1. Toronto's pedestrian tunnel system, The Path, that emerged in response to congestion in the main streets.
In the early twentieth century, Toronto’s businesses developed a novel response to this. They began to create pedestrian tunnels from their offices to the metro stations so that their employees could flow in smoothly, avoiding the congested streets (and, in winter, the cold). Shops quickly started to be added. After a few businesses had done this, a ‘network effect’ emerged whereby other businesses started to add their own tunnels to the system, benefiting from the existing tunnels while also making them more useful. It became routine for downtown developers to tie new office blocks into the network. Over many decades, a sort of ‘pedestrian metro’ emerged.Known as the Path, the network today stretches for more than 30 kilometers, linking nearly all central metro and railway stations with many of the major office buildings. Although the Path forms a unified network, it is not in unified ownership: it is divided into some 35 chunks, each of which is still owned and managed separately by descendants of whichever business originally contributed it. Many branches of the Path thus terminate in the lobbies of office buildings, with the curious result that these grand spaces function as metro entrances for the general public. The municipal authorities play only a limited regulatory role.The Path is unlike the gloomy and malodorous underpasses with which most of us are familiar. It is expensively decorated and feels like a high-end shopping mall, which in a way it is. It is extremely clean and closely policed by dozens of private security teams. Until recently, it was thronged with shoppers: this use suffered in the pandemic and has not wholly recovered, but the Path is still used for its original commuting purpose by hundreds of thousands of people every weekday.
2. Nvidia has a new rival for its GPU chips, Google's tensor processing units (TPUs), which it used to train its latest Gemini 3 LLM.
Nvidia’s customers have a big incentive to explore cheaper alternatives. Bernstein, an investment-research firm, estimates that Nvidia’s GPUs account for over two-thirds of the cost of a typical AI server rack. Google’s TPUs cost between a half and a tenth as much as an equivalent Nvidia chip. Those savings matter, given the vast sums currently being poured into computing power for AI. Bloomberg Intelligence, another research group, expects Google’s capital expenditures to hit $95bn next year, with nearly three-quarters of that being used to train and run AI models.
But Nvidia's moat is unlikely to disappear.
For Nvidia’s other customers, however, switching to Google’s chips will not be straightforward. Nvidia’s edge lies partly in CUDA, the software platform that helps programmers make use of its GPUs. AI developers have become accustomed to it. And whereas the software surrounding TPUs has been created with Google’s own products in mind, including search, CUDA is intended to cater to a wide range of applications. What is more, reckons Jay Goldberg of Seaport Research Partners, an industry analyst, there may be a limit to Google’s willingness to sell its TPU; it could prefer instead to steer prospective customers towards its lucrative cloud-computing service. To stymie its AI competitors, Google may also be tempted to keep prices for its chips high.
3. AI adoption is stalling, so says a survey by statisticians at the US Census Bureau. It finds that the employement-weighted share of Americans using AI at work has fallen by a percentage point to 11%, and has fallen sharply at the largest businesses.
The article has this description of the challenge facing the AI market.
From today until 2030 big tech firms will spend $5trn on infrastructure to supply AI services. To make those investments worthwhile, they will need on the order of $650bn a year in AI revenues, according to JPMorgan Chase, a bank, up from about $50bn a year today. People paying for AI in their personal lives will probably buy only a fraction of what is ultimately required. Businesses must do the rest... Jon Hartley of Stanford University and colleagues found that in September 37% of Americans used generative ai at work, down from 46% in June. A tracker by Alex Bick of the Federal Reserve Bank of St Louis and colleagues revealed that, in August 2024, 12.1% of working-age adults used generative AI every day at work. A year later 12.6% did. Ramp, a fintech firm, finds that in early 2025 AI use soared at American firms to 40%, before levelling off. The growth in adoption really does seem to be slowing...According to a poll of executives by Deloitte, a consultancy, and the Centre for AI, Management and Organisation at Hong Kong University, 45% reported returns from AI initiatives that were below their expectations. Only 10% reported their expectations being exceeded. A study by McKinsey, another consultancy, argued that for most organisations, the use of aihas not yet significantly affected enterprise-wide profits... A paper by Yvonne Chen of ShanghaiTech University and colleagues refers to “genAI's mediocrity trap”. With the assistance of the tech, people can produce something “good enough”. This helps weaker workers. But the paper finds it can harm the productivity of better ones, who decide to work less hard.
