Boston Dynamics
14 HN mentions · mentioned in 13 months, 2016–2026
2:42 · 41M views · Feb 23, 2016
Boston Dynamics unveils a new, smaller Atlas humanoid robot that is electrically powered and hydraulically actuated. It balances with body sensors and uses lidar and stereo vision to navigate and manipulate objects.
Used as a benchmark of robotics progress and a go-to example of impressive bipedal walking in AI and automation debates.
14 comments from Hacker News
> And where are the people proposing rocket designs, in modern AI research? We like people like Geoffrey Hinton as their work produces results - he is the first to admit you can't get there from here. I think it's the people who are concerned with fundamentals, like the people at the Sante Fe Institute - complex adaptive systems. In the beginning we believed in programming AI from the axioms of mathematics - not many people believe that now. A bit like configuring an animal from atoms. Difficult, pointless. The first story is that 'fundamentals' might mean some evolutionary framework being required to plug in results from other areas like computer vision and machine learning, my guess would be something from genetic algorithms. The other story is there exists a 'God Algorithm' that all sapient beings possess - but I find that difficult to believe. Another story is that we simply have to start from the start - literally everything we know is nearly worthless because consciousness is too unlikely with computer hardware - that the entire history of computing is a dead end. Great for human technology but just not the route to a synthetic version of biological beings. I suspect we're more biased against this possibility than we should be. I hope that it is the first story - my rationale is that biological intelligence and consciousness is not as far away as we think it is. If we look to evolution we see these vast periods of time in which nature works on different paths and it's o
Someone sent me this article on IM. My (unedited) response: nothing worse than someone who both doesn't understand wtf he's talking about and is very critical either are ok on their own >> He‘s wrong then? well if either author can provide an article from 10-20 years ago, saying "in 10-20 years, we'll invent a single machine that can reach almost human-level translation proficiency, drive a car in complex environments, beat the best human player at logical games including chess and Go, beat the best human player at language/knowledge based games like Jeopardy, hold a lengthy conversation and answer questions, be able to accurately describe and caption images and video, and outperform humans at trading the stock market and detecting fraud but I won't be impressed because all of those things are simple" then it might have some weight "The dream of artificial intelligence was supposed to be grander than this — to help revolutionize medicine, say, or to produce trustworthy robot helpers for the home." robots: we already have the vacuum cleaners. Actual flexible domestic work is coming soon, the moment the military gets bored and releases some knowledge and/or people have finished making money from helping amazon pack boxes and starts making money from normal people instead: this video medicine: same machines already being used to detect cancer and heart conditions more accurately than humans, as well as folding proteins to create new medicines. Not sure what more he wants.. "If mach
Bipedal walking and running on uneven terrain has been demonstrated years ago - Boston Dynamics has a lot of nice videos; e.g. here's a four year old video on walking this video , here's two year old videos on running [LINK] and [LINK] - perhaps it's debatable if it's "full human level" but it seems sufficient to me for most purposes. IMHO any improvements to that would be mostly for sensors (seeing what terrain is there even in poor conditions e.g. fog/rain/snow) and modelling environment (understanding which objects might break or slide if you step on them), not walking/running as such. The main problem for bipedal robots that makes them still impractical is the hardware expense (wheels are simpler and cheaper) and the power supply required, so for most use cases it's more efficient to use something other than a bipedal robot and there's limited business application and future revenue in scaling up research demos of bipedal walking to practicality, so most people who are working on walking algorithms are doing so in simulated virtual environments (where we have algorithms that can learn walking and running "from scratch" through experimentation) and not building very expensive hardware.
Your examples have a point in them - To really understand how insects fly, it is helpful to build and analyze various machines that can flap its wings - since aerodynamics is complex and the equations we use to model airplanes don't really work on that scale. To understand how exactly humans walk, it really helps to build a machine that can lift its two feet in alternating motion and analyze how all the minor forces interact to make it work. It's immensely useful when we're building e.g. powered ankle prosthetics, and bipedal movement has some advantages in terrain, so we also want machines to be able to do that (e.g. this video ) For understanding human eyes - experimenting with lense systems that change focus was how we got to "augmented vision" e.g. humans with spectacles. The same goes for analyzing and understanding how human brains work. It's also valuable to think about minds in general, but for many purposes we care about a particular mind, and all the individuals I currently care about are homo sapiens, not machines; so we need to understand their brains.
Depending on how you mean 'reasoning, walking robots' then not yet really.. but every few weeks or months another amazing deep learning/NN whatever thing comes out in different domains. So these types of techniques seem to have very broad application. Of course, if you mean 'walking' in a literal sense, there are a number of impressive walking robots such as Atlas this video , HRP-2 [LINK] or HRP 4C [LINK] , etc.. Also there are many types of useful reasoning systems. I am guessing you are thinking of language understanding and generation.. but I believe these types of techniques are being applied quite impressively in that area also, from DeepMind or Watson [LINK] etc.