional process with power skiving using CoroMill® 178, cutting time was reduced and tool life increased significantly. With annual growth in production, the customer was able to save over 100 hours of machining time each year. It's not just about cutting tools with Sandvik Coromant. Customers receive tooling and application support, along with a service offering that includes technical feasibility consultancy. For example, our ESCO software is another vital component of our power skiving portfolio, enabling high-quality and precise production of power skiving tools. InvoMilling® is a vital part of Sandvik Coromant's gear machining portfolio. As part of the CoroPlus® Tool Path software, InvoMilling® is a process used for machining external gears, splines, and straight bevel gears with exceptional flexibility. This makes it highly suitable for small batch production and situations where short lead times are essential. The solution takes advantage of multitasking machines and machining centres' capability to produce various gear profiles using the same set of tools. As the world prepares for an electrified future, automakers must consider their manufacturing techniques. While traditional gear machining methods have long served the industry, thriving in a changing and increasingly competitive environment requires flexibility. Power skiving provides that flexible, adaptable approach — all while delivering finished components of the highest quality. As market leader, Sandvik Coromant is also focusing on high-level sustainable Power skiving tools and reducing CO2 footprints.

After a summer break, Peter and Jackie are back with their weekly podcast. This week, they catch up on the events and news headlines from the summer, including: Geoeconomics – recap examples where countries use economic tools to influence foreign affairs – as well as more moves towards state capitalism by the United States, where the government exercises more control over institutions and companies. Canadian oil patch M&A news. Updates regarding the federal government's Bill C-5 and its plans for advancing nation-building projects. Tariff negotiation tactics, including news that Canada is removing countervailing tariffs on the United States.  The United States is exerting more influence over the International Energy Agency (IEA), with the organization planning to reintroduce the Current Policies Scenario in the next World Energy Outlook to be released in the fall of 2025. Content referenced in this podcast: CTV, “Hodgeson ‘hopeful' first batch of major projects announcements to start in the fall” (August 20, 2025) Calgary Herald, “Varcoe: Carney has opened the door to Canadian LNG exports — one closed by Trudeau government, says Liberal natural resources minister” (August 27, 2025) The Vassy Kapelos Show, “I know there are buyers: Federal Energy Minister bullish on LNG as a nation-building project” (August 12, 2025) Oilprice.com, “Republicans Move to Cut U.S. Funding for the IEA” (July 24, 2025) E&ENEWS by Politico, “Trump team pushes for ouster of top IEA official” (August 7, 2025) Please review our disclaimer at: https://www.arcenergyinstitute.com/disclaimer/ Check us out on social media: X (Twitter): @arcenergyinstLinkedIn: @ARC Energy Research Institute Subscribe to ARC Energy Ideas PodcastApple PodcastsAmazon MusicSpotify

In this episode of the Energy Newsbeat Daily Standup - Weekly Recap, Stuart Turley and Michael Tanner break down why model-based oil forecasts consistently miss the mark, highlighting Irina Slav's takedown of flawed IEA predictions. They dive into Fed Chair Powell's Jackson Hole speech and its implications for oil and gas capital markets, LNG export-driven shale growth, the myth of peak Permian, and ERCOT's $14B clean energy project cancellations. From misguided net-zero assumptions to underreported system costs in renewables, this episode covers the real data behind energy trends and what investors should really be watching.Subscribe to Our Substack For Daily InsightsWant to Add Oil & Gas To Your Portfolio? Fill Out Our Oil & Gas Portfolio SurveyNeed Power For Your Data Center, Hospital, or Business?Follow Stuart On LinkedIn: https://www.linkedin.com/in/stuturley/ and Twitter: https://twitter.com/STUARTTURLEY16Follow Michael On LinkedIn: https://www.linkedin.com/in/michaelta... and Twitter: https://twitter.com/mtanner_1Timestamps:00:00 - Intro00:14 - What Does Powell's Comments in Jackson Hole Mean to the Oil and Gas Markets and Investors?03:40 - Surging US LNG Exports Fuel Growth in US Shale08:13 - ERCOT Project Cancellations Reached a Record in Q2 2025, and What is Next?10:43 - The True Cost of Renewable Energy and the Impact on Consumers' Electrical Bills13:33 - Why Model-Based Oil Forecasts Keep Missing the Mark18:13 - OutroLinks to articles discussed:What Does Powell's Comments in Jackson Hole Mean to the Oil and Gas Markets and Investors?Surging US LNG Exports Fuel Growth in US ShaleERCOT Project Cancellations Reached a Record in Q2 2025, and What is Next?The True Cost of Renewable Energy and the Impact on Consumers' Electrical BillsWhy Model-Based Oil Forecasts Keep Missing the Mark

In this episode of Energy Newsbeat Daily Standup Stuart Turley breaks down the hidden costs of renewable energy and its real impact on consumer electricity bills, using EU, UK, and ERCOT examples. He highlights Doug Sheridan's call for more baseload gas and nuclear, critiques flawed oil demand forecasts from the IEA, and reviews Irina Slav's takedown of politicized modeling. Plus, he spotlights record U.S. natural gas consumption projected for 2025 and analyzes how BlackRock's gas deal boosts Aramco's financial strength.Subscribe to Our Substack For Daily InsightsWant to Add Oil & Gas To Your Portfolio? Fill Out Our Oil & Gas Portfolio SurveyNeed Power For Your Data Center, Hospital, or Business?Follow Stuart On LinkedIn: https://www.linkedin.com/in/stuturley/ and Twitter: https://twitter.com/STUARTTURLEY16Follow Michael On LinkedIn: https://www.linkedin.com/in/michaelta... and Twitter: https://twitter.com/mtanner_1Timestamps:00:00 - Intro00:17 - The True Cost of Renewable Energy and the Impact on Consumers' Electrical Bills03:11 - Climate change supporters and their media try to hit Net Zero by 2050, but at what cost – Doug Sheridan04:58 - Why Model-Based Oil Forecasts Keep Missing the Mark09:39 - EIA expects record U.S. natural gas consumption in 202511:26 - BlackRock Gas Deal Shores Up Aramco's Financial Firepower13:02 - OutroLinks to articles discussed:The True Cost of Renewable Energy and the Impact on Consumers' Electrical BillsClimate change supporters and their media try to hit Net Zero by 2050, but at what cost – Doug SheridanWhy Model-Based Oil Forecasts Keep Missing the MarkEIA expects record U.S. natural gas consumption in 2025BlackRock Gas Deal Shores Up Aramco's Financial Firepower

WATCH the video on Substack by clicking the play button above or on YouTube (here).STREAM audio only on Apple Podcasts (here), Spotify (here), or your favorite podcast player app.We have a bonus Super-Spiked video podcast on a week we were not expecting to publish due to a college drop off. But last weekend we couldn't resist digging into trying to understand why crude oil prices have been far more resilient in the face of unexpected OPEC quota increases and a seemingly lackluster economic backdrop. Our punchline is that while we agree there is risk of oil price softness in the back-half of this year and early 2026, underlying crude oil supply/demand balances are not anywhere near as oversupplied as consensus fears. We believe fears of a crash and potential extended bear market are way overdone. We are also gaining confidence that by the time we get to 2H2026 and 2027, oil price risk shifts more meaningfully to the upside. The main points of difference in our more constructive outlook are (1) to disaggregate black crude oil from the more widely reported and followed overall liquids figures; and (2) to give greater consideration to OPEC Research's Monthly Oil Market Report versus the more broadly used equivalent report (Oil Market Report) from the IEA. Over the past month, we have published several posts (here, here, and here) that have examined the long-term outlook from various macro forecasting agencies, consultants, and oil companies. We conclude OPEC Research leads the pack on being most realistic and pragmatic and was least impacted by “net zero / energy transition” madness of the prior 4-5 years. That doesn't mean they are necessarily better at short-term supply/demand balances, but we don't think they should be entirely ignored or dismissed either. As a reminder, at Super-Spiked and Veriten, our focus is on the long-term outlook for energy markets and companies. We have zero interest in joining the short-term oil price guessing game that the Street and others tend to focus on. But in this case, the prevailing bearish narrative around crude oil is so pronounced and at odds with what we are seeing, we thought it worth commenting. It remains our view that prudent risk management suggests oil companies and investors should always be prepared for the potential to have a “normal” trough, which we would describe as low $50s for a 12-month period. Our message today is not to ignore that long-standing advice. But rather to recognize that sentiment is likely way too bearish and that medium- and longer-term risks are skewed toward better outcomes than consensus narratives suggest. Exhibit 1: Underlying “black crude oil” balances using OPEC's MOMR appears significantly less bearish than implied “liquids” oversupply using IEA OMR balancesSource: IEA, OPEC, Veriten.

Esta semana en Gandini Análisis pongo el foco en el mercado del petróleo a partir de la advertencia de la IEA sobre el aumento histórico de la producción en 2025. Analizo no solo lo que está ocurriendo actualmente en este mercado, sinotambién cuáles son las expectativas para 2026Link informe IEA: https://www.iea.org/reports/oil-market-report-august-2025Suscríbanse a mi newsletter para contenido exclusivo: https://gandinianalisis.substack.com/subscribeNota importante: Ningún episodio de este podcast ni las opiniones expresadas en él deben interpretarse como recomendaciones de inversión.

WATCH the video on Substack by clicking the play button above or on YouTube (here).STREAM audio only on Apple Podcasts (here), Spotify (here), or your favorite podcast player app.DOWNLOAD a pdf of the slide deck by clicking the blue Download button below.This week we extend our “Obliterating Peak Oil Demand” series to take on other mainstream macro narratives with a focus on natural gas. We have to admit, it did not even cross our mind that the outlook for global gas demand was anything other than continued growth for the foreseeable future. In fact, there are a number of high-profile macro forecasters projecting a permanent peak in global natural gas demand by as soon as 2030 and in some cases the mid-2030s. This, in our view, is pure insanity. We will take the over, and in fact the way over, that global natural gas demand will grow for many, many decades into the future.Perhaps we were lulled into a false sense of presumed natural gas growth optimism based on what we think is a broad-based acceptance of US natural gas growth due to LNG export expansion and now AI-driven power demand growth. But we are realizing that a positive view of US growth is not necessarily extending to a positive view on global natural gas growth for some of the major macro forecasting agencies.The final topic we discuss this week is a warning to ignore energy macro forecasters that merely tweak prior "transition" assumptions by pushing them slightly out in time. It was an article in the Financial Times this past week that caught our attention on this front and we would strongly encourage energy executives, investors, and board members to simply ignore and pushback on energy macro outlooks that are not grounded in energy's natural hierarchy of needs, which acknowledges that energy availability and reliability is all everyone everywhere cares about. Macro forecasts that prioritize counting carbon should not be the basis for how to think about capital allocation.Before we dig in, two reminders. If you are listening to this on Spotify or Apple Podcasts, there is a corresponding video you can find on YouTube (here), Substack (here), or Veriten's website (here). And second, this will be our final Super-Spiked of the summer. We will return after Labor Day.Exhibit 1: We do not agree with energy macro forecasting groups that are calling for a peak in global gas demand by 2030 or 2035Source: Energy Institute, IEA, OPEC, Veriten.Exhibit 2: We do not agree with the projected sharp slowdown in global gas consumption growth made by some leading energy macro forecastersSource: Energy Institute, IEA, OPEC, Veriten.Peak natural gas even more non-sensical than oil* The idea that global natural gas demand will peak, or even slow, by 2030 is even more far-fetched than the oil debate.* Global power demand expected to grow at a healthy clip.* 24x7x365 requirement supports base-load natural gas, coal, nuclear.* Geothermal, while worth studying, is still unproven at scale; hydro is niche.* Solar + batteries will grow in areas with high solar radiation. Wind is also location specific.* Natural gas does need to compete on overall price/cost economics with alternatives.* Access to capital matters in natural gas, which lacks the mega caps seen in the oil value chain.Don't fall for “delayed transition” narratives* There is now broad-based recognition that the “easy energy transition”” is a bad joke that has adverse societal consequences.* Our Obliterating Peak Oil Demand series, which we have extended to coal and natural gas, illustrates the absurdity.* The mindset that everyone deserves to be energy rich is gaining in acceptance.* What to watch: (1) With upcoming high profile energy outlooks, watch for “delayed transition” language, which is a cop out. (2) If you are a corporate executive, board member, or investor, don't fall for it in making capital allocation decisions.Exhibit 3: Don't fall for “delayed transition” narrativesSource: Financial Times.⚡️ On A Personal Note: Summer Reading List

國際能源署 (IEA) 對石油市場的預測是什麼？IEA 上調了2025年和2026年全球石油供應的預測，預計供應量將增加。同時，IEA 也下調了全球石油需求增長預測，原因包括中國、印度和巴西等地的經濟疲弱 。這導致全球商業原油庫存已升至46個月以來的高位 。為什麼OPEC產油國對減產的立場不一致？ 沙地阿拉伯傾向於減產以穩定油價。然而，部分 OPEC 成員國不願意犧牲它們的市場佔有率 。如果無法落實減產，油價短期內可能會進一步回落，直接影響中東產油國的收入。美國在液化天然氣 (LNG) 市場的地位如何？ 今年頭八個月，美國的液化天然氣出口量按年增加了22%，再次成為全球最大的液化天然氣出口國。其中，歐洲吸納了美國三分之二的出口，原因在於再生能源供應不穩定以及俄羅斯供應的減少 。美國液化天然氣出口的增長對美國國內有什麼影響？ 由於出口需求，美國國內的天然氣供應面臨壓力，導致能源成本有所增加 。國內住宅、商業和工業用天然氣的價格平均上漲了27% 。中東主權基金目前的投資策略有什麼改變？中東的五大主權基金，其資產規模合計超過4.2萬億美元 。在過去一年，他們加快了在歐洲和美國的基建、能源轉型和科技創投等領域的投資 。與此同時，他們也縮減了在中國部分行業的投資比例 。為什麼中東主權基金會減少在中國的投資？ 其中一個解釋是，中東主權基金現在會主動參與企業的管理和決策 。然而，在中國市場，任何達到一定規模的企業都不太可能完全自主發展方向 。這一點會影響投資者的決定 。 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leesimon.substack.com/subscribe

