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Category: robotics/AI – Page 1,095

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Massachusetts-headquartered Dynatrace, which provides an intelligence layer to monitor and optimize application development, performance and security, today announced key updates for its core platform, including a new AutomationEngine that enables teams to streamline monitoring and other activity across a variety of workflows.

Developers, security specialists, operations personnel and even business users can tap into the platform. The company made the announcement at its annual cloud observability conference in Las Vegas.

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Google has trained an artificial intelligence, named SingSong, that can generate a musical backing track to accompany people’s recorded singing.

To develop it, Jesse Engel and his colleagues at Google Research used an algorithm to separate the instrumental and vocal parts from 46,000 hours of music and then fine-tuned an existing AI model – also created by Google Research, but for generating speech and piano music – on those pairs of recordings.

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Business Insider reported based on a leaked company-wide email that Google is asking all of its employees to take two to four hours of their day to test Google’s “Bard” AI, the same system the company plans to integrate into its chat function. It’s unclear if all Googlers over the world have received the same ask. The company recently announced 12,000 job cuts to its global workforce, but Google, without its parent company Alphabet, still employs over 170,000 around the world.

In that memo, Google CEO Sundar Pichai said he would “appreciate” if all staff “contributed in a deeper way” and take two to four hours to pressure test Bard. Anybody who’s ever read a “suggestion” email from their boss knows that it’s more of a mandate than anything else. It’s unclear based on the email text if the two-to-four hour suggestion would be asked of them every day or spread over a longer period of time.

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https://youtube.com/watch?v=qusXSHkcQZg&feature=share

(Filmed as: Blade Runner) by Philip K. Dick full audiobook. With cast and corresponding animated imagery.

Bounty hunter Rick Deckard wakes up to a world devastated by nuclear war, where humans care for animals to prevent the mass extinction of several species, where androids are colonial slaves who kill their masters and flee to hide on Earth.
Deckard’s boss Harry Bryant tells him that Dave Holden, another bounty hunter, was hurt while hunting fugitive androids, and now Deckard has to finish the job.
The catch? The androids are Nexus-6 models, the most intelligent, advanced androids ever created.

We appreciate the support. Thank you for listening! As always, we truly hope you enjoy!
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Thanks again to all those who’ve listened and joined our channel!

All male parts (except Roy Batty) voiced by Matthew Silas Sedgwick.
All female parts voiced by Makyla Meyer.
Roy Batty voiced by Chris Carter.

Prologue — 00:00:00
Chapter 1 — 00:00:40
Chapter 2 — 00:19:19
Chapter 3 — 00:38:44
Chapter 4 — 00:51:12
Chapter 5 — 01:10:13
Chapter 6 — 01:30:45
Chapter 7 — 01:42:17
Chapter 8 — 02:05:21
Chapter 9 — 02:23:44
Chapter 10 — 02:45:38
Chapter 11 — 02:58:12
Chapter 12 — 03:10:20
Chapter 13 — 03:33:27
Chapter 14 — 03:47:35
Chapter 15 — 04:06:07
Chapter 16 — 04:34:16
Chapter 17 — 04:53:27
Chapter 18 — 05:04:06
Chapter 19 — 05:25:33
Chapter 20 — 05:39:39
Chapter 21 — 05:43:52
Chapter 22 — 05:56:07

#philipkdick #bladerunner #audiobook

Continue reading “Do Androids Dream of Electric Sheep” | >

For centuries, the town of Carrara’s prosperity has depended on artists. Its famed Tuscan marble quarries supplied artists like Michelangelo, Canova and Bernini with the finest material for their sculptures. Today, robots are being used to create modern-day works. Chris Livesay has more.

#news #marble #technology.

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Continue reading “Robots used to carve out marble sculptures” | >

Over 50 percent of high-mass stars reside in multiple star systems. But due to their complex orbital interactions, physicists have a difficult time understanding just how stable and long-lived these systems are. Recently a team of astronomers applied machine learning techniques to simulations of multiple star systems and found a new way that stars in such systems can arrange themselves.

Classical mechanics has a notorious problem known as the three-body problem. While Newton’s laws of gravity can easily handle calculations of the forces between two objects and their subsequent evolution, there is no known analytic solution when you include a third massive object. In response to that problem, physicists over the centuries have developed various approximation schemes to study these kinds of systems, concluding that the vast majority of possible three-object arrangements are unstable.

But it turns out that there are a lot of multiple-star systems out there in the galaxy. Indeed, over half of all massive stars belong to at least a binary pair, and many of them belong to triple or quadruple star systems. Obviously, the systems last a long time. Otherwise, they would have flung themselves apart a long time ago before we had a chance to observe them. But because of the limitations of our tools, we have difficulty assessing how these systems organize themselves and what stable orbit options exist.

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