Nathan Baschez: “What holds a social app together? Ask any tech enthusiast and they will quickly tell you: network effects. Put simply, social apps allow us to communicate with familiar faces in a familiar way, and they make it easy to meet new people. Starting a new social app is kind of like starting a new town: it’s just a bunch of empty space at first. This is why most social apps fail. New networks usually are formed when a new way of communicating is enabled by a technology shift. Broadband internet and flash video enabled YouTube. SMS enabled Twitter. Mobile photography enabled Instagram. Today it feels like we’re living through another important cultural shift—the decline of Twitter—and a new generation of networks are experimenting with new structures to try and capitalize on it. If we want to understand what’s next, it helps to ask: What caused the culture shift? What new structures would be better? And what will it feel like to use the internet in the future?”
NYTimes: “We do remain dependent on traditional gig labor, a fact that blazed into our collective consciousness with the pandemic and our sudden reliance on workers like delivery drivers. What is less often appreciated, though, is just how much, and how steadily, the structure and technology of gig work have expanded beyond our most obviously “Uberized” jobs. The gig economy, at this point, encompasses not just drivers or repairmen, not just designers or proofreaders, but also retail workers, the armies of itinerant nurses who crossed the country to shifting Covid hot spots and even white-collar professionals like lawyers and consultants. Whether they seem like “gigs” or not, countless varieties of jobs are sliding into the ecosystem of the gig — the world, broadly defined, of technology-enabled temporary employment — and steadily loosening the ties between workers and employers.”
WSJ: “With the new generative AI tools, like ChatGPT, anyone can put in a prompt—type in a few words and get a result. But that doesn’t mean that the results will be relevant or accurate. The key is putting in the right prompt. The fact that you can communicate with the latest AI systems in plain English “is very deceptive,” says Peter Lin, a computer-science professor at the University of Waterloo. That’s why some businesses are now hiring prompt engineers—people with the skills, background and practice to talk to so-called large-language AI systems effectively—and why many people expect prompt engineering to be a desirable skill for many kinds of workers to add to their resumes.”
FT: “As co-founder of the database software company, Ellison had long owned around a fifth of the stock. Then, just over a decade ago, Oracle started repurchasing its shares in earnest, ploughing much of its free cash flow — along with tens of billions that it borrowed — into one of the biggest buyback programmes in corporate history. Simply by sitting on his holding and not selling, Ellison has seen his personal stake increase steadily, to reach 43 per cent of Oracle…Along with a history of solid if unspectacular earnings, this judicious financial engineering has boosted the value of Ellison’s stake more than three-fold. His personal fortune has soared to more than $100bn, making him the world’s fourth-richest person, according to Forbes.”
