Lifeboat Foundation

New technique could be used to design a wide range of optical devices.

The founder of robot maker Boston Dynamics, Marc Raibert, is moving from CEO to chairman as the company prepares for a “new stage of growth.” The firm, well-known for its robotic creations, has been researching and developing its technology for decades, and it started leasing its first commercial robot, Spot, in 2019.

Evolutionary cyberneticist and digital philosopher Alex M. Vikoulov, author of The Syntellect Hypothesis, is interviewed by Agah Bahari, host and producer of NeoHuman podcast.

On this recent podcast, Alex Vikoulov, author of The Syntellect Hypothesis, is interviewed by NeoHuman podcaster Agah Bahari. Topics include evolutionary cybernetics, computational physics, consciousness, the simulation theory, the transcension hypothesis, the Global mind, AGI, VR, AR, psychedelics, technological singularities, transhumanism, Fermi Paradox, Digital Physics, objective reality, philosophy of mind, the extended mind hypothesis, absolute idealism, physics of time, the Omega Point cosmology, mind-uploading, synthetic telepathy, and more.

Watch a short intro here ↴.

Machines, especially through the power of AI, will surpass humans in Intelligence, effectiveness, and functionality.

Though there are some areas where humans will hold the dominance; mostly areas that require feeling and emotion.

But overall, machines will have capabilities that far surpass even the most Intelligent of humans.

TDS interviews AI visionary on her cutting-edge research at Google Brain, how Deep Reinforcement Learning works, and more.

CS230 | Deep Learning

https://www.newworldai.com/cs230-deep-learning-stanford-engineering/

Continue reading “CS230 Deep Learning Lectures | Stanford Engineering” »

Circa 2017

Chess isn’t an easy game, by human standards. But for an artificial intelligence powered by a formidable, almost alien mindset, the trivial diversion can be mastered in a few spare hours.

In a new paper, Google researchers detail how their latest AI evolution, AlphaZero, developed “superhuman performance” in chess, taking just four hours to learn the rules before obliterating the world champion chess program, Stockfish.

Continue reading “In Just 4 Hours, Google’s AI Mastered All The Chess Knowledge in History” »

Circa 2017

Thousands of years of human knowledge has been learned and surpassed by the world’s smartest computer in just 40 days, a breakthrough hailed as one of the greatest advances ever in artificial intelligence.

Google DeepMind amazed the world last year when its AI programme AlphaGo beat world champion Lee Sedol at Go, an ancient and complex game of strategy and intuition which many believed could never be cracked by a machine.

Continue reading “AlphaGo Zero: Google DeepMind supercomputer learns 3,000 years of human knowledge in 40 days” »

As others have pointed out, voxel-based games have been around for a long time; a recent example is the whimsical “3D Dot Game Hero” for PS3, in which they use the low-res nature of the voxel world as a fun design element.

Voxel-based approaches have huge advantages (“infinite” detail, background details that are deformable at the pixel level, simpler simulation of particle-based phenomena like flowing water, etc.) but they’ll only win once computing power reaches an important crossover point. That point is where rendering an organic world a voxel at a time looks better than rendering zillions of polygons to approximate an organic world. Furthermore, much of the effort that’s gone into visually simulating real-world phenomena (read the last 30 years of Siggraph conference proceedings) will mostly have to be reapplied to voxel rendering. Simply put: lighting, caustics, organic elements like human faces and hair, etc. will have to be “figured out all over again” for the new era of voxel engines. It will therefore likely take a while for voxel approaches to produce results that look as good, even once the crossover point of level of detail is reached.

I don’t mean to take anything away from the hard and impressive coding work this team has done, but if they had more academic background, they’d know that much of what they’ve “pioneered” has been studied in tremendous detail for two decades. Hanan Samet’s treatise on the subject tells you absolutely everything you need to know, and more: (http://www.amazon.com/Foundations-Multidimensional-Structure…sr=8-1) and even goes into detail about the application of these spatial data structures to other areas like machine learning. Ultimately, Samet’s book is all about the “curse of dimensionality” and how (and how much) data structures can help address it.