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Category: robotics/AI – Page 2,469

Elon Musk could soon share more on his plan to help humans keep up with AI

Neural lace. A brain implant. Such a thing must be separate enough that if the lace is hacked nothing happens to your brain. Otherwise no deal.

In nearly the same breath as he shared updates on his plans to dig tunnels, Elon Musk also noted he’s looking to hopefully share more on his progress with developing a “neural lace” next month. That’s a technical term for direct cortical interface, and it’s something that the SpaceX and Tesla CEO takes very seriously, in case you thought he might just be having a laugh.

Musk discussed the potential of a functional neural lace at Recode’s Code conference last year, speaking earnestly about its benefits in terms of being able to help humans keep pace with advancements in AI that threaten to render us vastly inferior to complex virtual intelligences.

@BelovedRevol Maybe next month.

A Quick Rundown of the Alcubierre “Warp Drive”

In Brief Science fiction often serves as a curiosity catalyst for a lot of technological innovation. One such example is this Alcubierre Warp Drive, that would absolutely revolutionize the capability of humans to traverse the stars.

It’s always a welcome thing to learn that ideas that are commonplace in science fiction have a basis in science fact. Cryogenic freezers, laser guns, robots, silicate implants… and let’s not forget the warp drive! Believe it or not, this concept – alternately known as FTL (Faster-Than-Light) travel, Hyperspace, Lightspeed, etc. – actually has one foot in the world of real science.

In physics, it is what is known as the Alcubierre Warp Drive. On paper, it is a highly speculative, but possibly valid, solution of the Einstein field equations, specifically how space, time and energy interact. In this particular mathematical model of spacetime, there are features that are apparently reminiscent of the fictional “warp drive” or “hyperspace” from notable science fiction franchises, hence the association.

Chan Zuckerberg Initiative’s AI Acquisition Will Make Science Free for All

Back in September, the Chan Zuckerberg Initiative – the philanthropic company set up by Facebook CEO Mark Zuckerberg and his wife, Dr. Priscilla Chan – set a goal to invest $3 billion to cure, prevent, and manage disease by the end of the century.

The company has taken a huge first step toward the objective by partnering with scientists, doctors, engineers, and other key stakeholders. With the acquisition of Toronto-based company, Meta, the team is moving even closer to their goal by creating tools and technology designed to empower the scientific community.

Meta is a research paper search engine that uses artificial intelligence (AI) to deliver the most relevant results to researchers. Following this acquisition, the Chan Zuckerberg initiative will enhance the service before eventually rolling it out for free.

IBM Just Posted 5 Predictions About What Life Will Be Like in 2022

Technology giant IBM is known for of making bold predictions about the future, and it’s just announced its latest “5 in 5” list, highlighting the five innovations that they think will have the biggest impact on our lives over the next five years.

According to the company, in only a few years, we’re set to see huge developments in artificial intelligence (AI), ultra-powerful telescopes, smart sensors, and medical devices — with benefits ranging from healthcare and the environment, to our understanding of Earth and the Universe itself.

Of course, all these predictions are based on technology and research developments that are happening right now — there’s no way of knowing what else might crop up in the next five years.

Singularity CGI

Carrie Fisher just died but she will likely come back to life because the Singularity is Near and is bringing Singularity CGI with it!

Bringing the dead back to life

In the latest Star Wars movie, Rogue One, five characters were brought back as they would have looked between episodes 3 and 4 of Star Wars. They were Princess Leia, Grand Moff Tarkin, Dr. Cornelius Evazan (who said “I have the death sentence on twelve systems” in episode 4), General Dodonna, and Mon Mothma. General Dodonna and Mon Mothma were brought back with the traditional method of using actors who looked similar to the original actors. The other three were brought back with CGI (computer-generated imagery), more specifically CGI enhanced with motion capture.

Princess Leia (Carrie Fisher) created by computer in Rogue One (credit: Lucasfilm)

Grand Moff Tarkin created by computer in Rogue One (credit: Lucasfilm)
(He looks better because he had more screen time so they spent more money on him.)

Motion capture has been used for a while including depicting Gollum in Lord of the Rings and all the apes in the latest Planet of the Apes movies but Grand Moff Tarkin was considered possibly too hard to do with today’s technology because people are better at seeing flaws in CGI humans than CGI apes and CGI twisted hobbits.

Here is how Grand Moff Tarkin was created:

English actor Guy Henry (Harry Potter) wore motion capture materials on his head so that his face could eventually be replaced with a digital likeness of Cushing’s (the original actor for Moff Tarkin). He was picked because he had a similar build and stature as Cushing and was able to speak in a similar manner.

Guy Henry looked a little different before the CGI was placed on top of him.
(credit: Industrial Light & Magic/Lucasfilm)

John Knoll, the chief creative officer at Industrial Light & Magic, wasn’t sure they were going to be able to pull this off. He said, “We did talk about Tarkin participating in conversations via hologram, or transferring that dialogue to other characters.” Tarkin ended up looking pretty good (actually fooling some critics!) although Dr. Evazan looked even better for his scene mostly because his distorted face doesn’t look completely human.

