"It starts out like a conventional women's thriller," Cajsa explains. "She wakes up, feels strange, memories are there but confusing. It seems like the usual waking-up-after-accident-thriller where someone dies or loses memory. But no, son and husband are alive. She's dead. And a cobot (companion robot) is waking up with her consciousness."
As that suggests, the novel touches on themes and ideas many New World Notes readers may find appealing. More from Cajsa:
Nettrice Gaskins, an artist whose work explores "techno-vernacular creativity", created this beautiful tribute to the most famous character played by actor Rutger Hauer, who died yesterday: Roy Batty, the lead replicant in Blade Runner. As with her other illustrations, her medium for creating this image is Deep Dream, the neural network AI. She randomly played around with two-three algorithms to generate this image, she tells me, one of them likely being Leon Gatys’ Neural Style Transfer. So if you like, this is a portrait of an AI generated by an AI.
Watch this new tech demo from DeepMotion, the AI company which taught NPCs how to argue, and learn to dribble basketballs: An AI "stuntman" agent who can run through a physics-enabled breakable wall -- and adjusts his momentum based on the wall's thickness.
"[W]hat's changing each iteration is the strength of the wall," DeepMotion's Anna Ploegh tells me, "by way of adjusting the mass of each brick. So the running movement is responding each time to a difference in the wall obstacle. Over each iteration, that mass of the bricks increases until it is too difficult for the character to jump through."
This is why each crash in the demo is different, as is the way the AI agent falls. This is in contrast to technology often used in videogames to simulate a similar effect, where an NPC is suddenly turned into a physics-enabled ragdoll (i.e ragdoll physics). Here's why:
"I use images with abstract textures and them composite the results -- sometimes [with] Photoshop and sometimes Microsoft Word (true story)," Dr. Gaskins tells me. "My work in Deep Dream is similar to my collage work using traditional artist materials. The process I use to draw and paint is what I'm using in Deep Dream." More specifically:
With only a few learned skills, the character controllers used in this demo are relatively simple, as are the mechanics of the simulation. When the simulation is played, each character transitions between the three argumentative gestures at random, creating the appearance of a lively debate. When the characters experience external force from a user, the environment, or another character, they fall and then promptly get up. The primary goal is to continue arguing.
Fit a few hundred of these in an auditorium, and you could simulate a session of Congress! (With possibly less pratfalls.)
"The short term plan," Deep Motion's Chief Scientist Libin Liu tells me, "is to let the characters learn argument and idling actions from those unstructured motion sequences, so that they can perform them freely based on scripts, user commands, or mimic user actions based on sparse input (like 3 point tracking)."
Most game-focused AI is developed around core mechanics like pathfinding and combat, but Liu and his team believe subtle group interactions like this can do much to make a game world seem that much more real:
Here's a new high def version of the dazzling 3D video/AI-driven performance displayed on the Walt Disney Concert Hall last year. Refik Anadol created the projected visuals, and the music was co-created by adaptive music/sound artist Robert Thomas, who as longtime New World Notes readers know, once experimented with voice-activated installations and location-reactive soundtracks in Second Life. (Disclosure: Also a pal.) Here's how Robert and his collaborators created the music for this event -- and by "collaborators", I'm including the machine learning algorithms they created to assist them, which searched through the LA Phil's massive archive of performances, merging disparate fragments of music together in new and novel ways:
Mica was sitting at the table in the same room. She smiled at me and look at me. I was struck that she wasn’t just looking at me. She was looking in my eyes. She tilted her head from side to side... When I noticed how attentive she was, I moved my head forward and looked in her eyes. She did the same and looked at me. I moved my head back and she moved her head back too. She was mimicking some of the movements that she saw me make. She didn’t talk, but that is coming in the future.
I need to process some thoughts. The Mica AI left me in a deeply introspective mode. I didn’t want to think of it as “she” but I couldn’t control my reaction. They Ex Machina’d me a little bit. https://t.co/gHZyzIAXKi
Full keynote below, beginning with inspiring words from company CMO Brenda Freeman and acclaimed designer Robin Hunicke, an apparent (and admirable) attempt to make a clean break from the startup's history with internal sexism, followed by a fireside featuring Neal Stephenson and John Gaeta (the Matrix effects guy), with Andy Serkis and others soon after:
Video shot during last night's WDCH preview by Brooke Erdmann
If you're anywhere near downtown Los Angeles between tonight and October 6, you absolutely have to experience WDCH DREAMS. I was lucky enough to attend a preview with my wife last night (almost bumping into the Mayor, who was also there) and we were utterly dazzled by this flood of images and music echoing off Frank Gehry's famed concert hall:
The Los Angeles Philharmonic has commissioned award-winning media artist Refik Anadol to create unprecedented, breathtaking, three-dimensional projections onto the steel exterior of Walt Disney Concert Hall to signal the commencement of the LA Phil’s 100-year anniversary celebrations. Free and open to the public, nightly performances are scheduled to occur every half hour, with the first performance at 7:30 p.m., and the last at 11:30 p.m., September 28 to October 6... WDCH Dreams’ accompanying soundtrack was created from hand-picked audio from the LA Phil’s archival recordings. Sound designers Robert Thomas, and Kerim Karaoglu augmented these selections by using machine-learning algorithms to find similar performances recorded throughout the LA Phil’s history, creating a unique exploration of historic audio recordings.
Based in London, Robert tells me how he and his collaborators used machine learning to take and shape disparate performances and composers from the LA Phil's massive archive of recordings, and sculpt them into a completely new soundtrack:
What you're looking at above appears to be a pretty big breakthrough in artificial intelligence -- an avatar "learning" how to dribble in real time through AI. DeepDribble is a project from researchers at DeepMotion and Carnegie Mellon, and the idea is to demonstrate how an AI-controlled avatar can acquire the complex and subtle set of integrated physical skills and coordination that humans take for granted:
Basketball at its peak is known for intricate ball handling, quick pivoting, and fake outs. A good player will fluidly transition between have a variety of dribbling skills. In order to recreate this, the trained characters need to be able to transition between separately trained behaviors... Libin Liu and Jessica Hodgins use the same methods for training single skills to create a multi-skill control graph (which allows transition between motion fragments of two different skills). The training is done incrementally, behavior by behavior, to ensure integration occurs with proper transitions for each skill. The result is a player that can perform multiple ball handling skills in a variety of orders, changing course with seamless blending.
"First we build a bio-mechanical model of the digital character, using physics to simulate bones and virtual muscles," Deep Motion's Libin Liu tells me. "We put the digital character in the physically simulated virtual world and let it mimic how real players perform the motions using their muscle forces."
The training process, as you might have imagine, requires quite a lot of power -- but Liu says the learning arc took about as long as a single televised NBA game -- or even half of one:
