Multiple locations — the most-requested Weathergraph feature — is finally here.
Save home, work, your favourite trails, or your next destination. Switch between them instantly with a single tap.
Finally. This is still my favorite weather app. As with the forecast provider toggle, the location toggle works on the main graph (and retains your scroll position) but not within a daily forecast.
Previously:
Fifteen years ago, we started work on the Dark Sky weather app.
[…]
We enjoyed our time at Apple. So why did we leave to start another weather company?
It’s simple: when looking at the landscape of the countless weather apps out there, many of them lovely, we found ourselves feeling unsatisfied.
[…]
Our homegrown forecasts are produced using many different data sources, including numerical weather prediction models, satellite data, ground station observations, and radar data. Most of the time, our forecast will be a reliable source of information (it’s better than the one we had at Dark Sky). But, crucially, we supplement the main forecast with a spread of alternate predictions. These are additional forecast lines that capture a range of alternate possible outcomes[…]
The main two things I want, which previous apps didn’t provide, are an easy way to see different predictions for the same location (since there can be huge variance, e.g. in the number of inches of snow) and different locations at the same future time (to help decide where I should go). This tries to address the first half, though it doesn’t seem to give a range of alternate predictions for the amount of snow, only the likelihood of precipitation and its subjective intensity.
If you see widely separated lines, there’s a greater chance that conditions will vary from what Acme’s model expects, whereas a tight cluster of lines gives you greater confidence as you walk out the door.
[…]
Beneath the hourly conditions graph, Acme displays a horizontally scrolling list of weather stats. Swiping between them repopulates the graph with whichever forecast metric you want. It’s a lot of data, and it’s all accessible without scrolling vertically or switching views, which I love. Also, when precipitation is on its way, the app displays an additional graph with minute-by-minute details for the upcoming hour.
[…]
Acme Weather includes an unusual emphasis on notifications, too. Instead of relegating the feature to the app’s settings, Acme dedicates an entire tab to it. In a world of notification overload, that’s a bold move, but it works. That’s because Acme puts its users in the driver’s seat, offering fine-grained control over the notifications you receive.
What strikes me most about the app is how well it takes large amounts of information and distills that into an interface that is actually readable.
I’ve thought before that I’d like error ranges in weather graphs. Alternative predictions aren’t quite how I’d imagined it. Showing some detail/personality/confidence level for the alternative prediction lines might help. This might also be solved by time with the app to learn how surprising the weather turns out to be when predictions were divergent.
Cumulative precipitation could use another dimension to the data to show either soon-ness in the next 24 hours or how short of a time period is predicted to deliver most of the rainfall. That’s a hard data visualization problem.
Previously:
Maggie Harrison Dupré (Hacker News, more context):
The Condé Nast-owned Ars Technica has terminated senior AI reporter Benj Edwards following a controversy over his role in the publication and retraction of an article that included AI-fabricated quotes, Futurism has confirmed.
Earlier this month, Ars retracted the story after it was found to include fake quotes attributed to a real person. The article — a write-up of a viral incident in which an AI agent seemingly published a hit piece about a human engineer named Scott Shambaugh — was initially published on February 13. After Shambaugh pointed out that he’d never said the quotes attributed to him, Ars’ editor-in-chief Ken Fisher apologized in an editor’s note, in which he confirmed that the piece included “fabricated quotations generated by an AI tool and attributed to a source who did not say them” and characterized the error as a “serious failure of our standards.”
I’ve enjoyed Edwards’ work over the years and linked to many of his pieces, but obviously this is a very serious offense.
The individual firing is a distraction from the structural issue. Newsrooms have been cutting editorial staff for a decade, which means the verification layers that would have caught this — fact-checkers, copy editors, senior editors doing source verification — largely don’t exist anymore. Then they adopt AI tools that increase throughput without increasing oversight capacity, and act surprised when fabrication slips through.
This is a classic systems failure: you remove the safety mechanisms, add a new source of risk, and punish the individual operator. It’s the same pattern you see in industrial accidents.
This has been going on for a lot longer than a decade. To me, the takeaway is not that it’s the system’s fault but that many of these media brands are operating on undeserved trust. There’s a lot less checking going on than there used be or that you might imagine.
The other interesting point is that Edwards says the intent was not to use AI to fabricate quotes but as a tool for processing quotes he already had:
During the process, I decided to try an experimental Claude Code-based Al tool to help me extract relevant verbatim source material. Not to generate the article but to help list structured references I could put in my outline.
[…]
I inadvertently ended up with a paraphrased version of Shambaugh’s words rather than his actual words.
Being sick and rushing to finish, I failed to verify the quotes in my outline notes against the original blog source before including them in my draft.
This seems not so different from how I commonly hear people say that they use AI to collect/extract or reformat information into a table. I’ve never understood, given the propensity for hallucination and citing papers that don’t exist, why such a distillation should be trusted. Yet I know that people are already relying on such LLM-derived works to make decisions. At least with code, you can compile it and test it and read it to see whether it makes sense. With a number in a table cell, how can you easily check where it came from?
Previously:
Todd Bishop (via Adam Engst):
In early 1984, Paul Brainerd and four engineers packed into his old Saab and another car and drove south on Interstate 5 from Seattle. They had been laid off after Kodak bought their employer, Atex, a company whose computerized text-processing systems let newspaper reporters and editors write and edit stories on video terminals instead of typewriters.
They had six months of savings, a rough idea for a piece of software, and no company name.
What happened next was documented years later in oral history interviews with Brainerd for the Computer History Museum, and Seattle’s Museum of History and Industry.
[…]
Paul Brainerd, who went on to coin the term “desktop publishing” and build Aldus Corporation’s PageMaker into one of the defining programs of the personal computer era, died Sunday at his home[…]
It’s not hyperbole to say I wouldn’t be where I am today without PageMaker. My school paper had a Mac Plus and swapped 3.5-in disks often to run both the Mac and PageMaker.
Desktop publishing was one of the biggest reasons I obsessed over computers in the late ’80s and early ’90s. Though I spent more of my time in QuarkXPress than PageMaker, I can trace my early creative and business ambitions to the software and industry Brainerd pioneered.