It takes a lot of work to make CGI look realistic!
(credit: Industrial Light & Magic/Lucasfilm)

Nvidia

Was this CGI good enough to envision Princess Leia having a significant role using this technology? Probably not. But something amazing happened in 2016. Nvidia completed an over $2 billion project to develop a new class of graphics/AI chips. An example of how good they were is that the new version of the Nvidia Titan X can do AI (artificial intelligence) 566% faster than the previous Titan X that was only released a year before. This $1,200 card is so popular that half a year after its release Nvidia is still rationing this card to two per customer. (Disney gets to use Nvidia cards that are even more powerful than the Titan X!)

Why does Nvidia matter to Star Wars fans? Because Nvidia’s chips power the CGI in virtually all movies. Nvidia is now making 100% of the profits of all companies selling graphics cards, with their chips being put into everything from Nintendo’s newest console to every Tesla car currently being built. This has caused Nvidia to soar in value, with their stock over tripling in 2016. This means that Nvidia is going to be able to spend a lot more than $2 billion on their next generation of graphics/AI chips! (Nvidia has found a way to use about the same architecture for AI chips and regular graphics chips.)

Not only is Nvidia’s new graphics/AI chip design affecting movies but they are helping make Ray Kurzweil’s prediction of human equivalent AI by 2029 a reality. Nvidia’s CEO Jen-Hsun Huang said, “AI is going to increase in capability faster than Moore’s Law. I believe it’s a kind of a hyper Moore’s Law phenomenon because it has the benefit of continuous learning. It has the benefit of large-scale networked continuous learning. Today, we roll out a new software package, fix bugs, update it once a year. That rhythm is going to change. Software will learn from experience much more quickly. Once one smart piece of software on one device learns something, then you can over-the-air (OTA) it across the board. All of a sudden, everything gets smarter.”

Singularity CGI

Nvidia’s improved chips are part of a three layer accelerating returns juggernaut that is affecting CGI and which we will call Singularity CGI.

Layer one of Singularity CGI is better hardware with Nvidia having just switched from 28 nanometer transistors to 16/14 nanometer transistors. (They are getting 16 nanometer technology from TSMC and 14 nanometer from Samsung.) A 14 nanometer part is only 140 atoms wide! Both Samsung and TSMC will be producing 10 nanometer parts in 2017, with large Nvidia parts likely in 2018. (The 10 nanometer parts in 2017 will be for companies like Apple who don’t need large, complex chips as Nvidia does.)

Layer two of Singularity CGI is better Nvidia designs which is what Nvidia just spent over two billion dollars on. Layer three of Singularity CGI is better software. An example of this exponentially improved software is that Disney Research and Carnegie Mellon University scientists have found that three computer vision methods commonly used to reconstruct 3D scenes produce superior results in capturing facial details when they are performed simultaneously, rather than independently.

“The quality of a 3D model can make or break the perceived realism of an animation,” said Paulo Gotardo, an associate research scientist at Disney Research. “That’s particularly true for faces; people have a remarkably low threshold for inaccuracies in the appearance of facial features. PGSF (photogeometric scene flow) could prove extremely valuable because it can capture dynamically moving objects in high detail and accuracy.”

Conclusion

The growing power of Singularity CGI means that when Disney is ready to release episode 9 in 2019, Disney will be able to use much more powerful Nvidia cards and more sophisticated software to bring Carrie Fisher back to life to finish her story whose first two parts were in The Force Awakens (episode 7) in 2015 and episode 8 in 2017. (Carrie already filmed her scenes for episode 8.)

To increase the chance of success of creating a realistic Carrie Fisher, Disney will even be given $50 million thanks to insurance through Lloyd’s of London to fund this effort. May the force be with us!

Technology for making Death Star Sized Structures will have technical feasibility in the next 20 years

I never heard of this sort of making bubbles. And the details given are slim. Anyone here of this?

The first Death Star had a diameter of between 140 and 160 kilometers. The second Death Star’s diameter ranged from 160 to 900 kilometers.

There are two near term technologies which could be applied to making Death Star sized structures:

1. Space bubbles
2. Robotic spiderfab construction

Giant Space Bubbles

Google’s AI is Learning to Make Other AI

In Brief:

  • Even though AI systems creating AI systems seems like the recipe for a Sci-Fi nightmare, experts agree that it could create a future with a less expensive and more efficient workforce
  • The benefits of an AI-powered future might be outweighed by the jobs that the technology makes obsolete

Imagine the conflicted feelings of the machine learning expert who is creating artificial intelligence (AI) that they know will one day, possibly very soon, be able to create better AI than them. It’s the new age’s way of holding on to the time-honored tradition of having to train your own replacement. Machine learning experts are currently being paid a premium wage due to their limited numbers and the high demand for their valuable skills. However, with the dawn of software that is “learning to learn,” those days may be numbered.

Artificial Intelligence is Leading a Revolution in Medicine

In Brief The success of this work will help healthcare professionals diagnose more accurately and efficiently, and it will allow for more diagnostic care in areas with limited healthcare services and providers.

In early August, IBM announced that it will acquire Merge Healthcare Inc., a company that sells systems that help medical professionals access and store medical images. This move is a critical step in IBM’s plan to put AI to work medically by training its Watson software to identify maladies like heart disease and cancer.

Merge is valuable to IBM because it owns 30 billion images, including computerized tomography, X-rays, and magnetic-resonance-imaging scans. The company can use these images in its deep learning training program. IBM is hoping that the same kind of software that lets Flickr recognize your face or a dog in your photos can help Watson identify symptoms of diseases.