Summer rewind: Greg Lindsay is an urban tech expert and a Senior Fellow at MIT. He's also a two-time Jeopardy champion and the only human to go undefeated against IBM's Watson. Greg joins thinkenergy to talk about how artificial intelligence (AI) is reshaping how we manage, consume, and produce energy—from personal devices to provincial grids, its rapid growth to the rising energy demand from AI itself. Listen in to learn how AI impacts our energy systems and what it means individually and industry-wide. Related links: ●       Greg Lindsay website: https://greglindsay.org/ ●       Greg Lindsay on LinkedIn: https://www.linkedin.com/in/greg-lindsay-8b16952/ ●       International Energy Agency (IEA): https://www.iea.org/ ●       Trevor Freeman on LinkedIn: https://www.linkedin.com/in/trevor-freeman-p-eng-cem-leed-ap-8b612114/ ●       Hydro Ottawa: https://hydroottawa.com/en    To subscribe using Apple Podcasts: https://podcasts.apple.com/us/podcast/thinkenergy/id1465129405   To subscribe using Spotify: https://open.spotify.com/show/7wFz7rdR8Gq3f2WOafjxpl   To subscribe on Libsyn: http://thinkenergy.libsyn.com/ --- Subscribe so you don't miss a video: https://www.youtube.com/user/hydroottawalimited   Follow along on Instagram: https://www.instagram.com/hydroottawa   Stay in the know on Facebook: https://www.facebook.com/HydroOttawa   Keep up with the posts on X: https://twitter.com/thinkenergypod --- Transcript: Trevor Freeman  00:00 Hi everyone. Well, summer is here, and the think energy team is stepping back a bit to recharge and plan out some content for the next season. We hope all of you get some much needed downtime as well, but we aren't planning on leaving you hanging over the next few months, we will be re releasing some of our favorite episodes from the past year that we think really highlight innovation, sustainability and community. These episodes highlight the changing nature of how we use and manage energy, and the investments needed to expand, modernize and strengthen our grid in response to that. All of this driven by people and our changing needs and relationship to energy as we move forward into a cleaner, more electrified future, the energy transition, as we talk about many times on this show. Thanks so much for listening, and we'll be back with all new content in September. Until then, happy listening.   Trevor Freeman  00:55 Welcome to think energy, a podcast that dives into the fast changing world of energy through conversations with industry leaders, innovators and people on the front lines of the energy transition. Join me, Trevor Freeman, as I explore the traditional, unconventional and up and coming facets of the energy industry. If you have any thoughts feedback or ideas for topics we should cover, please reach out to us at think energy at hydro ottawa.com, Hi everyone. Welcome back. Artificial intelligence, or AI, is a term that you're likely seeing and hearing everywhere today, and with good reason, the effectiveness and efficiency of today's AI, along with the ever increasing applications and use cases mean that in just the past few years, AI went from being a little bit fringe, maybe a little bit theoretical to very real and likely touching everyone's day to day lives in ways that we don't even notice, and we're just at the beginning of what looks to be a wave of many different ways that AI will shape and influence our society and our lives in the years to come. And the world of energy is no different. AI has the potential to change how we manage energy at all levels, from our individual devices and homes and businesses all the way up to our grids at the local, provincial and even national and international levels. At the same time, AI is also a massive consumer of energy, and the proliferation of AI data centers is putting pressure on utilities for more and more power at an unprecedented pace. But before we dive into all that, I also think it will be helpful to define what AI is. After all, the term isn't new. Like me, many of our listeners may have grown up hearing about Skynet from Terminator, or how from 2001 A Space Odyssey, but those malignant, almost sentient versions of AI aren't really what we're talking about here today. And to help shed some light on both what AI is as well as what it can do and how it might influence the world of energy, my guest today is Greg Lindsay, to put it in technical jargon, Greg's bio is super neat, so I do want to take time to run through it properly. Greg is a non resident Senior Fellow of MIT's future urban collectives lab Arizona State University's threat casting lab and the Atlantic Council's Scowcroft center for strategy and security. Most recently, he was a 2022-2023 urban tech Fellow at Cornell Tech's Jacobs Institute, where he explored the implications of AI and augmented reality at an urban scale. Previously, he was an urbanist in resident, which is a pretty cool title, at BMW minis urban tech accelerator, urban X, as well as the director of Applied Research at Montreal's new cities and Founding Director of Strategy at its mobility focused offshoot, co motion. He's advised such firms as Intel, Samsung, Audi, Hyundai, IKEA and Starbucks, along with numerous government entities such as 10 Downing Street, us, Department of Energy and NATO. And finally, and maybe coolest of all, Greg is also a two time Jeopardy champion and the only human to go undefeated against IBM's Watson. So on that note, Greg Lindsey, welcome to the show.   Greg Lindsay  04:14 Great to be here. Thanks for having me. Trevor,   Trevor Freeman  04:16 So Greg, we're here to talk about AI and the impacts that AI is going to have on energy, but AI is a bit of one of those buzzwords that we hear out there in a number of different spheres today. So let's start by setting the stage of what exactly we're talking about. So what do we mean when we say AI or artificial intelligence?   Speaker 1  04:37 Well, I'd say the first thing to keep in mind is that it is neither artificial nor intelligence. It's actually composites of many human hands making it. And of course, it's not truly intelligent either. I think there's at least two definitions for the layman's purposes. One is statistical machine learning. You know that is the previous generation of AI, we could say, doing deep, deep statistical analysis, looking for patterns fitting to. Patterns doing prediction. There's a great book, actually, by some ut professors at monk called prediction machines, which that was a great way of thinking about machine learning and sense of being able to do large scale prediction at scale. And that's how I imagine hydro, Ottawa and others are using this to model out network efficiencies and predictive maintenance and all these great uses. And then the newer, trendier version, of course, is large language models, your quads, your chat gpts, your others, which are based on transformer models, which is a whole series of work that many Canadians worked on, including Geoffrey Hinton and others. And this is what has produced the seemingly magical abilities to produce text and images on demand and large scale analysis. And that is the real power hungry beast that we think of as AI today.   Trevor Freeman  05:42 Right! So different types of AI. I just want to pick those apart a little bit. When you say machine learning, it's kind of being able to repetitively look at something or a set of data over and over and over again. And because it's a computer, it can do it, you know, 1000s or millions of times a second, and learn what, learn how to make decisions based on that. Is that fair to say?   Greg Lindsay  06:06 That's fair to say. And the thing about that is, is like you can train it on an output that you already know, large language models are just vomiting up large parts of pattern recognition, which, again, can feel like magic because of our own human brains doing it. But yeah, machine learning, you can, you know, you can train it to achieve outcomes. You can overfit the models where it like it's trained too much in the past, but, yeah, it's a large scale probabilistic prediction of things, which makes it so powerful for certain uses.   Trevor Freeman  06:26 Yeah, one of the neatest explanations or examples I've seen is, you know, you've got these language models where it seems like this AI, whether it's chat, DBT or whatever, is writing really well, like, you know, it's improving our writing. It's making things sound better. And it seems like it's got a brain behind it, but really, what it's doing is it's going out there saying, What have millions or billions of other people written like this? And how can I take the best things of that? And it can just do that really quickly, and it's learned that that model, so that's super helpful to understand what we're talking about here. So obviously, in your work, you look at the impact of AI on a number of different aspects of our world, our society. What we're talking about here today is particularly the impact of AI when it comes to energy. And I'd like to kind of bucketize our conversation a little bit today, and the first area I want to look at is, what will ai do when it comes to energy for the average Canadian? Let's say so in my home, in my business, how I move around? So I'll start with that. It's kind of a high level conversation. Let's start talking about the different ways that AI will impact you know that our average listener here?   Speaker 1  07:41 Um, yeah, I mean, we can get into a discussion about what it means for the average Canadian, and then also, of course, what it means for Canada in the world as well, because I just got back from South by Southwest in Austin, and, you know, for the second, third year in row, AI was on everyone's lips. But really it's the energy. Is the is the bottleneck. It's the forcing factor. Everyone talked about it, the fact that all the data centers we can get into that are going to be built in the direction of energy. So, so, yeah, energy holds the key to the puzzle there. But, um, you know, from the average gain standpoint, I mean, it's a question of, like, how will these tools actually play out, you know, inside of the companies that are using this, right? And that was a whole other discussion too. It's like, okay, we've been playing around with these tools for two, three years now, what do they actually use to deliver value of your large language model? So I've been saying this for 10 years. If you look at the older stuff you could start with, like smart thermostats, even look at the potential savings of this, of basically using machine learning to optimize, you know, grid optimize patterns of usage, understanding, you know, the ebbs and flows of the grid, and being able to, you know, basically send instructions back and forth. So you know there's stats. You know that, basically you know that you know you could save 10 to 25% of electricity bills. You know, based on this, you could reduce your heating bills by 10 to 15% again, it's basically using this at very large scales of the scale of hydro Ottawa, bigger, to understand this sort of pattern usage. But even then, like understanding like how weather forecasts change, and pulling that data back in to basically make fine tuning adjustments to the thermostats and things like that. So that's one stands out. And then, you know, we can think about longer term. I mean, yeah, lots have been lots has been done on imagining, like electric mobility, of course, huge in Canada, and what that's done to sort of change the overall energy mix virtual power plants. This is something that I've studied, and we've been writing about at Fast Company. At Fast Company beyond for 20 years, imagining not just, you know, the ability to basically, you know, feed renewable electricity back into the grid from people's solar or from whatever sources they have there, but the ability of utilities to basically go in and fine tune, to have that sort of demand shaping as well. And then I think the most interesting stuff, at least in demos, and also blockchain, which has had many theoretical uses, and I've got to see a real one. But one of the best theoretical ones was being able to create neighborhood scale utilities. Basically my cul de sac could have one, and we could trade clean electrons off of our solar panels through our batteries and home scale batteries, using Blockchain to basically balance this out. Yeah, so there's lots of potential, but yeah, it comes back to the notion of people want cheaper utility bills. I did this piece 10 years ago for the Atlantic Council on this we looked at a multi country survey, and the only reason anybody wanted a smart home, which they just were completely skeptical about, was to get those cheaper utility bills. So people pay for that.   Trevor Freeman  10:19 I think it's an important thing to remember, obviously, especially for like the nerds like me, who part of my driver is, I like that cool new tech. I like that thing that I can play with and see my data. But for most people, no matter what we're talking about here, when it comes to that next technology, the goal is make my life a little bit easier, give me more time or whatever, and make things cheaper. And I think especially in the energy space, people aren't putting solar panels on their roof because it looks great. And, yeah, maybe people do think it looks great, but they're putting it up there because they want cheaper electricity. And it's going to be the same when it comes to batteries. You know, there's that add on of resiliency and reliability, but at the end of the day, yeah, I want my bill to be cheaper. And what I'm hearing from you is some of the things we've already seen, like smart thermostats get better as AI gets better. Is that fair to say?   Greg Lindsay  11:12 Well, yeah, on the machine learning side, that you know, you get ever larger data points. This is why data is the coin of the realm. This is why there's a race to collect data on everything. Is why every business model is data collection and everything. Because, yes, not only can they get better, but of course, you know, you compile enough and eventually start finding statistical inferences you never meant to look for. And this is why I've been involved. Just as a side note, for example, of cities that have tried to implement their own data collection of electric scooters and eventually electric vehicles so they could understand these kinds of patterns, it's really the key to anything. And so it's that efficiency throughput which raises some really interesting philosophical questions, particularly about AI like, this is the whole discussion on deep seek. Like, if you make the models more efficient, do you have a Jevons paradox, which is the paradox of, like, the more energy you save through efficiency, the more you consume because you've made it cheaper. So what does this mean that you know that Canadian energy consumption is likely to go up the cleaner and cheaper the electrons get. It's one of those bedeviling sort of functions.   Trevor Freeman  12:06 Yeah interesting. That's definitely an interesting way of looking at it. And you referenced this earlier, and I will talk about this. But at the macro level, the amount of energy needed for these, you know, AI data centers in order to do all this stuff is, you know, we're seeing that explode.   Greg Lindsay  12:22 Yeah, I don't know that. Canadian statistics my fingertips, but I brought this up at Fast Company, like, you know, the IEA, I think International Energy Agency, you know, reported a 4.3% growth in the global electricity grid last year, and it's gonna be 4% this year. That does not sound like much. That is the equivalent of Japan. We're adding in Japan every year to the grid for at least the next two to three years. Wow. And that, you know, that's global South, air conditioning and other needs here too, but that the data centers on top is like the tip of the spear. It's changed all this consumption behavior, where now we're seeing mothballed coal plants and new plants and Three Mile Island come back online, as this race for locking up electrons, for, you know, the race to build God basically, the number of people in AI who think they're literally going to build weekly godlike intelligences, they'll, they won't stop at any expense. And so they will buy as much energy as they can get.   Trevor Freeman  13:09 Yeah, well, we'll get to that kind of grid side of things in a minute. Let's stay at the home first. So when I look at my house, we talked about smart thermostats. We're seeing more and more automation when it comes to our homes. You know, we can program our lights and our door locks and all this kind of stuff. What does ai do in order to make sure that stuff is contributing to efficiency? So I want to do all those fun things, but use the least amount of energy possible.   Greg Lindsay  13:38 Well, you know, I mean, there's, again, there's various metrics there to basically, sort of, you know, program your lights. And, you know, Nest is, you know, Google. Nest is an example of this one, too, in terms of basically learning your ebb and flow and then figuring out how to optimize it over the course of the day. So you can do that, you know, we've seen, again, like the home level. We've seen not only the growth in solar panels, but also in those sort of home battery integration. I was looking up that Tesla Powerwall was doing just great in Canada, until the last couple of months. I assume so, but I it's been, it's been heartening to see that, yeah, this sort of embrace of home energy integration, and so being able to level out, like, peak flow off the grid, so Right? Like being able to basically, at moments of peak demand, to basically draw on your own local resources and reduce that overall strain. So there's been interesting stuff there. But I want to focus for a moment on, like, terms of thinking about new uses. Because, you know, again, going back to how AI will influence the home and automation. You know, Jensen Wong of Nvidia has talked about how this will be the year of robotics. Google, Gemini just applied their models to robotics. There's startups like figure there's, again, Tesla with their optimists, and, yeah, there's a whole strain of thought that we're about to see, like home robotics, perhaps a dream from like, the 50s. I think this is a very Disney World esque Epcot Center, yeah, with this idea of jetsy, yeah, of having home robots doing work. You can see concept videos a figure like doing the actual vacuuming. I mean, we invented Roombas to this, but, but it also, I, you know, I've done a lot of work. Our own thinking around electric delivery vehicles. We could talk a lot about drones. We could talk a lot about the little robots that deliver meals on the sidewalk. There's a lot of money in business models about increasing access and people needing to maybe move less, to drive and do all these trips to bring it to them. And that's a form of home automation, and that's all batteries. That is all stuff off the grid too. So AI is that enable those things, these things that can think and move and fly and do stuff and do services on your behalf, and so people might find this huge new source of demand from that as well.   Trevor Freeman  15:29 Yeah, that's I hadn't really thought about the idea that all the all these sort of conveniences and being able to summon them to our homes cause us to move around less, which also impacts transportation, which is another area I kind of want to get to. And I know you've, you've talked a little bit about E mobility, so where do you see that going? And then, how does AI accelerate that transition, or accelerate things happening in that space?   Greg Lindsay  15:56 Yeah, I mean, I again, obviously the EV revolutions here Canada like, one of the epicenters Canada, Norway there, you know, that still has the vehicle rebates and things. So, yeah. I mean, we've seen, I'm here in Montreal, I think we've got, like, you know, 30 to 13% of sales is there, and we've got our 2035, mandate. So, yeah. I mean, you see this push, obviously, to harness all of Canada's clean, mostly hydro electricity, to do this, and, you know, reduce its dependence on fossil fuels for either, you know, Climate Change Politics reasons, but also just, you know, variable energy prices. So all of that matters. But, you know, I think the key to, like the electric mobility revolution, again, is, is how it's going to merge with AI and it's, you know, it's not going to just be the autonomous, self driving car, which is sort of like the horseless carriage of autonomy. It's gonna be all this other stuff, you know. My friend Dan Hill was in China, and he was thinking about like, electric scooters, you know. And I mentioned this to hydro Ottawa, like, the electric scooter is one of the leading causes of how we've taken internal combustion engine vehicles offline across the world, mostly in China, and put people on clean electric motors. What happens when you take those and you make those autonomous, and you do it with, like, deep seek and some cameras, and you sort of weld it all together so you could have a world of a lot more stuff in motion, and not just this world where we have to drive as much. And that, to me, is really exciting, because that changes, like urban patterns, development patterns, changes how you move around life, those kinds of things as well. That's that might be a little farther out, but, but, yeah, this sort of like this big push to build out domestic battery industries, to build charging points and the sort of infrastructure there, I think it's going to go in direction, but it doesn't look anything like, you know, a sedan or an SUV that just happens to be electric.   Trevor Freeman  17:33 I think that's a the step change is change the drive train of the existing vehicles we have, you know, an internal combustion to a battery. The exponential change is exactly what you're saying. It's rethinking this.   Greg Lindsay  17:47 Yeah, Ramesam and others have pointed out, I mean, again, like this, you know, it's, it's really funny to see this pushback on EVs, you know. I mean, I love a good, good roar of an internal combustion engine myself, but, but like, you know, Ramesam was an energy analyst, has pointed out that, like, you know, EVS were more cost competitive with ice cars in 2018 that's like, nearly a decade ago. And yeah, the efficiency of electric motors, particularly regenerative braking and everything, it just blows the cost curves away of ice though they will become the equivalent of keeping a thorough brat around your house kind of thing. Yeah, so, so yeah, it's just, it's that overall efficiency of the drive train. And that's the to me, the interesting thing about both electric motors, again, of autonomy is like, those are general purpose technologies. They get cheaper and smaller as they evolve under Moore's Law and other various laws, and so they get to apply to more and more stuff.   Trevor Freeman  18:32 Yeah. And then when you think about once, we kind of figure that out, and we're kind of already there, or close to it, if not already there, then it's opening the door to those other things you're talking about. Of, well, do we, does everybody need to have that car in their driveway? Are we rethinking how we're actually just doing transportation in general? And do we need a delivery truck? Or can it be delivery scooter? Or what does that look like?   Greg Lindsay  18:54 Well, we had a lot of those discussions for a long time, particularly in the mobility space, right? Like, and like ride hailing, you know, like, oh, you know, that was always the big pitch of an Uber is, you know, your car's parked in your driveway, like 94% of the time. You know, what happens if you're able to have no mobility? Well, we've had 15 years of Uber and these kinds of services, and we still have as many cars. But people are also taking this for mobility. It's additive. And I raised this question, this notion of like, it's just sort of more and more, more options, more availability, more access. Because the same thing seems to be going on with energy now too. You know, listeners been following along, like the conversation in Houston, you know, a week or two ago at Sarah week, like it's the whole notion of energy realism. And, you know, there's the new book out, more is more is more, which is all about the fact that we've never had an energy transition. We just kept piling up. Like the world burned more biomass last year than it did in 1900 it burned more coal last year than it did at the peak of coal. Like these ages don't really end. They just become this sort of strata as we keep piling energy up on top of it. And you know, I'm trying to sound the alarm that we won't have an energy transition. What that means for climate change? But similar thing, it's. This rebound effect, the Jevons paradox, named after Robert Stanley Jevons in his book The question of coal, where he noted the fact that, like, England was going to need more and more coal. So it's a sobering thought. But, like, I mean, you know, it's a glass half full, half empty in many ways, because the half full is like increasing technological options, increasing changes in lifestyle. You can live various ways you want, but, but, yeah, it's like, I don't know if any of it ever really goes away. We just get more and more stuff,   Trevor Freeman  20:22 Exactly, well. And, you know, to hear you talk about the robotics side of things, you know, looking at the home, yeah, more, definitely more. Okay, so we talked about kind of home automation. We've talked about transportation, how we get around. What about energy management? And I think about this at the we'll talk about the utility side again in a little bit. But, you know, at my house, or for my own personal use in my life, what is the role of, like, sort of machine learning and AI, when it comes to just helping me manage my own energy better and make better decisions when it comes to energy? ,   Greg Lindsay  20:57 Yeah, I mean, this is where it like comes in again. And you know, I'm less and less of an expert here, but I've been following this sort of discourse evolve. And right? It's the idea of, you know, yeah, create, create. This the set of tools in your home, whether it's solar panels or batteries or, you know, or Two Way Direct, bi directional to the grid, however it works. And, yeah, and people, you know, given this option of savings, and perhaps, you know, other marketing messages there to curtail behavior. You know? I mean, I think the short answer the question is, like, it's an app people want, an app that tell them basically how to increase the efficiency of their house or how to do this. And I should note that like, this has like been the this is the long term insight when it comes to like energy and the clean tech revolution. Like my Emery Levin says this great line, which I've always loved, which is, people don't want energy. They want hot showers and cold beer. And, you know, how do you, how do you deliver those things through any combination of sticks and carrots, basically like that. So, So, hence, why? Like, again, like, you know, you know, power walls, you know, and, and, and, you know, other sort of AI controlled batteries here that basically just sort of smooth out to create the sort of optimal flow of electrons into your house, whether that's coming drive directly off the grid or whether it's coming out of your backup and then recharging that the time, you know, I mean, the surveys show, like, more than half of Canadians are interested in this stuff, you know, they don't really know. I've got one set here, like, yeah, 61% are interested in home energy tech, but only 27 understand, 27% understand how to optimize them. So, yeah. So people need, I think, perhaps, more help in handing that over. And obviously, what's exciting for the, you know, the utility level is, like, you know, again, aggregate all that individual behavior together and you get more models that, hope you sort of model this out, you know, at both greater scale and ever more fine grained granularity there. So, yeah, exactly. So I think it's really interesting, you know, I don't know, like, you know, people have gamified it. What was it? I think I saw, like, what is it? The affordability fund trust tried to basically gamify AI energy apps, and it created various savings there. But a lot of this is gonna be like, as a combination like UX design and incentives design and offering this to people too, about, like, why you should want this and money's one reason, but maybe there's others.   Trevor Freeman  22:56 Yeah, and we talk about in kind of the utility sphere, we talk about how customers, they don't want all the data, and then have to go make their own decisions. They want those decisions to be made for them, and they want to say, look, I want to have you tell me the best rate plan to be on. I want to have you automatically switch me to the best rate plan when my consumption patterns change and my behavior chat patterns change. That doesn't exist today, but sort of that fast decision making that AI brings will let that become a reality sometime in the future,   Greg Lindsay  23:29 And also in theory, this is where LLMs come into play. Is like, you know, to me, what excites me the most about that is the first time, like having a true natural language interface, like having being able to converse with an, you know, an AI, let's hopefully not chat bot. I think we're moving out on chat bots, but some sort of sort of instantiation of an AI to be like, what plan should I be on? Can you tell me what my behavior is here and actually having some sort of real language conversation with it? Not decision trees, not event statements, not chat bots.   Trevor Freeman  23:54 Yeah, absolutely. Okay, so we've kind of teased around this idea of looking at the utility levels, obviously, at hydro Ottawa, you referenced this just a minute ago. We look at all these individual cases, every home that has home automation or solar storage, and we want to aggregate that and understand what, what can we do to help manage the grid, help manage all these new energy needs, shift things around. So let's talk a little bit about the role that AI can play at the utility scale in helping us manage the grid.   