Is It Really Worth It? Apple, Michigan taxpayers, and one of Detroit's wealthiest families spent roughly $30 million training hundreds of people to build iPhone apps. Two years ago, Lizmary Fernandez took a detour from studying to be an immigration attorney to join a free Apple course for making iPhone apps . The Apple Developer Academy in Detroit launched as part of the company's $200 million response to the Black Lives Matter protests and aims to expand opportunities for people of color in the country's poorest big city. But Fernandez found the program's cost-of-living stipend lacking--"A lot of us got on food stamps," she says--and the coursework insufficient for landing a coding job. "I didn't have the experience or portfolio," says the 25-year-old, who is now a flight attendant and preparing to apply to law school. "Coding is not something I got back to."

Data quality is a crucial factor in the performance of machine learning models, a principle that dataset distillation methods exploit by compressing training datasets into much smaller counterparts that maintain similar downstream performance. Understanding how and why data distillation methods work is vital not only for improving these methods but also for revealing fundamental characteristics of "good" training data. However, a major challenge in achieving this goal is the observation that distillation approaches, which rely on sophisticated but mostly disparate methods to generate synthetic data, have little in common with each other. In this work, we highlight a largely overlooked aspect common to most of these methods: the use of soft (probabilistic) labels. Through a series of ablation experiments, we study the role of soft labels in depth.

If AI could let you speak with your deceased loved ones again, would you take the chance? A few companies and experts believe this will soon be possible, and some are even starting to market their own solutions. Nothing supernatural about their proposal; what they are offering is, rather, the ability to talk to a digital representation of the dead, fine-tuned by combining large language models like GPT-4, speech synthesis and AI generation tools. In China, as the Strait Times reports, some funeral companies are rapidly bringing the worship of the deceased into the digital age, allowing relatives to speak to a digital avatar of the dearly departed. Many have started offering this service in early April, around the time of the Qing Ming Festival (or Tomb Sweeping Day), a public holiday when people remember and honor the dead. One of them, funeral services provider Shanghai Fushouyun, started even earlier, conducting its first AI-assisted funeral in January 2022, when colleagues and students of a deceased Chinese surgeon had the opportunity to chat with his digital replica on a screen, for a final farewell.

The Web3 hype has dulled and artificial intelligence is taking its place. AI has entered the mainstream and people are using it to create artwork or write novels, captions or marketing copy. For creators, AI could serve as a personal assistant to design their YouTube thumbnails or draft podcast scripts. But some worry that the new technology will become smart enough to make them redundant. James Currier, general partner at seed-stage venture capital firm NFX, said AI won't replace creators, but will help them produce more and better content.