Deirdre McCloskey: “What are the virtues of capitalism? Trying things out. The only way to get new things, such as we have to an astonishing degree since the liberal revolutions of the 19th century is to let ordinary people “have a go” (as the English say), is through trying out commercially tested betterment. If an electric car in 1900 is a failure in the market, the age of internal combustion engines comes. If it succeeds in 2000, the age of electric cars comes. The government is ill-equipped to choose such winners. The other virtue is massive altruism. A novelty does not survive a commercial test unless it is profitable. Being profitable means that the entrepreneur has found something that masses of people find desirable, such as central heating in cold countries or cheap air conditioning in hot. Being unprofitable means that you are harming people on balance, wasting resources to make things they do not want. Markets are the most altruistic system we have. Governments, by contrast, are systems of coercion, by definition producing what people do not want, worsened by corruption impossible in mutually advantageous exchange.” [via CafeHayek]
Ben Thompson: “The broader issue is that the video industry finally seems to be facing what happened to the print and music industry before them: the Internet comes bearing gifts like infinite capacity and free distribution, but those gifts are a poisoned chalice for industries predicated on scarcity. When anyone could publish text, most text-based businesses went from massive profitability to terminal decline; when anyone could distribute music the music industry could only be saved by tech companies like Spotify helping them sell convenience in place of plastic discs. For the video industry the first step to survival must be to retreat to what they are good at — producing content that isn’t available anywhere else — and getting away from what they are not, i.e. running undifferentiated streaming services with massive direct costs and even larger opportunity ones. Talent, meanwhile, has to realize that they and the studios are not divided by this new paradigm, but jointly threatened: the Internet is bad news for content producers with outsized costs, and long-term sustainability will be that much harder to achieve if the focus is on increasing them.”
Martin Wolf: “Where is India now and where might it go, economically and politically?…Let us assume that India’s GDP per head continues to grow at 5 per cent a year, while that of the US grows at 1.4 per cent, roughly as it has over the last three decades. Then, by 2050, India’s GDP per head (at purchasing power) would reach about 30 per cent of US levels, roughly where China’s is today. According to UN median forecasts, India’s population would also be 4.4 times as big as that of the US. So, its economy would be some 30 per cent larger than the US’s. It is, in sum, quite reasonable to assume that India will become a great power. It is not that hard to imagine that its economy will be of a similar size to that of the US by 2050. Thus, western leaders are making a sensible bet on an alliance of convenience with India.”
FT: “Artificial intelligence companies are exploring a new avenue to obtain the massive amounts of data needed to develop powerful generative models: creating the information from scratch. Microsoft, OpenAI and Cohere are among the groups testing the use of so-called synthetic data — computer-generated information to train their AI systems known as large language models (LLMs) — as they reach the limits of human-made data that can further improve the cutting-edge technology…Generic data from the web is no longer good enough to push the performance of AI models, according to developers. “If you could get all the data that you needed off the web, that would be fantastic,” said Aidan Gomez, chief executive of $2bn LLM start-up Cohere. “In reality, the web is so noisy and messy that it’s not really representative of the data that you want. The web just doesn’t do everything we need.”…The new trend of using synthetic data sidesteps this costly requirement. Instead, companies can use AI models to produce text, code or more complex information related to healthcare or financial fraud. This synthetic data is then used to train advanced LLMs to become ever more capable.” Jayant Sinha: “Amidst challenges, India can thrive with transformative opportunities in AI, innovative batteries, nuclear fusion, and manufacturing growth, paving the way for sustainable prosperity.”