Greg Lindsay  24:28 All right? Well, yeah, there's couple ways to approach it. So one, of course, is like, let's go back to, like, smart meters, right? Like, and this is where I don't know how many hydro Ottawa has, but I think, like, BC Hydro has like, 2 million of them, sometimes they get politicized, because, again, this gets back to this question of, like, just, just how much nanny state you want. But, you know, you know, when you reach the millions, like, yeah, you're able to get that sort of, you know, obviously real time, real time usage, real time understanding. And again, if you can do that sort of grid management piece where you can then push back, it's visual game changer. But, but yeah. I mean, you know, yeah, be. See hydro is pulling in. I think I read like, like, basically 200 million data points a day. So that's a lot to train various models on. And, you know, I don't know exactly the kind of savings they have, but you can imagine there, whether it's, you know, them, or Toronto Hydro, or hydro Ottawa and others creating all these monitoring points. And again, this is the thing that bedells me, by the way, just philosophically about modern life, the notion of like, but I don't want you to be collecting data off me at all times, but look at what you can do if you do It's that constant push pull of some sort of combination of privacy and agency, and then just the notion of like statistics, but, but there you are, but, but, yeah, but at the grid level, then I mean, like, yeah. I mean, you can sort of do the same thing where, like, you know, I mean, predictive maintenance is the obvious one, right? I have been writing about this for large enterprise software companies for 20 years, about building these data points, modeling out the lifetime of various important pieces equipment, making sure you replace them before you have downtime and terrible things happen. I mean, as we're as we're discussing this, look at poor Heathrow Airport. I am so glad I'm not flying today, electrical substation blowing out two days of the world's most important hub offline. So that's where predictive maintenance comes in from there. And, yeah, I mean, I, you know, I again, you know, modeling out, you know, energy flow to prevent grid outages, whether that's, you know, the ice storm here in Quebec a couple years ago. What was that? April 23 I think it was, yeah, coming up in two years. Or our last ice storm, we're not the big one, but that one, you know, where we had big downtime across the grid, like basically monitoring that and then I think the other big one for AI is like, Yeah, is this, this notion of having some sort of decision support as well, too, and sense of, you know, providing scenarios and modeling out at scale the potential of it? And I don't think, I don't know about this in a grid case, but the most interesting piece I wrote for Fast Company 20 years ago was an example, ago was an example of this, which was a fledgling air taxi startup, but they were combining an agent based model, so using primitive AI to create simple rules for individual agents and build a model of how they would behave, which you can create much more complex models. Now we could talk about agents and then marrying that to this kind of predictive maintenance and operations piece, and marrying the two together. And at that point, you could have a company that didn't exist, but that could basically model itself in real time every day in the life of what it is. You can create millions and millions and millions of Monte Carlo operations. And I think that's where perhaps both sides of AI come together truly like the large language models and agents, and then the predictive machine learning. And you could basically hydro or others, could build this sort of deep time machine where you can model out all of these scenarios, millions and millions of years worth, to understand how it flows and contingencies as well. And that's where it sort of comes up. So basically something happens. And like, not only do you have a set of plans, you have an AI that has done a million sets of these plans, and can imagine potential next steps of this, or where to deploy resources. And I think in general, that's like the most powerful use of this, going back to prediction machines and just being able to really model time in a way that we've never had that capability before. And so you probably imagine the use is better than I.   Trevor Freeman  27:58 Oh man, it's super fascinating, and it's timely. We've gone through the last little while at hydro Ottawa, an exercise of updating our playbook for emergencies. So when there are outages, what kind of outage? What's the sort of, what are the trigger points to go from, you know, what we call a level one to a level two to level three. But all of this is sort of like people hours that are going into that, and we're thinking through these scenarios, and we've got a handful of them, and you're just kind of making me think, well, yeah, what if we were able to model that out? And you bring up this concept of agents, let's tease into that a little bit explain what you mean when you're talking about agents.   Greg Lindsay  28:36 Yeah, so agentic systems, as the term of art is, AI instantiations that have some level of autonomy. And the archetypal example of this is the Stanford Smallville experiment, where they took basically a dozen large language models and they gave it an architecture where they could give it a little bit of backstory, ruminate on it, basically reflect, think, decide, and then act. And in this case, they used it to plan a Valentine's Day party. So they played out real time, and the LLM agents, like, even played matchmaker. They organized the party, they sent out invitations, they did these sorts of things. Was very cute. They put it out open source, and like, three weeks later, another team of researchers basically put them to work writing software programs. So you can see they organized their own workflow. They made their own decisions. There was a CTO. They fact check their own work. And this is evolving into this grand vision of, like, 1000s, millions of agents, just like, just like you spin up today an instance of Amazon Web Services to, like, host something in the cloud. You're going to spin up an agent Nvidia has talked about doing with healthcare and others. So again, coming back to like, the energy implications of that, because it changes the whole pattern. Instead of huge training runs requiring giant data centers. You know, it's these agents who are making all these calls and doing more stuff at the edge, but, um, but yeah, in this case, it's the notion of, you know, what can you put the agents to work doing? And I bring this up again, back to, like, predictive maintenance, or for hydro Ottawa, there's another amazing paper called virtual in real life. And I chatted with one of the principal authors. It created. A half dozen agents who could play tour guide, who could direct you to a coffee shop, who do these sorts of things, but they weren't doing it in a virtual world. They were doing it in the real one. And to do it in the real world, you took the agent, you gave them a machine vision capability, so added that model so they could recognize objects, and then you set them loose inside a digital twin of the world, in this case, something very simple, Google Street View. And so in the paper, they could go into like New York Central Park, and they could count every park bench and every waste bin and do it in seconds and be 99% accurate. And so agents were monitoring the landscape. Everything's up, because you can imagine this in the real world too, that we're going to have all the time. AIS roaming the world, roaming these virtual maps, these digital twins that we build for them and constantly refresh from them, from camera data, from sensor data, from other stuff, and tell us what this is. And again, to me, it's really exciting, because that's finally like an operating system for the internet of things that makes sense, that's not so hardwired that you can ask agents, can you go out and look for this for me? Can you report back on this vital system for me? And they will be able to hook into all of these kinds of representations of real time data where they're emerging from, and give you aggregated reports on this one. And so, you know, I think we have more visibility in real time into the real world than we've ever had before.   Trevor Freeman  31:13 Yeah, I want to, I want to connect a few dots here for our listeners. So bear with me for a second. Greg. So for our listeners, there was a podcast episode we did about a year ago on our grid modernization roadmap, and we talked about one of the things we're doing with grid modernization at hydro Ottawa and utilities everywhere doing this is increasing the sensor data from our grid. So we're, you know, right now, we've got visibility sort of to our station level, sometimes one level down to some switches. But in the future, we'll have sensors everywhere on our grid, every switch, every device on our grid, will have a sensor gathering data. Obviously, you know, like you said earlier, millions and hundreds of millions of data points every second coming in. No human can kind of make decisions on that, and what you're describing is, so now we've got all this data points, we've got a network of information out there, and you could create this agent to say, Okay, you are. You're my transformer agent. Go out there and have a look at the run temperature of every transformer on the network, and tell me where the anomalies are, which ones are running a half a degree or two degrees warmer than they should be, and report back. And now I know hydro Ottawa, that the controller, the person sitting in the room, knows, Hey, we should probably go roll a truck and check on that transformer, because maybe it's getting end of life. Maybe it's about to go and you can do that across the entire grid. That's really fascinating,   Greg Lindsay  32:41 And it's really powerful, because, I mean, again, these conversations 20 years ago at IoT, you know you're going to have statistical triggers, and you would aggregate these data coming off this, and there was a lot of discussion there, but it was still very, like hardwired, and still very Yeah, I mean, I mean very probabilistic, I guess, for a word that went with agents like, yeah, you've now created an actual thing that can watch those numbers and they can aggregate from other systems. I mean, lots, lots of potential there hasn't quite been realized, but it's really exciting stuff. And this is, of course, where that whole direction of the industry is flowing. It's on everyone's lips, agents.   Trevor Freeman  33:12 Yeah. Another term you mentioned just a little bit ago that I want you to explain is a digital twin. So tell us what a digital twin is.   Greg Lindsay  33:20 So a digital twin is, well, the matrix. Perhaps you could say something like this for listeners of a certain age, but the digital twin is the idea of creating a model of a piece of equipment, of a city, of the world, of a system. And it is, importantly, it's physics based. It's ideally meant to represent and capture the real time performance of the physical object it's based on, and in this digital representation, when something happens in the physical incarnation of it, it triggers a corresponding change in state in the digital twin, and then vice versa. In theory, you know, you could have feedback loops, again, a lot of IoT stuff here, if you make changes virtually, you know, perhaps it would cause a change in behavior of the system or equipment, and the scales can change from, you know, factory equipment. Siemens, for example, does a lot of digital twin work on this. You know, SAP, big, big software companies have thought about this. But the really crazy stuff is, like, what Nvidia is proposing. So first they started with a digital twin. They very modestly called earth two, where they were going to model all the weather and climate systems of the planet down to like the block level. There's a great demo of like Jensen Wong walking you through a hurricane, typhoons striking the Taipei, 101, and how, how the wind currents are affecting the various buildings there, and how they would change that more recently, what Nvidia is doing now is, but they just at their big tech investor day, they just partner with General Motors and others to basically do autonomous cars. And what's crucial about it, they're going to train all those autonomous vehicles in an NVIDIA built digital twin in a matrix that will act, that will be populated by agents that will act like people, people ish, and they will be able to run millions of years of autonomous vehicle training in this and this is how they plan to catch up to. Waymo or, you know, if Tesla's robotaxis are ever real kind of thing, you know, Waymo built hardwired like trained on real world streets, and that's why they can only operate in certain operating domain environments. Nvidia is gambling that with large language models and transformer models combined with digital twins, you can do these huge leapfrog effects where you can basically train all sorts of synthetic agents in real world behavior that you have modeled inside the machine. So again, that's the kind, that's exactly the kind of, you know, environment that you're going to train, you know, your your grid of the future on for modeling out all your contingency scenarios.   Trevor Freeman  35:31 Yeah, again, you know, for to bring this to the to our context, a couple of years ago, we had our the direcco. It's a big, massive windstorm that was one of the most damaging storms that we've had in Ottawa's history, and we've made some improvements since then, and we've actually had some great performance since then. Imagine if we could model that derecho hitting our grid from a couple different directions and figure out, well, which lines are more vulnerable to wind speeds, which lines are more vulnerable to flying debris and trees, and then go address that and do something with that, without having to wait for that storm to hit. You know, once in a decade or longer, the other use case that we've talked about on this one is just modeling what's happening underground. So, you know, in an urban environments like Ottawa, like Montreal, where you are, there's tons of infrastructure under the ground, sewer pipes, water pipes, gas lines, electrical lines, and every time the city wants to go and dig up a road and replace that road, replace that sewer, they have to know what's underground. We want to know what's underground there, because our infrastructure is under there. As the electric utility. Imagine if you had a model where you can it's not just a map. You can actually see what's happening underground and determine what makes sense to go where, and model out these different scenarios of if we underground this line or that line there. So lots of interesting things when it comes to a digital twin. The digital twin and Agent combination is really interesting as well, and setting those agents loose on a model that they can play with and understand and learn from. So talk a little bit about.   Greg Lindsay  37:11 that. Yeah. Well, there's a couple interesting implications just the underground, you know, equipment there. One is interesting because in addition to, like, you know, you know, having captured that data through mapping and other stuff there, and having agents that could talk about it. So, you know, next you can imagine, you know, I've done some work with augmented reality XR. This is sort of what we're seeing again, you know, meta Orion has shown off their concept. Google's brought back Android XR. Meta Ray Bans are kind of an example of this. But that's where this data will come from, right? It's gonna be people wearing these wearables in the world, capturing all this camera data and others that's gonna be fed into these digital twins to refresh them. Meta has a particularly scary demo where you know where you the user, the wearer leaves their keys on their coffee table and asks metas, AI, where their coffee where their keys are, and it knows where they are. It tells them and goes back and shows them some data about it. I'm like, well, to do that, meta has to have a complete have a complete real time map of your entire house. What could go wrong. And that's what all these companies aspire to of reality. So, but yeah, you can imagine, you know, you can imagine a worker. And I've worked with a startup out of urban X, a Canada startup, Canadian startup called context steer. And you know, is the idea of having real time instructions and knowledge manuals available to workers, particularly predictive maintenance workers and line workers. So you can imagine a technician dispatched to deal with this cut in the pavement and being able to see with XR and overlay of like, what's actually under there from the digital twin, having an AI basically interface with what's sort of the work order, and basically be your assistant that can help you walk you through it, in case, you know, you run into some sort of complication there, hopefully that won't be, you know, become like, turn, turn by turn, directions for life that gets into, like, some of the questions about what we wanted out of our workforce. But there's some really interesting combinations of those things, of like, you know, yeah, mapping a world for AIS, ais that can understand it, that could ask questions in it, that can go probe it, that can give you advice on what to do in it. All those things are very close for good and for bad.   Trevor Freeman  39:03 You kind of touched on my next question here is, how do we make sure this is all in the for good or mostly in the for good category, and not the for bad category you talk in one of the papers that you wrote about, you know, AI and augmented reality in particular, really expanding the attack surface for malicious actors. So we're creating more opportunities for whatever the case may be, if it's hacking or if it's malware, or if it's just, you know, people that are up to nefarious things. How do we protect against that? How do we make sure that our systems are safe that the users of our system. So in our case, our customers, their data is safe, their the grid is safe. How do we make sure that?   Greg Lindsay  39:49 Well, the very short version is, whatever we're spending on cybersecurity, we're not spending enough. And honestly, like everybody who is no longer learning to code, because we can be a quad or ChatGPT to do it, I. Is probably there should be a whole campaign to repurpose a big chunk of tech workers into cybersecurity, into locking down these systems, into training ethical systems. There's a lot of work to be done there. But yeah, that's been the theme for you know that I've seen for 10 years. So that paper I mentioned about sort of smart homes, the Internet of Things, and why people would want a smart home? Well, yeah, the reason people were skeptical is because they saw it as basically a giant attack vector. My favorite saying about this is, is, there's a famous Arthur C Clarke quote that you know, any sufficiently advanced technology is magic Tobias Ravel, who works at Arup now does their head of foresight has this great line, any sufficiently advanced hacking will feel like a haunting meaning. If you're in a smart home that's been hacked, it will feel like you're living in a haunted house. Lights will flicker on and off, and systems will turn and go haywire. It'll be like you're living with a possessed house. And that's true of cities or any other systems. So we need to do a lot of work on just sort of like locking that down and securing that data, and that is, you know, we identified, then it has to go all the way up and down the supply chain, like you have to make sure that there is, you know, a chain of custody going back to when components are made, because a lot of the attacks on nest, for example. I mean, you want to take over a Google nest, take it off the wall and screw the back out of it, which is a good thing. It's not that many people are prying open our thermostats, but yeah, if you can get your hands on it, you can do a lot of these systems, and you can do it earlier in the supply chain and sorts of infected pieces and things. So there's a lot to be done there. And then, yeah, and then, yeah, and then there's just a question of, you know, making sure that the AIs are ethically trained and reinforced. And, you know, a few people want to listeners, want to scare themselves. You can go out and read some of the stuff leaking out of anthropic and others and make clot of, you know, models that are trying to hide their own alignments and trying to, like, basically copy themselves. Again, I don't believe that anything things are alive or intelligent, but they exhibit these behaviors as part of the probabilistic that's kind of scary. So there's a lot to be done there. But yeah, we worked on this, the group that I do foresight with Arizona State University threat casting lab. We've done some work for the Secret Service and for NATO and, yeah, there'll be, you know, large scale hackings on infrastructure. Basically the equivalent can be the equivalent can be the equivalent to a weapons of mass destruction attack. We saw how Russia targeted in 2014 the Ukrainian grid and hacked their nuclear plans. This is essential infrastructure more important than ever, giving global geopolitics say the least, so that needs to be under consideration. And I don't know, did I scare you enough yet? What are the things we've talked through here that, say the least about, you know, people being, you know, tricked and incepted by their AI girlfriends, boyfriends. You know people who are trying to AI companions. I can't possibly imagine what could go wrong there.   Trevor Freeman  42:29 I mean, it's just like, you know, I don't know if this is 15 or 20, or maybe even 25 years ago now, like, it requires a whole new level of understanding when we went from a completely analog world to a digital world and living online, and people, I would hope, to some degree, learned to be skeptical of things on the internet and learned that this is that next level. We now need to learn the right way of interacting with this stuff. And as you mentioned, building the sort of ethical code and ethical guidelines into these language models into the AI. Learning is pretty critical for our listeners. We do have a podcast episode on cybersecurity. I encourage you to go listen to it and reassure yourself that, yes, we are thinking about this stuff. And thanks, Greg, you've given us lots more to think about in that area as well. When it comes to again, looking back at utilities and managing the grid, one thing we're going to see, and we've talked a lot about this on the show, is a lot more distributed generation. So we're, you know, the days of just the central, large scale generation, long transmission lines that being the only generation on the grid. Those days are ending. We're going to see more distributed generations, solar panels on roofs, batteries. How does AI help a utility manage those better, interact with those better get more value out of those things?   Greg Lindsay  43:51 I guess that's sort of like an extension of some of the trends I was talking about earlier, which is the notion of, like, being able to model complex systems. I mean, that's effectively it, right, like you've got an increasingly complex grid with complex interplays between it, you know, figuring out how to basically based on real world performance, based on what you're able to determine about where there are correlations and codependencies in the grid, where point where choke points could emerge, where overloading could happen, and then, yeah, basically, sort of building that predictive system to Basically, sort of look for what kind of complex emergent behavior comes out of as you keep adding to it and and, you know, not just, you know, based on, you know, real world behavior, but being able to dial that up to 11, so to speak, and sort of imagine sort of these scenarios, or imagine, you know, what, what sort of long term scenarios look like in terms of, like, what the mix, how the mix changes, how the geography changes, all those sorts of things. So, yeah, I don't know how that plays out in the short term there, but it's this combination, like I'm imagining, you know, all these different components playing SimCity for real, if one will.   Trevor Freeman  44:50 And being able to do it millions and millions and millions of times in a row, to learn every possible iteration and every possible thing that might happen. Very cool. Okay. So last kind of area I want to touch on you did mention this at the beginning is the the overall power implications of of AI, of these massive data centers, obviously, at the utility, that's something we are all too keenly aware of. You know, the stat that that I find really interesting is a normal Google Search compared to, let's call it a chat GPT search. That chat GPT search, or decision making, requires 10 times the amount of energy as that just normal, you know, Google Search looking out from a database. Do you see this trend? I don't know if it's a trend. Do you see this continuing like AI is just going to use more power to do its decision making, or will we start to see more efficiencies there? And the data centers will get better at doing what they do with less energy. What is the what does the future look like in that sector?   Greg Lindsay  45:55 All the above. It's more, is more, is more! Is the trend, as far as I can see, and every decision maker who's involved in it. And again, Jensen Wong brought this up at the big Nvidia Conference. That basically he sees the only constraint on this continuing is availability of energy supplies keep it going and South by Southwest. And in some other conversations I've had with bandwidth companies, telcos, like laying 20 lumen technologies, United States is laying 20,000 new miles of fiber optic cables. They've bought 10% of Corning's total fiber optic output for the next couple of years. And their customers are the hyperscalers. They're, they're and they're rewiring the grid. That's why, I think it's interesting. This has something, of course, for thinking about utilities, is, you know, the point to point Internet of packet switching and like laying down these big fiber routes, which is why all the big data centers United States, the majority of them, are in north of them are in Northern Virginia, is because it goes back to the network hub there. Well, lumen is now wiring this like basically this giant fabric, this patchwork, which can connect data center to data center, and AI to AI and cloud to cloud, and creating this entirely new environment of how they are all directly connected to each other through some of this dedicated fiber. And so you can see how this whole pattern is changing. And you know, the same people are telling me that, like, yeah, the where they're going to build this fiber, which they wouldn't tell me exactly where, because it's very tradable, proprietary information, but, um, but it's following the energy supplies. It's following the energy corridors to the American Southwest, where there's solar and wind in Texas, where you can get natural gas, where you can get all these things. It will follow there. And I of course, assume the same is true in Canada as we build out our own sovereign data center capacity for this. So even, like deep seek, for example, you know, which is, of course, the hyper efficient Chinese model that spooked the markets back in January. Like, what do you mean? We don't need a trillion dollars in capex? Well, everyone's quite confident, including again, Jensen Wong and everybody else that, yeah, the more efficient models will increase this usage. That Jevons paradox will play out once again, and we'll see ever more of it. To me, the question is, is like as how it changes? And of course, you know, you know, this is a bubble. Let's, let's, let's be clear, data centers are a bubble, just like railroads in 1840 were a bubble. And there will be a bust, like not everyone's investments will pencil out that infrastructure will remain maybe it'll get cheaper. We find new uses for it, but it will, it will eventually bust at some point and that's what, to me, is interesting about like deep seeking, more efficient models. Is who's going to make the wrong investments in the wrong places at the wrong time? But you know, we will see as it gathers force and agents, as I mentioned. You know, they don't require, as much, you know, these monstrous training runs at City sized data centers. You know, meta wanted to spend $200 billion on a single complex, the open AI, Microsoft, Stargate, $500 billion Oracle's. Larry Ellison said that $100 billion is table stakes, which is just crazy to think about. And, you know, he's permitting three nukes on site. So there you go. I mean, it'll be fascinating to see if we have a new generation of private, private generation, right, like, which is like harkening all the way back to, you know, the early electrical grid and companies creating their own power plants on site, kind of stuff. Nicholas Carr wrote a good book about that one, about how we could see from the early electrical grid how the cloud played out. They played out very similarly. The AI cloud seems to be playing out a bit differently. So, so, yeah, I imagine that as well, but, but, yeah, well, inference happen at the edge. We need to have more distributed generation, because you're gonna have AI agents that are going to be spending more time at the point of request, whether that's a laptop or your phone or a light post or your autonomous vehicle, and it's going to need more of that generation and charging at the edge. That, to me, is the really interesting question. Like, you know, when these current generation models hit their limits, and just like with Moore's law, like, you know, you have to figure out other efficiencies in designing chips or designing AIS, how will that change the relationship to the grid? And I don't think anyone knows quite for sure yet, which is why they're just racing to lock up as many long term contracts as they possibly can just get it all, core to the market.   Trevor Freeman  49:39 Yeah, it's just another example, something that comes up in a lot of different topics that we cover on this show. Everything, obviously, is always related to the energy transition. But the idea that the energy transition is really it's not just changing fuel sources, like we talked about earlier. It's not just going from internal combustion to a battery. It's rethinking the. Relationship with energy, and it's rethinking how we do things. And, yeah, you bring up, like, more private, massive generation to deal with these things. So really, that whole relationship with energy is on scale to change. Greg, this has been a really interesting conversation. I really appreciate it. Lots to pack into this short bit of time here. We always kind of wrap up our conversations with a series of questions to our guests. So I'm going to fire those at you here. And this first one, I'm sure you've got lots of different examples here, so feel free to give more than one. What is a book that you've read that you think everybody should read?   Greg Lindsay  50:35 The first one that comes to mind is actually William Gibson's Neuromancer, which is which gave the world the notion of cyberspace and so many concepts. But I think about it a lot today. William Gibson, Vancouver based author, about how much in that book is something really think about. There is a digital twin in it, an agent called the Dixie flatline. It's like a former program where they cloned a digital twin of him. I've actually met an engineering company, Thornton Thomas Eddie that built a digital twin of one of their former top experts. So like that became real. Of course, the matrix is becoming real the Turing police. Yeah, there's a whole thing in there where there's cops to make sure that AIS don't get smarter. I've been thinking a lot about, do we need Turing police? The EU will probably create them. And so that's something where you know the proof, again, of like science fiction, its ability in world building to really make you think about these implications and help for contingency planning. A lot of foresight experts I work with think about sci fi, and we use sci fi for exactly that reason. So go read some classic cyberpunk, everybody.   Trevor Freeman  51:32 Awesome. So same question. But what's a movie or a show that you think everybody should take a look at?   Greg Lindsay  51:38 I recently watched the watch the matrix with ideas, which is fun to think about, where the villains are, agents that villains are agents. That's funny how that terms come back around. But the other one was thinking about the New Yorker recently read a piece on global demographics and the fact that, you know, globally, less and less children. And it made several references to Alfonso Quons, Children of Men from 2006 which is, sadly, probably the most prescient film of the 21st Century. Again, a classic to watch, about imagining in a world where we don't where you where you lose faith in the future, what happens, and a world that is not having children as a world that's losing faith in its own future. So that's always haunted me.   Trevor Freeman  52:12 It's funny both of those movies. So I've got kids as they get, you know, a little bit older, a little bit older, we start introducing more and more movies. And I've got this list of movies that are just, you know, impactful for my own adolescent years and growing up. And both matrix and Children of Men are on that list of really good movies that I just need my kids to get a little bit older, and then I'm excited to watch with them. If someone offered you a free round trip flight anywhere in the world, where would you go?   Greg Lindsay  52:40 I would go to Venice, Italy for the Architecture Biennale, which I will be on a plane in May, going to anyway. And the theme this year is intelligence, artificial, natural and collective. So it should be interesting to see the world's brightest architects. Let's see what we got. But yeah, Venice, every time, my favorite city in the world.   Trevor Freeman  52:58 Yeah, it's pretty wonderful. Who is someone that you admire?   Greg Lindsay  53:01 Great question.

