Ch 1 notes the big shift over the past decade has been better infra–physical+digital. Roads+railways are growing fast. Digital payments and electronic forms work.
This reflects Modi’s forte–executing big projects
3/ Ch 2+3 continues on India's relative strengths--the financial and corporate sectors
Contra to narratives of crony capitalism, mkt concentration is actually falling in India. Modi favours national champions, but less than you might think economist.com/special-report…
4/ Ch 4 is the tricky trio. It’s well-known that 🇮🇳 is an IT services superpower, but the govt wants it to be a manufacturing power too
There is some success–14% of iPhones are now assembled in India. But corp investment and exports have yet to budge economist.com/special-report…
5/ Why has🇮🇳struggled to⬆️investment and beat 6% growth?
Historical reforms left state-level red tape on land/labour/power mostly untouched
Mass education remains poor contributing to a weak labour mkt. Strongman govt and rising protectionism don’t help economist.com/special-report…
6/ Our final chapter lays out a reform agenda touching on everything form innovation policy to beefing up city governance
A striking stat: only 15% of Indian govt employees work at the local level vs 60% in 🇨🇳 or 🇺🇸 leading to poor state capacity economist.com/special-report…
7/ The problem is that the needed reform requires buy-in from states and social groups that might lose from change. But Modi’s weakness has been building such a consensus
NEW in @TheEconomist. Industry labs have driven rapid progress in large-scale AI leading to @OpenAI's ChatGPT. I ask:
1. Why did academia pass the baton to firms? 2. Does Google's LaMDA (which I got access to) or ChatGPT give better dating advice? 3. Where are things headed? 1/
First, industry is leading the way in large-scale AI (though it builds on years of work from academia). Why?
- Training big models is computationally intensive and therefore expensive
- In AI research outputs can rapidly be commercialised (a herald to the era of Bell Labs) 2/
Second, ChatGPT is not the only game in town.
Some Googlers helped me compare ChatGPT and LaMDA (Google's currently-private chatbot model). We asked math and reading questions, and also for some dating advice. Some results below, but in short, ChatGPT faces stiff competition 3/
New piece in @TheEconomist! An important second-order impact of remote work: Firm “boundaries” are blurring.
Remote work changes the calculus of what to do, and crucially, what not to do. It boosts freelancing, outsourcing and offshoring, just as Coase would predict: 1/
First, skilled jobs are more distributed across geographies, in part reflecting a rise in remote work.
Second, cross-border service exports, including IT services, are booming.
Third, the market for skilled freelancers has doubled since 2018.
Fourth, perhaps most interestingly, as firm's grow in size, and adopt more technologies, their "outsourcing intensity" grows.
This can be seen by looking at what share of a firm's cost of sales is purchased from other firms.