With a name like Colt Wrangler, it’s safe to assume that the man is from Texas and probably a bit of a cowboy. Hot dang if you aren’t right on both counts—Colt has been riding broncos and bulls competitively since he was a kid. But what you’re less likely to guess, is that this young cowpoke is also one of the most impressive motorcycle builders to emerge from the US custom scene in recent years.

Since Colt Wrangler Motorcycles was founded in 2015, Colt has established a distinct design language of his own. Recognizable by their high-level sheet-metal work, his builds exist in perfect proportion and hold high-performance details for those that know what they’re looking at—or even better, for those lucky enough to ride them.

We have featured Cole’s bikes before. But with more time to work on his latest project—a 1999 Harley-Davidson Sportster—he’s taken his personal style to new heights.

Colt had just started the Harley Sportster project, working in collaboration with local Texas truck builders Vintage Vendetta Garage, when Roland Sands Design announced the Dream Build-Off. This was a competition for local shops and backyard builders, with new motorcycles from BMW, Indian, and Royal Enfield as prizes. The Sportster was originally supposed to be a street-ready scrambler, but with this added motivation, Colt went

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By: Morgan Gales
Title: Giddy up: Colt Wrangler’s prizewinning Harley Sportster
Sourced From: www.bikeexif.com/custom-harley-sportster-colt-wrangler
Published Date: Fri, 19 May 2023 17:01:46 +0000

Kaytranada and Aminé have joined forces to deliver on their captivating new collab album, KAYTRAMINÉ. As you’ll hear below, the highly-anticipated project showcases the unique and genre-blending abilities of both artists; from Kaytranada’s signature production style and Aminé’s charismatic flow, the EP is a sonic journey that arrives just in time for summer. The duo effortlessly combines elements of hip-hop, R&B, and electronic music, pushing boundaries and creating a refreshing sound that defies categorization. Hear what we mean by streaming the album below and let us know your thoughts in the comments section as well.

KAYTRAMINÉ (Self Titled) | Stream

‘LISTEN: Kaytranda & Aminé Unleash Anticipated Collaborative Album, “KAYTRAMINÉ”

The post LISTEN: Kaytranda & Aminé Unleash Anticipated Collaborative Album, “KAYTRAMINÉ” appeared first on Run The Trap: The Best EDM, Hip Hop & Trap Music.

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By: Max Chung
Title: LISTEN: Kaytranda & Aminé Unleash Anticipated Collaborative Album, “KAYTRAMINÉ”
Sourced From: runthetrap.com/2023/05/20/listen-kaytranda-amine-unleash-anticipated-collaborative-album-kaytramine/
Published Date: Sat, 20 May 2023 19:49:30 +0000

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Did you miss our previous article…
https://mansbrand.com/monolink-releases-new-track-the-silence-featuring-stephan-jolk/

It’s an evening in 1531, in the city of Venice. In a printer’s workshop, an apprentice labors over the layout of a page that’s destined for an astronomy textbook—a dense line of type and a woodblock illustration of a cherubic head observing shapes moving through the cosmos, representing a lunar eclipse.

Like all aspects of book production in the 16th century, it’s a time-consuming process, but one that allows knowledge to spread with unprecedented speed.

Five hundred years later, the production of information is a different beast entirely: terabytes of images, video, and text in torrents of digital data that circulate almost instantly and have to be analyzed nearly as quickly, allowing—and requiring—the training of machine-learning models to sort through the flow. This shift in the production of information has implications for the future of everything from art creation to drug development.

But those advances are also making it possible to look differently at data from the past. Historians have started using machine learning—deep neural networks in particular—to examine historical documents, including astronomical tables like those produced in Venice and other early modern cities, smudged by centuries spent in mildewed archives or distorted by the slip of a printer’s hand.

Historians say the application of modern computer science to the distant past helps draw connections across a broader swath of the historical record than would otherwise be possible, correcting distortions that come from analyzing history one document at a time. But it introduces distortions of its own, including the risk that machine learning will slip bias or outright falsifications into the historical record. All this adds up to a question for historians and others who, it’s often argued, understand the present by examining history: With machines set to play a greater role in the future, how much should we cede to them of the past?

Parsing complexity

Big data has come to the humanities throughinitiatives to digitize increasing numbers of historical documents, like the Library of Congress’s collection of millions of newspaper pages and the Finnish Archives’ court records dating back to the 19th century. For researchers, this is at once a problem and an opportunity: there is much more information, and often there has been no existing way to sift through it.

That challenge has been met with the development of computational tools that help scholars parse complexity. In 2009, Johannes Preiser-Kapeller, a professor at the Austrian Academy of Sciences, was examining a registry of decisions from the 14th-century Byzantine Church. Realizing that making sense of hundreds of documents would require a systematic digital survey of bishops’ relationships, Preiser-Kapeller built a database of individuals and used network analysis software to reconstruct their connections.

This reconstruction revealed hidden patterns of influence, leading Preiser-Kapeller to argue that the bishops who spoke the most in meetings weren’t the most influential; he’s since applied the technique to other networks, including the 14th-century Byzantian elite, uncovering ways in which its social fabric was sustained through the hidden contributions of women. “We were able to identify, to a certain extent, what was going on outside the official narrative,” he says.

Preiser-Kapeller’s work is but one example of this trend in scholarship. But until recently, machine learning has often been unable to draw conclusions from ever larger collections of text—not least because certain aspects of historical documents (in Preiser-Kapeller’s case, poorly handwritten Greek) made them indecipherable to machines. Now advances in deep learning have begun to address these limitations, using networks that mimic the human brain to pick out patterns in large and complicated data sets.

Nearly 800 years ago, the 13th-century astronomer Johannes de Sacrobosco published the Tractatus de sphaera, an introductory treatise on the geocentric cosmos. That treatise became required reading for early modern university students. It was the most widely distributed textbook on geocentric cosmology, enduring even after the Copernican revolution upended the geocentric view of the cosmos in the 16th century.

The treatise is also the star player in a digitized collection of 359 astronomy textbooks published between 1472 and 1650—76,000 pages, including tens of thousands of scientific illustrations and astronomical tables. In that comprehensive data set, Matteo Valleriani, a professor with the Max Planck Institute for the History of Science, saw an opportunity to trace the evolution of European knowledge toward a shared scientific worldview. But he realized that discerning the pattern required more than human capabilities. So Valleriani and a team of researchers at the Berlin Institute for the

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By: Moira Donovan
Title: How AI is helping historians better understand our past
Sourced From: www.technologyreview.com/2023/04/11/1071104/ai-helping-historians-analyze-past/
Published Date: Tue, 11 Apr 2023 09:00:00 +0000