WATCH the video on Substack by clicking the play button above or on YouTube (here).STREAM audio only on Apple Podcasts (here), Spotify (here), or your favorite podcast player app.DOWNLOAD a pdf of the slide deck by clicking the blue Download button below.Last week we published a written post that took a fresh look at a long standing theme of ours “obliterating peak oil demand” (here). We dug into OPEC Research's most recent World Oil Outlook report (here) to compare OPEC's more optimistic view of long-term oil demand to more bearish forecasts from the IEA and frankly many other leading energy voices. Our own outlook is closely aligned with OPEC's in recognizing the massive unmet energy needs of the other 7 billion people on Earth. The idea that anyone can know today that oil demand is going to permanently peak within the next decade is something we push back hard on. That post has sparked a number of questions, five of which we will aim to address today.Our On A Personal Note this week remembers heavy metal pioneer Ozzy Osbourne, who passed away on July 21. I was fortunate to catch a Black Sabbath reunion tour in 2016.

In this episode of the Energy Newsbeat Daily Standup, Stuart Turley and Michael Tanner discuss the approaching "day of reckoning" for wind and solar energy, highlighting the growing challenges of the net-zero transition and the high costs associated with renewable energy. They also cover the U.S.'s potential withdrawal from the International Energy Agency (IEA) as Energy Secretary Chris Wright pushes for reform or exit due to the IEA's political stance on clean energy. The conversation shifts to the impact of AI in Pennsylvania, with major companies investing billions in data centers, and concludes with insights into grid reliability, emphasizing the complexities of integrating renewable energy and the need for microgrids.Highlights of the Podcast 00:00 - Intro00:13 - Wind and Solar's Day of Reckoning is Approaching.04:32 - Energy Secretary Chris Wright Says Withdrawal from IEA Is Now on the Table06:57 - AI in Pennsylvania is on the move – Doug Sheridan brings up some great questions08:14 - Voltage, inertia and the Iberian blackout part 1: the theory11:59 - Markets Update12:57 - EIA Crude Oil Inventory14:39 - OutroPlease see the links below or articles that we discuss in the podcast.Wind and Solar's Day of Reckoning is Approaching.Energy Secretary Chris Wright Says Withdrawal from IEA Is Now on the TableAI in Pennsylvania is on the move – Doug Sheridan brings up some great questionsVoltage, inertia and the Iberian blackout part 1: the theoryFollow Michael On LinkedIn and TwitterFollow Stu on LinkedIn and XENB Top NewsEnergy DashboardENB PodcastENB SubstackENB Trading DeskOil & Gas InvestingNeed Power For Your Data Center, Hospital, or Business?– Get in Contact With The Show –

