Recent, rapid ocean warming ahead of El Niño alarms scientists

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Recent, rapid ocean warming ahead of El Niño alarms scientists

In March, sea surface temperatures off the east coast of North America were as much as 13.8C higher than the 1981-2011 average.

"It's not yet well established, why such a rapid change, and such a huge change is happening," said Karina Von Schuckmann, the lead author of the new study and an oceanographer at the research group Mercator Ocean International.

"We have doubled the heat in the climate system the last 15 years, I don't want to say this is climate change, or natural variability or a mixture of both, we don't know yet. But we do see this change."

One factor that could be influencing the level of heat going into the oceans is, interestingly, a reduction in pollution from shipping.

In 2020, the International Maritime Organisation put in place a regulation to reduce the sulphur content of fuel burned by ships.

This has had a rapid impact, reducing the amount of aerosol particles released into the atmosphere.

But aerosols that dirty the air also help reflect heat back into space - removing them may have caused more heat to enter the waters.

Electric Streetcar | Kenosha, WI

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Electric Streetcar | Kenosha, WI

Beautifully restored electric streetcars travel a 2-mile loop, providing a scenic tour of the Lake Michigan shoreline, HarborPark, the Sculpture Walk, two historic districts, and Downtown Kenosha. Ride the streetcar to restaurants, shops, museums, lakefront events, and more.

Stops include the Kenosha Transit Center, 8th Ave. and 54th St., and the METRA train station.

From 1903 to 1932, electric rail was a regular mode of transportation in Kenosha. On June 17, 2000, streetcar transportation returned to our community. Most of Kenosha’s streetcars are authentic 1951 President’s Conference Committee (PCC) cars. Each Kenosha streetcar has a name and color scheme that represents the legacy of streetcar transportation in North America.

Where I think ChatGPT and Machine Learning is Going in Computing 🤖

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Like many people I’ve been following closely both the hype and reality of ChatGPT. At the same time, I’ve been learning a lot about different forms of machine learning, and how they can be used to enhance computing, especially as computers grow in power. I also have been using computers for more then a quarter century, so I have some ideas on where machine learning could be useful for every day uses, while other cases were not so useful.

Things I Don’t Think We’ll See in the Future

  • ChatGPT is not going to replace writers, artists, or secretaries except for the most basic tasks
  • ChatGPT will not ever write quality news articles, press releases, or publications.
  • Natural language searches will not become the norm, as it’s a lot of typing or speaking and prone to mistakes, however machine learning will continue to be applied to both search terms and results to get more useful results

Things I Think We’ll See in the Future

  • Machine learning will be applied to people’s personal computer file system to better flag mistakes in documents, like in Microsoft Word. If for example, you regularly type out a press release or a report a certain way in Word, and something is different format-wise or stylistically in your current version, your Word processor would flag if not automatically fix it.
  • Machine learning could automatically generate templates based on previously saved documents on your computer, allowing you just to update and fill in the details of the document.
  • Machine learning would be used for resizing and colorizing photos in Gimp and Adobe Photoshop, automatically tracing edges, vectorizing and detecting words.
  • Machine learning would make the creation of graphics more automated, by creating sensible styles, and anticipating your next move.
  • Command line code would be far better automated, with much better tab competition both based on the commands others have used, and what you have previously run
  • Basically, any process you run on your computer would have much more tab completion, with the computer automatically predicting your likely next move, helping to speed up processing, as the computer could start working on the likely next step

I don’t anticipate the centralized machine learning model, with vast databases getting that much play. Internet access can be funky, and people are often hesitant to share data. It’s risky to be too reliant on other people’s servers. But I do think machine learning is going to only grow in importance on desktop computers, with more and more predictions made locally to assist users in getting tasks done quicker on their computers.