AI and Traffic Flow: Innovation, Emissions, and the Google Factor

An initiative by Google and the city of Manchester aims to use AI to dynamically regulate traffic lights across the Greater Manchester region. This is a great use case for AI technology, as studies show that 50% of car emissions at traffic intersections come from vehicles stopping and starting. Based on previous experiences in Brazil and India, traffic flow is expected to improve by up to 30%, while emissions could decrease by up to 10%. The only caveat is that, after reading The Age of Surveillance Capitalism by Shoshana Zuboff (https://www.goodreads.com/review/show/6776829635), I’m always looking for the catch—questioning what Google stands to gain beyond the explicit use case. In this particular instance, the implications seem both obvious and concerning. That said, opportunities like this should be explored and supported. However, we must remain vigilant and ensure that the inevitable data surplus we provide to companies like Google is not misused. (text revised LLM) https://content1.avplayer.com/6536783932d8a8365a0842d9/videos/65367e747ebff164c504fe60/65367e87c1aacf127d085a34/video.mp4?AV_TAGID=65367eb2aacb313497060747&pid=6536783932d8a8365a0842d9&cid=65367e8906c29393c30221d6&AV_TEMPID=65367eb2bc7bf3bcc50e2584&AV_PUBLISHERID=6536783932d8a8365a0842d9&av_qd1=6536806d667c2a96db026742&videoId=65367e747ebff164c504fe60

- Pedro

Read on Substack

How Machine Learning Is Revolutionizing Economic Thinking

A Sendhil Mullainathan delivered a fantastic keynote on Economics in the Age of Algorithms, a talk lasting approximately one hour (at normal speed). In it, he compellingly argues that algorithms (machine learning, AI, etc.) are, at their core, economics. Among the many fascinating topics he covered, I particularly enjoyed how he framed the difference between Estimation and Prediction. Estimation represents the traditional approach to tackling problems, while Prediction is the newer approach enabled by supervised learning (ML). In essence, estimation focuses on optimizing the estimated Beta, while prediction aims to optimize the estimated Y. Sophisticated algorithms that optimize Y (the prediction) are remarkably valuable for uncovering new and strikingly original hypotheses. However, economists (humans) play a crucial role in designing recommendations for payoffs and loss functions, ensuring that ML outputs are meaningful and actionable. Did this triggered your interest? Sit back, relax, and enjoy an hour of insights from one of the great economic minds! (text revised by a LLM) https://videosolutions.mediasite.com/Mediasite/Play/cb9d64c0274d4aae98b61dd6779791b31d?playfrom=970000

- Pedro

Read on Substack

10 Trends to Watch in 2025: Insights from Tom Standage

10 Trends to Watch in 2025, Inspired by Tom Standage’s Insights 1-America First Redux Geopolitical shifts will unfold as the U.S. doubles down on its "America First" policy. 2-A Call for Change Macro-political transformations are imminent, driven by demands for reform in nearly every major election of 2024. 3-Heightened Instability in Europe and the Middle East A transactional approach from the new U.S. administration could exacerbate tensions in these regions. 4-The Tariff Tsunami Expect more tariffs, with ripple effects on global trade and economic growth. 5-The Clean-Tech Boom China's advancements in clean technology could revolutionize the energy sector worldwide. 6-Inflation and Fiscal Tightening Most economies are gearing up for stricter fiscal policies, raising questions about growth and voter approval. 7-The Politics of Aging Could age limits for political leaders become a global trend? 8-AI Revolution Agentic AI systems are poised to become the most transformative innovation since the internet. 9-Tourism Backlash The pushback against overtourism will reshape the travel industry. 10-Expect the Unexpected From global pandemics to solar storms, the world must brace for unpredictable disruptions. Stay tuned for a deeper dive into each of these trends in the near future. (text revised by a LLM) Tom Standage’s ten trends to watch in 2025 https://www.economist.com/the-world-ahead/2024/11/18/tom-standages-ten-trends-to-watch-in-2025 From The Economist

- Pedro

Read on Substack

Demis Hassabis and James Manyika on the Future of Artificial Intelligence

The Economist hosted an excellent subscriber event on AI, science, and society, featuring Demis Hassabis, CEO of Google DeepMind and Nobel laureate, along with James Manyika, Google's Senior Vice President of Research, Technology, and Society. The discussion offered fascinating insights into what we can expect from AGI, including the transformative opportunities it presents and the challenges it brings and it is around the corner (before 2035 creating a virtual cell…). If you have 30 minutes to spare, it’s absolutely worth your time—you won’t regret it! (text revise by a LLM) Event overview: Hear from Sir Demis Hassabis, who leads Google DeepMind and who won a Nobel prize in chemistry last month, to discuss how AI transforms science—and what is possible to be known. He is joined by James Manyika, Google’s head of research, technology and society. Our science editor, Alok Jha, will moderate the discussion. https://www.economist.com/subscriber-events/ai-science-and-society-demis-hassabis-and-james-manyika-hub

- Pedro

Read on Substack

Why Generative AI Is Missing from CEOs’ Top Priorities

For me, it’s truly puzzling why Generative AI hasn’t made it into the top five priorities on CEOs’ agendas, considering it’s the most disruptive technology of the last 20 years. There’s a striking disconnect between the hype and investment we see in the tech sector compared to its adoption in other industries. Several factors may explain this gap. Many members of the C-suite, including CIOs, lack the technical acumen to fully comprehend the transformative potential of Generative AI. Additionally, the risk-reward calculus of large organizations often leans heavily toward minimizing risks, even at the cost of forgoing significant rewards. An insightful article by The Economist (linked below) delves into this fascinating conundrum. (text revised by a LLM) https://www.economist.com/business/2024/11/04/why-your-company-is-struggling-to-scale-up-generative-ai

- Pedro

Read on Substack

Dynamic Pricing Silver Bullet?

https://www.ibbaka.com/blog/2019/11/7/dynamic-pricing-is-a-two-edged-sword

Fully agree with this great post! When you only have (want to sell) a hammer everything looks like a nail. Every solution has its value and should be applied accordingly and we should avoid to go with the latest trend flow and thoroughly assess the pros & cons and look at the value fundamentals. "...The conflation of willingness to pay and differentiated value has to come to an end. Willingness to pay is an outcome of the creation, communication and delivery of differentiated value. It is an outcome and not a driver. Pretending that you understand value because you can estimate willingness to pay is wrong headed. ..."

Automation Isn’t About to Make Truckers Obsolete

Automation Isn’t About to Make Truckers Obsolete

Interesting article on AI and the impact on the auto-industry and specially the trucking activity.

As always in order to fully understand a problem you should analyze in its different workable variables and then make an assessment, is not doomsday (although it will impact several person)but most probably will be a pivotal one specifically for the current truck drivers