A salute to Cipher ... Renewables go missing in Pittsburgh ... The US threatens to pull out of the IEA ... Uncertainty persists for transferability of tax credits ... California bill tweaks net metering for home salesSign up for the Renewable Energy SmartBrief

Brent prices strengthened last week despite ongoing geopolitical risks, as the IEA adjusted its 2025 and 2026 demand forecasts and highlighted a surplus in the market. Meanwhile, developments in US trade policy and a shift in Trump's stance on Russia add further complexity to the outlook for oil prices. Please note: this podcast is provided for information purposes only and should not be construed as an offer, or a solicitation of an offer, to buy or sell financial instruments. This podcast does not constitute a personal recommendation and is not investment advice. Investec

Welcome back to The Hydrogen Podcast! I'm Paul Rodden, and today we're breaking down two major hydrogen headlines that could reshape the global energy landscape:

Artificial intelligence is transforming our world — and the energy sector. Earlier this year, the International Energy Agency (IEA) released a comprehensive report examining both AI's projected energy demands and how it  might reshape energy systems. But while headlines often raise alarms around electricity demand growth, the reality is more nuanced and complex. While data centers currently account for just 1.5% of global electricity use, that share is expected to double by 2030, driven largely by the growth of AI. In some regions, particularly in the US, data centers could account for nearly half of all electricity demand growth in the coming years. So how should we understand the relationship between AI and energy? What does this mean for power systems around the world? Is artificial intelligence a friend or foe to the clean energy transition? This week, Jason Bordoff speaks with Laura Cozzi, about the IEA's findings on AI's energy demands. Laura is the chief energy modeler at the International Energy Agency, and its director of sustainability, technology, and outlooks. She oversees the IEA's analytical work on energy, climate, and economic modeling, and led the team that produced the agency's report on artificial intelligence and energy. Credits: Hosted by Jason Bordoff and Bill Loveless. Produced by Mary Catherine O'Connor, Caroline Pitman, and Kyu Lee. Engineering by Gregory Vilfranc.  

