Economist: “The heft that JPMorgan has developed under Mr Dimon provides the bank with a compounding advantage. Wall Street executives moan about how hard it is to compete across JPMorgan’s full range of businesses. The bank has an enormous base of $2.5trn in deposits. Over the past two years it has paid out $190bn in interest on deposits, while hoovering up $374bn in interest on loans. Yet the bank is not just larger than its rivals—it is also more streamlined. Its efficiency ratio (non-interest expenses as a share of total revenue) has dropped from 61% in 2015 to 51%, a figure that is 15 percentage points lower than any competitor. Increasingly, JPMorgan’s competition is to be found outside banking. “I want us to be better than the best in class, which is in many ways the non-bank trading houses,” says Mr Rohrbaugh. “In other parts of our business, like in payments, we’re not only competing against the big banks, we’re competing against fintechs.” Vast trading firms such as Citadel and Jane Street have grown into market-making activities once dominated by banks, while techy upstarts such as Stripe eat into payments.
NYTimes: “No part of the entertainment business has more to lose — and gain — from A.I. than animation. The $420 billion global animation industry (movies, television cartoons, games, anime) has long been dominated by computer-generated imagery; Walt Disney Animation hasn’t released a hand-drawn film since 2011. In other words, unlike much of Hollywood, animation companies are not technophobic. Even with computers, however, the process of making an animated movie (or even a cartoon) remains extraordinarily expensive, requiring squadrons of artists, animators, graphic designers, 3-D modelers and other craftspeople. Studios have a big incentive to find a more efficient way, and A.I can already do many of those things far faster, with far fewer people.”
Fortune: “Gemini Diffusion is part of a trajectory that many in the AI field had anticipated, according to Stefano Ermon, an associate professor in the department of computer science at Stanford University who has been working on diffusion models for the past five years. He is also the co-founder of Inception Labs, which announced the first diffusion large language model a few months ago, called Mercury. The model matched the performance of frontier models optimized for speed, while running five to ten times faster. “Google’s entry into this space validates the direction we’ve been pursuing,” he told Fortune by email. “It’s exciting to see the broader industry embracing these techniques, though we’re already working on training the next generation of text diffusion models.” Within a few years, he added that he expected “all frontier models will be diffusion models.””
The Daily Economy: “Entrepreneurship not only exists in real-world markets; it’s an essential feature of modern capitalism. And because entrepreneurs unleash real change – change that’s unforeseeable – entrepreneurs unleash real uncertainty.”
FT: “There is unlikely to be an “‘iPhone moment” for AI hardware. To be effective, artificial intelligence needs to be everywhere and nowhere. It needs to be in every device, enhancing every type of digital experience. But it also needs to retreat into the background, anticipating and completing tasks behind the scenes. This suggests there will not be one single hardware form-factor capable of turning AI into a hit consumer product. Instead, the technology looks set to give a lift to a range of new markets, from smart glasses to inconspicuous “wearables”, while also adding extra value to the gadgets people already use most in their lives. The biggest opportunity for OpenAI lies in using its AI to animate all of these devices.”
