Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: robotics/AI – Page 2391

Interesting position that IBM is taking with Quantum Computing. The one challenge that was highlighted in this article around unstable particles actually has been in the process of being resolved by Charles Marcus and colleagues at the University of Copenhagen’s Niels Bohr Institute; Univ. of Copenhagan’s report came out a few weeks ago and it may be a good thing for IBM to connect with the University so they can see how this was resolved.

Also, I don’t believe that we have 3 uniquely different platforms of Quantum as this article highlights. Trying to state that a D-Wave Quantum Computer is not a full Quantum platform or less of a Quantum Platform to is not a fair statement; and I encourage others to pull back from that perspective at this point until Quantum Computing is more evolved and standards around the platform is well defined and approved by industry. Also, the Gartner graph in this article is not one that I embraced given the work on Quantum is showing us the we’re less than 10 yrs away for it in the mainstream instead of Gartners graph showing us Quantum will require more than 10 years to hit the mainstream. And, I saw some of missed marks on Bio-sensors and BMI technology taking more than 10 years on the Gartner graph which is also incorrect since we hearing this week announcements of the new bio-chips which enables bio-sensors and BMIs are making some major steps forward with various devices and implants.

The 3 Types Of Quantum Computers And Their Applications by Jeff Desjardins, Visual Capitalist

It’s an exciting time in computing.

Continue reading “Quantum Computers And Their Applications [INFOGRAPHIC]” | >

Or not.

It was hailed as the most significant test of machine intelligence since Deep Blue defeated Garry Kasparov in chess nearly 20 years ago. Google’s AlphaGo has won two of the first three games against grandmaster Lee Sedol in a Go tournament, showing the dramatic extent to which AI has improved over the years. That fateful day when machines finally become smarter than humans has never appeared closer—yet we seem no closer in grasping the implications of this epochal event.

Indeed, we’re clinging to some serious—and even dangerous—misconceptions about artificial intelligence. Late last year, SpaceX co-founder Elon Musk warned that AI could take over the world, sparking a flurry of commentary both in condemnation and support. For such a monumental future event, there’s a startling amount of disagreement about whether or not it’ll even happen, or what form it will take. This is particularly troubling when we consider the tremendous benefits to be had from AI, and the possible risks. Unlike any other human invention, AI has the potential to reshape humanity, but it could also destroy us.

It’s hard to know what to believe. But thanks to the pioneering work of computational scientists, neuroscientists, and AI theorists, a clearer picture is starting to emerge. Here are the most common misconceptions and myths about AI.

Read more

Stanford’s μTug minibots are on a roll lately.

The latest battery of experiments at Stanford’s Biomimetics and Dextrous Manipulation Lab dealt with harnessing the power of ants in robot form— specifically, researchers hoped to replicate ants’ ability to work together to haul very heavy objects. In the experiments, robots that jump or walk with a quick, jerky force were quickly determined to be inefficient in groups, while the μTugs won out due to the longer duration of pulling force they were able to create with their tiny winches. If you’ve ever played tug of war than this strategy already makes intrinsic sense. Not only could the μTug smimc ants through teamwork, but they anchored themselves to the ground with an adhesive borrowed from gecko toes.

To prove just how powerful the robots are, scientists took a group of six μTugs—which can pull up to 52 pounds each —and had them move a full-sized car with a passenger inside. Did we mention the passenger was the author of the research paper? When those things start self-replicating, he’s going to be the first one they come after.

Read more

A master player of the game Go has won his first match against a Google computer program, after losing three in a row in a best-of-five competition.

Lee Se-dol, one of the world’s top players, said his win against AlphaGo was “invaluable”.

The Chinese board game is considered to be a much more complex challenge for a computer than chess, and AlphaGo’s wins were seen as a landmark moment for artificial intelligence.

Read more

“Deep learning enables the robot to perceive its immediate environment, including the location and movement of its limbs. Reinforcement learning means improving at a task by trial and error. A robot with these two skills could refine its performance based on real-time feedback.”

ARTIFICIAL INTELLIGENCE: Google and Facebook Team Up to Open Source the Gear Behind Their Empires.

Read more

This is all the best games from every year 1952–2015.
Here is the list:

1952: Nimrod Computer Game
1958: Tennis For Two
1971: Computer Space
1972: Pong
1973: Space Race
1974: Clean Sweep
1975: Anti-Ai
1976: Blockade
1977: Indy 500
1978: Sea Wolf 2
1979: Crash
1980: Pac-Man
1981: Ms. Pacman
1982: Paratrooper
1983: Super Gridder
1983: Hunchback
1984: Sokoban
1985: Super Mario Bros
1986: Outrun
1987: Leisure Suit Larry in the Land of the Lounge Lizards.
1988: Super Mario Bros 3
1989: Xenon 2
1990: Prince Of Persia
1991: Prehistorik
1992: Wolfenstein 3D
1993: Day of the Tentacle
1994: The Lion King
1995: Command & Conquer
1996: Tomb Raider
1997: Gta
1998: Half Life
1999: Quake 3
2000: Max Payne
2001: Gta 3
2002: Serious Sam: The First Encounter
2003: Medal Of Honor Allied Assault
2004: Half Life 2
2005: World Of Warcraft
2006: Need For Speed Most Wanted
2007: Crysis
2008: Assassin’s Creed
2009: Call Of Duty Modern Warfare 2
2010: Red Dead Redemption
2011: World Of Tanks
2012: Battlefield 3
2013: Gta 5
2014: Wolfenstein The New Order
2015: Tom Clancy’s The Division

Read more