Umetna inteligenca velja za tehnologijo, ki bo definirala 21. stoletje. Predvidena vlaganja vanjo v naslednjih nekaj letih gredo globalno gledano v bilijone dolarjev. Ob tem se bo občutno povečala tudi poraba elektrike, po ocenah IEA za štirikrat v le petih letih. Novi podatkovni centri se tako vse bolj načrtujejo skupaj s lastnim virom energije, od jedrskih elektrarn do polj vetrnic. Zakaj je sodobna umetna inteligenca tako lačna energije, koliko energije terja eno vprašanje ChatGPT-ju in kaj se pravzaprav dogaja v sodobnih podatkovnih centrih, so preverjali v oddaji Intelekta, ki jo vnovič predvajamo v oddaji Studio ob 17.00. Gostje: dr. Andrej Filipčič, Inštitut Jožef Stefan in Univerza v Novi Gorici; dr. Iztok Lebar Bajec, Fakulteta za računalništvo in informatiko Univerze v Ljubljani; dr. Uroš Lotrič, Fakulteta za računalništvo in informatiko Univerze v Ljubljani; dr. Patricia Bulić, Fakulteta za računalništvo in informatiko Univerze v Ljubljani.

IEA預測今年全球電動車銷售將突破2000萬輛，中國、歐洲成長強勁，轉型大勢依舊。但美國卻逆風而行——從補貼退場、油價偏低到川普反撲，讓電動車政策與民意同步轉向，「綠反挫」成為國際焦點。 台灣如何因應這場轉型分流？ 從產業佈局到電動機車推動，從充電設施不足到消費者不買單，政策目標喊得響，但落地難度高。 本集專訪邱俊榮教授，從美國市場風向變化談到台灣內部的轉型焦慮與機會。 #台達基金會 #氣候戰役在台灣 ★本集重點： 1️⃣ 全球電動車持續成長，但美國成「綠反挫」震央 2️⃣ 台灣機車電動化卡關：從產業現實到政策盲點 3️⃣ 公正轉型不能只靠補助，更要跨部會協調與長期調適 Powered by Firstory Hosting

The Future of Geothermal. What is it and how does it play out? The recent report by the IEA with the aforementioned title "The Future of Geothermal" goes into detail on the past, present and future of geothermal, new technologies, startups, oil and gas crossover, and so much more. It is well worth a read, but in the meantime, I sat down with Heymi Bahar, a senior analyst with the IEA to talk about the report in detail, giving a view into what the future may indeed hold for this amazing resource - the heat beneath our feet.  Heymi Bahar https://www.linkedin.com/in/heymi-bahar/IEA https://www.linkedin.com/company/international-energy-agency/posts/?feedView=allHeymi's Book Recommendation The Perfectionist: Life and death in Haue cuisine by Stephen Chelminski Nick Cestari https://www.linkedin.com/in/nick-cestari-48059268/CORE Knowledge https://www.linkedin.com/company/core-geothermal

Welcome to The Hydrogen Podcast! I'm Paul Rodden, and today kicks off Part 1 of our special two-part series on building the U.S. hydrogen economy by 2035. In this episode, we break down the four core hydrogen production technologies shaping America's clean energy strategy:

Chris Snowden of the IEA, a neoliberal think tank, joins Ava in the JOETowers basement to talk smoking, gambling, and threats to the neoliberal way of life. Hosted on Acast. See acast.com/privacy for more information.

欢迎收听雪球出品的财经有深度，雪球，国内领先的集投资交流交易一体的综合财富管理平台，聪明的投资者都在这里。今天分享的内容叫伊以冲突与全球能源市场脆弱性分析，来自航向向东。当前伊以冲突已超越单纯军事对抗，演变为对全球能源供应链的战略性威胁。尽管冲突尚未直接导致霍尔木兹海峡全面封锁或伊朗石油产能崩溃，但其潜在破坏力已引发市场恐慌性溢价。根据BCA Research报告，未来六个月全球石油供应面临超过1000万桶/日重大冲击的概率高达55%，这将使油价波动幅度达到50%-100%。与历史石油危机相比，当前局势在供应中断规模上可能不及1973年或1979年，但在市场心理层面已形成类似1970年代的恐慌情绪，且叠加了地缘政治风险溢价和供应链脆弱性。面对这一挑战，OPEC+的备用产能和美国页岩油的增产潜力难以完全弥补潜在缺口，而国际能源署战略石油储备释放的协同效应有限，这使得全球能源市场正站在”如履薄冰”的关键节点。一、伊朗石油供应与霍尔木兹海峡的战略地位伊朗作为全球第七大石油生产国，其能源地位不容忽视。截至2025年4月，伊朗原油产量约为331万桶/日，位居OPEC第三大产油国。伊朗石油出口量在2025年5月约为166万桶/日，但冲突爆发后激增至233万桶/日，显示其短期产能未受显著影响。然而，伊朗石油出口高度依赖灰色渠道，约90%流向远东，其余出口至叙利亚、委内瑞拉等国家。这种非正规贸易网络面临美国制裁的持续压力，2024年灰色船队的出口量已从120万桶/日收缩至约80万桶/日。霍尔木兹海峡的战略地位更为关键。这条位于伊朗与阿曼之间的狭窄水道是全球能源运输的咽喉要道。每天约有2090万桶原油通过该海峡，占全球石油液体消费量的21%。其中，伊朗、沙特、阿联酋、伊拉克、科威特和卡塔尔等波斯湾国家的石油出口几乎全部依赖这一通道。更值得注意的是，通过霍尔木兹海峡的石油运输中有83%流向亚太地区，这意味着该地区对霍尔木兹海峡的依赖度最高。冲突爆发后，霍尔木兹海峡的航运流量已出现初步变化。联合海事信息中心(JMIC)数据显示，6月15日通过该海峡的货轮数量为111艘，较6月12日的116艘略有减少，降幅约4%。尽管关键石油基础设施尚未受到重大干扰，但航运公司已开始采取规避措施。BIMCO首席安全与安保官拉森表示：“越来越多的货船正选择远离红海和波斯湾，以及具有重要战略意义的霍尔木兹海峡。”Frontline首席执行官拉斯·巴斯塔德也确认：“我们现已全面暂停签署进入波斯湾的新合约。”值得注意的是，伊朗封锁霍尔木兹海峡的能力虽存在，但其实施意愿受到多重制约。伊朗拥有2000-3000枚水雷和射程超过300公里的反舰导弹，理论上具备封锁海峡的能力。然而，伊朗经济严重依赖石油出口，封锁海峡将导致自身石油出口停滞，造成经济崩溃。此外，1988年美伊霍尔木兹海峡之战中，伊朗海军遭受重创，几艘主力军舰被美国海军编队击沉或击伤，几乎全军覆没。这一历史教训使伊朗对封锁海峡的军事后果保持警惕。二、当前局势与历史石油危机的对比分析伊以冲突引发的能源危机风险与历史上三次重大石油危机有相似之处，但也存在显著差异。1973年石油危机由OPEC对以色列实施禁运引发，全球供应减少约750万桶/日，油价从13美元/桶飙升至54美元/桶，持续时间约1年。1979年石油危机由伊朗伊斯兰革命引发，伊朗产量从580万桶/日骤降至100万桶/日，叠加两伊战争，全球供应缺口扩大至约600万桶/日，油价从13美元/桶飙升至35美元/桶，持续约2年。1990年海湾战争由伊拉克入侵科威特引发，导致两国约400万桶/日的供应中断，油价从21美元/桶涨至46美元/桶，持续9个月。当前局势与历史危机的相似性主要体现在：冲突直接威胁能源基础设施，引发市场恐慌性溢价；关键产油国产量可能因冲突而下降；地缘政治风险溢价推高油价。例如，伊朗已威胁关闭霍尔木兹海峡，这与1973年OPEC禁运和1979年伊朗革命时的威胁相似。同时，以色列对伊朗能源设施的打击可能导致伊朗石油产量下降，与历史上产油国产能崩溃的模式相似。然而，当前局势与历史危机也存在显著差异：供应中断规模与范围、市场机制变化、地缘政治参与方、经济背景差异。具体而言：当前局势最显著的差异在于供应中断规模与范围。伊朗当前出口量仅占全球4%，即使完全中断，缺口也仅为170万桶/日，远小于历史危机中的中断规模。此外，当前冲突未引发产油国集体行动，且主要集中在伊朗与以色列之间，未直接波及沙特等核心产油国。三、全球能源市场应对供应中断的能力评估面对潜在的石油供应中断，全球能源市场拥有多层次的应对机制，但其有效性受到多重制约。OPEC+的备用产能是市场的主要缓冲力量，但根据高盛2025年6月报告，当前OPEC+实际产能利用率已达89.7%，其中沙特、阿联酋等核心产油国的剩余产能仅存550万桶/日，接近历史低位。即使沙特理论上具备250万桶/日的增产空间，阿联酋宣称485万桶/日的最大生产能力，但实际增产能力受到长期减产政策和投资不足的限制。例如，沙特近年来将资源转向其他项目，停止扩充备用产能，这使其在应对突发危机时的灵活性大打折扣。美国页岩油是另一个重要的供应缓冲。截至2025年7月，美国页岩油产量预计将达到1320万桶/日，创历史新高。然而，页岩油的增产潜力受到钻井数和完井周期的制约。2025年贝克休斯活跃石油钻机数量为394台，尽管与2024年相比增加了181台，但仍处于历史较低水平。钻机数量上升通常滞后于原油价格上涨约4-6个月，这意味着即使油价飙升，页岩油企业也需要时间才能实现产量增长。此外，页岩油产量的提升更多是依靠DUC，而当前DUC库存已降至2013年以来的最低水平，这进一步限制了页岩油的增产能力。国际能源署战略石油储备是应对短期供应中断的重要工具。摩根大通分析师指出：“全球国家极不可能'协同释放战略石油储备'。”即使在2022年俄乌冲突期间，除美国外的IEA成员国也仅同意释放6000万桶石油储备，远低于美国的1.8亿桶。此外，战略石油储备的释放存在时间滞后，从宣布到实际投放市场通常需要2周以上的时间，这使得储备释放难以应对突发的供应中断。非OPEC产油国的产能释放也是市场关注的焦点。巴西深海油田、圭亚那陆上区块的新增产能持续释放，2025年非OPEC国家原油产量增速预计达2.3%。然而，这些新增产能主要集中在特定区域，且运输路线受限，无法完全替代霍尔木兹海峡的运输量。例如，巴西石油需要通过海运抵达亚洲市场，而圭亚那石油则主要面向美国市场。四、价格波动幅度预测与市场心理分析基于当前局势和历史经验，重大供应冲击将导致油价波动幅度达到50%-100%，远超当前市场预期。这一预测基于三个关键因素：潜在供应中断规模、市场恐慌溢价、以及备用产能释放的滞后性。首先，潜在供应中断规模可能远超当前实际影响。伊朗已威胁关闭霍尔木兹海峡，若实施将导致每天约2000万桶的石油运输中断。虽然伊朗不太可能全面封锁海峡，但”灰色干扰”手段可能导致运输成本上升和风险溢价增加。此外，以色列已打击伊朗的炼油厂、储油设施和天然气加工厂，若冲突升级，可能进一步破坏伊朗的能源基础设施，导致产量下降。其次，市场恐慌溢价已显著上升。布伦特原油期货价格在6月13日袭击事件后单日暴涨13%，创俄乌冲突以来最高涨幅。这一涨幅远超实际供应中断的影响，主要源于市场对潜在供应风险的恐慌性预期。恐慌溢价的持续存在将使油价波动幅度扩大，即使供应中断规模有限，也可能引发50%-100%的价格波动。再者，备用产能释放的滞后性将加剧价格波动。OPEC+的备用产能和美国页岩油的增产潜力需要3-6个月才能完全释放，而供应中断可能在短期内发生，这种时间差将导致油价在短期内大幅波动。此外，战略石油储备的释放也存在时间滞后，从宣布到实际投放市场通常需要2周以上的时间，这使得储备释放难以应对突发的供应中断。与历史石油危机相比，当前市场对价格波动的承受能力有所增强，但仍有脆弱性。1973年油价上涨315%和1979年上涨169%均导致全球经济衰退，而当前全球经济对高油价的承受能力因能源结构多元化而增强。例如，美国页岩油产量的大幅增长使其对中东石油的依赖度显著下降，从2010年的60%降至2025年的30%以下。此外，远东等新兴经济体在能源消费结构上更加多元化，减少了对单一能源的依赖。然而，当前全球经济仍面临通胀压力，高油价将进一步加剧这一压力，对经济复苏构成挑战。五、供应链多元化与地缘政治风险溢价伊以冲突引发的能源危机风险凸显了全球能源供应链的脆弱性，同时也加速了供应链多元化进程。供应链多元化已成为应对地缘政治风险的主要策略，包括运输路线多元化、供应来源多元化和能源消费结构多元化。运输路线多元化方面，油轮运费因绕行好望角单日飙升24%，VLCC日均收益达5.1万美元。这种运费上涨反映了市场对霍尔木兹海峡安全风险的担忧，以及对替代运输路线的迫切需求。然而，绕行路线无法完全替代霍尔木兹海峡的运输量，因为绕行增加了运输时间和成本，且需要更多的油轮运力。例如，绕行好望角的运输时间比经霍尔木兹海峡长30%-40%，这使得替代运输路线的经济性受到挑战。供应来源多元化方面，远东等主要进口国已开始减少对伊朗石油的依赖。然而，这种多元化进程仍面临挑战，因为沙特等国的石油出口也依赖霍尔木兹海峡，且其备用产能有限。例如，沙特2025年的备用产能约为190万桶/日，远低于其2020年疫情前的250万桶/日水平。地缘政治风险溢价已成为油价的重要组成部分。高盛分析指出，当前布伦特原油期货价格中的地缘政治风险溢价约为10美元/桶，主要源于中东局势的不确定性。这一溢价已部分反映了市场对潜在供应中断的担忧，但若冲突升级，溢价可能进一步上升。例如，若伊朗采取极端措施，如关闭霍尔木兹海峡或袭击地区石油基础设施，油价可能飙升至每桶超过94美元，市场反应将极为剧烈。六、全球能源市场前景面对伊以冲突引发的能源危机风险，全球能源市场前景复杂多变，需要采取多层次的应对策略。短期来看，市场将维持”乱而不战”的紧张态势，油价波动性将显著增加。布伦特原油价格可能在75-80美元/桶区间波动，较当前水平存在6.5%-10%的上行空间。这种波动性将主要由地缘政治风险溢价驱动，而非实际供应中断。中长期来看，能源市场将经历结构性调整。一方面，OPEC+的备用产能有限且高度集中于沙特和阿联酋，这使得全球市场在面对伊朗危机时显得脆弱不堪。高盛预测，OPEC+将于2025年8月正式结束持续14个月的增产周期，届时全球原油市场供需格局可能迎来结构性调整。另一方面，美国页岩油、巴西深海油田等非OPEC产能的持续释放将为市场提供一定缓冲，但其增产潜力受到钻井数和完井周期的制约。七、结论与展望若冲突升级导致伊朗石油产能大幅下降或霍尔木兹海峡运输受阻，全球能源市场将面临严峻考验。面对这一挑战，各国需采取多层次的应对策略，包括加强战略石油储备管理、推动能源消费结构多元化、加强国际能源合作等。能源转型将是长期应对地缘政治风险的关键，但短期内仍需依赖传统石油供应。因此，维护中东地区的能源安全稳定对全球经济发展至关重要。未来六个月，伊以冲突的走向将直接影响全球能源市场。BCA Research预测的三种情景各有不同的影响路径。无论哪种情景，全球能源市场都将面临不同程度的供应中断风险，油价波动幅度可能达到50%-100%，这将对全球经济复苏构成挑战。因此，各国需保持警惕，及时调整能源政策，以应对可能的能源危机。