4. India has caught up with China in education imports from the US (or students travelling to the US to study there). India's exports have doubled in just three years.
5. Striking statistic about private credit and insurance.
Close to 37 per cent of North American life insurance investments are allocated to private credit. But private credit encompasses a world of different types of lending — from private placements and commercial real estate lending to asset-based finance and fund finance — in which they have long-standing expertise.
Banks are also big lenders to private credit firms.
6. Comparing AI investments with those in railways in the 19th century.
The railways, for example, were considered similarly transformative in the 19th century... As a percentage of investment in the United Kingdom, the world’s economic behemoth in the mid-Victorian period, domestic railways accounted for perhaps half. This was at the peak of the mania, in the 1840s. But even over the longer term, railway investment accounted for around a fifth of total investment over the four decades after George IV died in 1830. Around the turn of the century, railway bonds and shares accounted for between a quarter and a third of household financial portfolios in Britain. In the United States, during various railway-building booms (the 1840s, the 1870s), investment in the sector accounted for 40 per cent of total investment in the economy. At some points, it accounted for almost 10 per cent of gross domestic product (GDP)... AI investment may have accounted for all of US GDP growth in the first half of this year, but that still means only a couple of percentage points of GDP, as compared to the 6-10 per cent that was routinely achieved during railway booms.
The MSCI India index has returned 2.5 per cent in dollar terms this year compared with 27.7 per cent for the MSCI Emerging Markets index, India’s weakest relative performance since 1993. Foreign investors have pulled more than $16bn out of India this year, the second-largest drawdown on record
9. Rising interest rates in Japan are bringing to an end decades of the yen carry trade which allowed western markets to benefit from Japan's savings.
To get a sense of how little electricity people use in sub-Saharan Africa, imagine each person there turning on a single 50-watt light bulb. That alone would instantly double electricity consumption. Nigeria, with 240m people, generates less electricity than the American state of Wyoming, which has 0.6m inhabitants. Uganda, with 50m people, produces less than Latvia, which has a population of 1.9m. Around 600m Africans have no electricity at all.
11. A good summary of the Indigo fiasco that is now playing out in India.
The story begins with pilot associations filing petitions in the Delhi High Court around 2019-20, pushing for stricter rules regarding pilot fatigue. The High Court repeatedly questioned India’s Directorate General of Civil Aviation about updating its rules on pilot fatigue and, in response, the DGCA unleashed the Flight Duty Time Limitations (FDTL) rules... FDTL is a set of safety regulations that determines how long a pilot can work, how much rest they must get, and how many night flights they can operate... These rules were notified in January 2024 and were to come into full effect on November 1, 2025. IndiGo has now admitted that it did not plan adequately for these changes and thus faced pilot and crew shortages, which have led to this mayhem.
This is an important aspect about what happens when a dominant market player defaults in an infrastructure sector.
In advanced economies, the repercussions would be through the markets and the courts. The markets are the first recourse – customers would punish the airline by choosing alternatives, and the company would have to go out of its way to win back market share. The problem, however, is the lack of alternatives in India, which was one of the main causes of such a scenario in the first place. IndiGo commands about 65 per cent of the market share, which translates to roughly two out of every three domestic flyers in India being on IndiGo on an average day, with the rest of the industry effectively competing for the remaining third. This enormous market power means that customers, despite themselves, might have to choose IndiGo again for their travel needs due to the lack of options.
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