Atlas, The Next Generation

Boston Dynamics · 40.8M views · 2016 · 2:42

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Why Hacker News recommends it

Used as a benchmark of robotics progress and a go-to example of impressive bipedal walking in AI and automation debates.

Recommended by 0 people across 0 different months, 2016 to 2026.

What it is

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.

What people said

Cites vardump · 2016-02 · Hacker News · on “Alphabet Unleashes New Humanoid Robot”

Let me guess, the new robot is called Cylon and is created by Greystone Industries? [LINK] More seriously, a pretty amazing product. It doesn't seem to be far from being actually useful for limited manual labor. Video embedded in the article: [this video]

Cites ccozan · 2016-02 · Hacker News · on “The dominance of baby boomers is becoming total”

Have you seen the latest robot from Boston Dynamics? Here is Atlas: [this video] I don't think we need 30y for a real robot application for old people. This could be in less than 10 years.

Cites Flenser · 2016-05 · Hacker News · on “Atlas – a platform for charts and data”

Other things called Atlas: HashiCorp's Enterprise Suite - [LINK] Stripe's startup tools - [LINK] Netflix's Telemetry Platform - [LINK] O’Reilly's learning environment - [LINK] Boston Dynamics's Robot - [LINK] [this video] Did I miss any?

Cites ilaksh · 2016-09 · Hacker News · on “WaveNet: A Generative Model for Raw Audio”

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.

Cites patcon · 2016-10 · Hacker News · on “Uber Self-Driving Truck Packed with Budweiser Makes First Delivery in Colorado”

Man, if we think this self-driving car thing is jarring, I wonder how we'll adjust to the incoming teachable general purpose biped robots... [this video] Basically, however fast we think self-driving cars are happening and requiring adjustment, that shift is like we're still on training wheels, compared to the real game-changer. We'd better figure out how to take care of those truckers and taxi-drivers, or it doesn't bode well for our adaptability as a society.

Cites Animats · 2016-12 · Hacker News · on “I was a robot and this is what I learned”

The Beam is a wimpy teleoperator. Send the new Atlas, from Boston Dynamics [1], to a conference, and you won't have that problem. People running away in terror might be more of an issue. (It's not clear what will become of Boston Dynamics. Google wants to sell them. DARPA and the Marines gave up on their BigDog as not militarily useful. The technology is impressive, but it cost well over $100 million (mostly DoD funding) and 25 years to get to this point, with no market in sight.) [1] [this video]

Cites PeterisP · 2017-04 · Hacker News · on “How brains are built: Principles of computational neuroscience”

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

Cites sixhobbits · 2018-05 · Hacker News · on “Today’s dominant approach to A.I. has not worked out”

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

Cites bachbach · 2018-08 · Hacker News · on “Artificial Intelligence Still Isn’t All That Smart”

> 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

Cites PeterisP · 2020-06 · Hacker News · on “How much did AlphaGo Zero cost? (2018)”

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 s