Month: September 2023

Enlarge / The Raspberry Pi 5's custom I/O chip, the RP1, is the result of $15M in investment over seven years. It unlocks far more data and storage capabilities in the single-board platform. (credit: Raspberry Pi)

Nearly everything on the Raspberry Pi 5 has improved over the 4 model, particularly the way you can buy it. In a first for the single-board company, the 5 is available for preorder today from approved resellers before it's generally available by the end of October.

Perhaps most importantly, the 5 is being prioritized for individual buyers rather than commercial partners.

"We’re incredibly grateful to the community of makers and hackers who make Raspberry Pi what it is; you’ve been extraordinarily patient throughout the supply chain issues that have made our work so challenging over the last couple of years," writes Raspberry Pi founder and CEO Eben Upton. "We’d like to thank you: we’re going to ringfence all of the Raspberry Pi 5s we sell until at least the end of the year for single-unit sales to individuals, so you get the first bite of the cherry."

Enlarge / Hurricane Irma as seen by satellite in 2019. (credit: NOAA)

Hurricane Lee wasn’t bothering anyone in early September, churning far out at sea somewhere between Africa and North America. A wall of high pressure stood in its westward path, poised to deflect the storm away from Florida and in a grand arc northeast. Heading where, exactly? It was 10 days out from the earliest possible landfall—eons in weather forecasting—but meteorologists at the European Centre for Medium-Range Weather Forecasts, or ECMWF, were watching closely. The tiniest uncertainties could make the difference between a rainy day in Scotland or serious trouble for the US Northeast.

Typically, weather forecasters would rely on models of atmospheric physics to make that call. This time, they had another tool: a new generation of AI-based weather models developed by chipmaker Nvidia, Chinese tech giant Huawei, and Google’s AI unit DeepMind. For Lee, the three tech-company models predicted a path that would strike somewhere between Rhode Island and Nova Scotia—forecasts that generally agreed with the official physics-based outlook. Land-ho, somewhere. The devil, of course, was in the details.

Weather forecasters describe the arrival of AI models with language that seems out of place in their forward-looking profession: “Sudden.” “Unexpected.” “It seemed to just come out of nowhere,” says Mark DeMaria, an atmospheric scientist at Colorado State University who recently retired from leading a division of the US National Hurricane Center. When he started a project this year with the US National Oceanographic and Atmospheric Administration to validate Nvidia’s FourCastNet model against real-time storm data, he was a “skeptic” of the new models, he says. “I thought there was no chance that it could work.”

Enlarge (credit: Aurich Lawson | Getty Images)

The world has been flooded with misinformation. Falsehoods and conspiracy theories bubble up on everything from the weather to vaccines to the shape of the Earth. Purveyors of this garbage may be motivated by attention, money, or simply the appeal of sticking it to the educated elite. For people who try to keep both feet planted in the real world, it's enough to make you want to scream. Even if you spend 24 hours a day pushing back against the wrongness on the Internet, it seems impossible to make a dent in it.

I've been pondering this, and I've decided that we need a way to target the worst sources of misinformation—a way to identify the people who are both the most wrong and the most dangerous. So, as a bit of a thought experiment, I started playing with a simplified scoring system for misinformation merchants.

I'm calling it the 10-point Ladapo scale in honor of the surgeon general of Florida, for reasons I hope are obvious. Any person can be given a score of zero or one (fractions are discouraged) for each of the following questions; scores are then totaled to provide a composite picture of just how bad any source is. To help you understand how to use it, we'll go through the questions and provide a sense of how each should be scored. We'll then apply the Ladapo scale to a couple of real-world examples.