Later On

A blog written for those whose interests more or less match mine.

Archive for December 14th, 2020

Online high-resolution images of great art

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During the several days I was without a computer, I came across an article I definitely wanted to blog. It told of where you could download high-resolution images of great art, images that allowed you zoom in to see details — even individual brushstrokes. (Click image above to open it in a separate tab, then click to enlarge.)

And of course I can’t find it now, but I did turn up some equivalents:

Download All 36 of Jan Vermeer’s Beautifully Rare Paintings (Most in Brilliant High Resolution)

The British Museum Just Put 1.9 Million Images Online for Public Use” (article)
The British Museum Collection Online

Paris Museums Put 60,000+ Historic Photos Online, Copyright-Free

The Metropolitan Museum of Art Puts 400,000 High-Res Images Online & Makes Them Free to Use

Written by Leisureguy

14 December 2020 at 6:58 pm

The paper that forced Timnit Gebru out of Google

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Karen Hao writes in MIT Technology Review:

On the evening of Wednesday, December 2, Timnit Gebru, the co-lead of Google’s ethical AI team, announced via Twitter that the company had forced her out.

Gebru, a widely respected leader in AI ethics research, is known for coauthoring a groundbreaking paper that showed facial recognition to be less accurate at identifying women and people of color, which means its use can end up discriminating against them. She also cofounded the Black in AI affinity group, and champions diversity in the tech industry. The team she helped build at Google is one of the most diverse in AI and includes many leading experts in their own right. Peers in the field envied it for producing critical work that often challenged mainstream AI practices.

A series of tweets, leaked emails, and media articles showed that Gebru’s exit was the culmination of a conflict over another paper she coauthored. Jeff Dean, the head of Google AI, told colleagues in an internal email (which he has since put online) that the paper “didn’t meet our bar for publication” and that Gebru had said she would resign unless Google met a number of conditions, which it was unwilling to meet. Gebru tweeted that she had asked to negotiate “a last date” for her employment after she got back from vacation. She was cut off from her corporate email account before her return.

Online, many other leaders in the field of AI ethics are arguing that the company pushed her out because of the inconvenient truths that she was uncovering about a core line of its research—and perhaps its bottom line. More than 1,400 Google staff members and 1,900 other supporters have also signed a letter of protest.

Many details of the exact sequence of events that led up to Gebru’s departure are not yet clear; both she and Google have declined to comment beyond their posts on social media. But MIT Technology Review obtained a copy of the research paper from one of the coauthors, Emily M. Bender, a professor of computational linguistics at the University of Washington. Though Bender asked us not to publish the paper itself because the authors didn’t want such an early draft circulating online, it gives some insight into the questions Gebru and her colleagues were raising about AI that might be causing Google concern.

“On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” lays out the risks of large language models—AIs trained on staggering amounts of text data. These have grown increasingly popular—and increasingly large—in the last three years. They are now extraordinarily good, under the right conditions, at producing what looks like convincing, meaningful new text—and sometimes at estimating meaning from language. But, says the introduction to the paper, “we ask whether enough thought has been put into the potential risks associated with developing them and strategies to mitigate these risks.”

The paper

The paper, which builds on the work of other researchers, presents the history of natural-language processing, an overview of four main risks of large language models, and suggestions for further research. Since the conflict with Google seems to be over the risks, we’ve focused on summarizing those here.

Environmental and financial costs

Training large AI models consumes a lot of computer processing power, and hence a lot of electricity. Gebru and her coauthors refer to a 2019 paper from Emma Strubell and her collaborators on the carbon emissions and financial costs of large language models. It found that their energy consumption and carbon footprint have been exploding since 2017, as models have been fed more and more data. . .

Continue reading. There’s much more.

It is becoming increasingly clear why Google dropped “Do no evil” from their mission statement.

Written by Leisureguy

14 December 2020 at 5:44 pm

Jacques Pepin’s version of fast food

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YouTube has a nice series “Jacques Pepin: More Fast Food My Way,” which from the title I believe is a sequent, but the original is not on YouTube. I haven’t watched it all, but I will. Watch the first 50 seconds — not even a minute of your time — for an excellent idea: quick, easy, and tasty. (I, of course, will will omit the salt and will not use nearly so much olive oil as he splashes on). Take a look:

Written by Leisureguy

14 December 2020 at 12:52 pm

What a great slant! And a sunny day inspires honeysuckle.

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The fragrance of honeysuckle as autumn draws to an end is a pleasant olfactory anachronism. And the lather from Phoenix Artisan’s kokum butter shaving soap is extremely nice. The Simpson Emperor 2 is a very nice little brush — I decided that this week will be Simpson week so far as brushes are concerned — and its lather work was excellent.

I’m still greatly enjoying my iKon stainless slant now that I’ve learned to favor the cap in the stroke — and what good acoustics it has! The crisp static-like sound of stubble being cut is quite soothing.

A splash of the aftershave and a new week begins, quite auspiciously. Not only a great shave with a razor I increasingly love, but also (as you see) a brilliantly sunny morning, and my hard reset of my diet (plus exercise) is working amazingly well. My average fasting blood glucose is dropping quickly, as you see, and the interesting thing about this morning’s chart is that 5.5 mmol/L (93 mg/dL) is that it is in the “normal” range — the top of the normal range, to be sure (5.6 starts the “pre-diabetic” range), but a vast improvement over the 6.5 that was my previous 90-day average. 

And returning to my diet brings its own pleasures — for example, I’ve making enjoying an afternoon cranberry slushie.

Written by Leisureguy

14 December 2020 at 11:11 am

Posted in Fitness, Food, Health, Shaving

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