Kate Roncarati Paul is the head coach of the Northeastern University Equestrian Team and has led an IEA team since 2018—both heading to nationals this year. She began as a working student and competed primarily on the local circuit before studying equine science at Mount Ida College, where she captained the IHSA team. After college, she worked under her former coach, Julie Chandler (Kelly), and returned to Massachusetts in 2017 to rejoin her at Cranberry Acres in Marshfield, MA—now home to both her teams. This year marks a milestone, with Northeastern making its first-ever appearance at IHSA Nationals.

Today we're excited to welcome Patrick White, Group Lead for Fusion Energy Safety and Regulation at the Clean Air Task Force (CATF), and Nicholas McMurray, Managing Director of International and Nuclear Policy at ClearPath. Patrick recently joined CATF and leads the organization's international working group focused on fusion energy safety, waste, and non-proliferation. He holds a Ph.D. in Nuclear Science and Engineering from MIT and previously served as Research Director at the Nuclear Innovation Alliance. Niko is an expert in industrial policy, nuclear energy policy, and regulation. He has been with ClearPath since 2019 and formerly served as a Materials Engineer at the U.S. Nuclear Regulatory Commission (NRC). A few weeks ago, Veriten partnered with CATF and ClearPath to publish a paper calling out reforms to NRC processes and procedures to accelerate the deployment of new nuclear reactors; establishing a more efficient regulatory framework for new and advanced reactors (paper linked here). We were thrilled to host Patrick and Niko for a discussion on the paper and broader trends in the nuclear landscape. Brett Rampal, Senior Director of Nuclear and Power Strategy at Veriten, joined for the conversation and led Veriten's contribution to the paper. In our discussion, Patrick and Niko share background on their organizations' missions and long-standing support for nuclear. We explore the need to demystify and modernize NRC processes to accommodate next-generation nuclear technologies, challenges with current regulatory frameworks originally designed for traditional large light-water reactors, the role of licensing structures and the value of more flexible licensing pathways, and the motivation behind their recent paper, which aims to provide actionable, bipartisan policy suggestions to enable nuclear deployment at scale. We examine the historical development and regulatory evolution of power versus non-power reactor definitions, how those distinctions have blurred over time, the shift toward performance-based regulation, and the commercial implications of licensing small reactors under Class 103. We discuss the importance of consistent terminology and regulatory clarity in advancing new nuclear technologies, whether the NRC's internal culture can evolve to support faster deployment without compromising safety, the NRC's broader oversight role beyond reactors including medical and industrial applications of radioactive materials, and congressional support for NRC modernization. Patrick and Niko provide insights into international regulatory approaches, such as performance-based models used in the UK, France, and Canada, the critical need to earn public trust through rigorous and efficient safety regulation, the feasibility of President Trump's goal of having 10 new reactors under construction by 2030, challenges beyond regulation, and much more. We greatly enjoyed the conversation. To start the show, Mike Bradley noted that the S&P 500 closed modestly lower on the day, while crude oil prices caught a bid amid escalating tensions in the Mideast. On the bond front, the 10-year bond yield (~4.4%) has pulled back over the last few days as markets await the outcome of the June 18th FOMC rate decision meeting. Consensus is for no change in interest rates at this FOMC meeting, but a cut is expected at the September meeting. From a crude oil market standpoint, WTI price has spiked by >$10/bbl to ~$74/bbl over the last five trading days due to the Iranian-Israeli military conflict. While Veriten isn't in the business of making short-term crude oil price calls based on supply disruption threats, we continue to emphasize that global oil demand growth projections are a more vital determinant for intermediate-term oil prices. On the global S/D front, the IEA recently modeled global oil demand peaking in 2029 (China in 2027), contra

Lindsay Shaw began riding at the age of 8 with an ever growing passion for the sport and horses. Lindsay attended the Grier School, having the top Interscholastic Equestrian program in the country, from 8th -12th grade and competed in USEF, USDF, and IEA shows with her team. She attended Emory & Henry University in 2020 and competed at IDA and IHSA shows. While at Emory & Henry, Lindsay earned the Female Newcomer Athlete of the Year for the 2020-2021 season and was Champion in First Level at IDA Nationals, helping her team win a national championship in 2024. Lindsay now works at her alma mater, Grier School, as an Admissions and Marketing Associate and Assistant Director of Summer Camp. 

In today's episode of The Hydrogen Podcast, we dive into Newsweek's June 2025 article on the Neom Green Hydrogen Company (NGHC), the heart of Saudi Arabia's bold $500 billion Neom megaproject.

In this episode of The Hydrogen Podcast, we unpack the sobering truths from Oilprice.com's May 2025 article, "Green Hydrogen Faces Reality Check in Europe."

In this episode of The Hydrogen Podcast, we explore two major hydrogen developments reshaping the global energy landscape.

On April 28th, millions of people across Spain, Portugal and beyond were plunged into darkness in one of Europe's most severe blackouts in decades. Was it a cyberattack? A renewables failure? Or might things be a little more complex?This week, Tom Rivett-Carnac, Christiana Figueres, and Paul Dickinson dig into what we know, what we don't, and ask what this blackout really tells us about the transition to renewables. They speak with energy strategist Kingsmill Bond of Ember and hear an on-the-ground account from José Manuel Entrecanales, CEO of global renewables leader Acciona, to build a picture of how our grids function – and how they fail.Plus: what can we say when friends or colleagues claim that ‘renewables aren't reliable'? And, after our recent conversations reflecting on the legacy of Pope Francis, what might Pope Leo XIV mean for future climate leadership?Learn more

On April 10, the International Energy Agency released a major report on energy and AI. The report explores topics including electricity demand for AI, how AI is being used in the energy sector, AI's role in accelerating energy innovation, the security implications of AI and greenhouse gas emissions from AI. Join host David Sandalow in conversation with Laura Cozzi, IEA's Director for Sustainability, Technology and Outlooks, who designed and directed this landmark report.   The AI, Energy and Climate Podcast is a special series from the DSR Network sponsored by NEDO and hosted by David Sandalow, Inaugural Fellow at Columbia University's Center on Global Energy Policy. AI for Climate Change Mitigation Roadmap -- https://www.icef.go.jp/roadmap and transitiondigital.org/ai-climate-roadmap.  Learn more about your ad choices. Visit megaphone.fm/adchoices