Release Date: 2020-01-13

About Lenovo Workstations - React Robotics ad

VIDEO Lenovo Workstations - React Robotics TV commercial 2020 • UK-based AI researchers, React Robotics, are helping construction professionals mitigate risks and delays with DogBot, a quadruped robotic “helper” that utilizes cutting-edge machine learning algorithms to complete a number of tasks in high-risk industrial environments. To harness the intense amount of computing power required to teach DogBot everything from walking to navigation and execution of tasks, React Robotics relies on Lenovo workstations for on-the-go power and performance.

00:00 right now there are many dull dirty and
00:01 dangerous jobs that people have to
00:03 perform what if in the future they could
00:05 be performed by robots we really think
00:07 it depends on a success of artificial
00:10 intelligence what we wanted to do was
00:11 find a way of bringing intelligence into
00:13 the real world so react robotics is
00:16 aiming to build robotics body for the
00:18 artificial revolution that we've all
00:19 seen coming da bot is about opening the
00:22 way to robots that really understand the
00:23 world to interact with it the robot has
00:25 12 axes so three axes on each leg it can
00:29 walk it in trots go out with sensors on
00:31 it and various types so it could be 3d
00:33 scanning the space but it could also
00:35 have thermal cameras and be detecting
00:38 gases with spectral cameras is
00:40 predominantly 3d printed we're using
00:42 Autodesk fusion 360 so we can very
00:45 quickly design something test it print a
00:47 new part overnight and retest that part
00:49 this allows us to manufacture and much
00:51 less components than if we use
00:52 conventional methods so we can
00:54 consolidate multiple functions into
00:56 single parts and therefore it's very
00:57 quick to build this robot Lenovo
00:59 ThinkPad p1 has been hugely helpful in
01:02 our politic development process the full
01:04 cad model of the of the robot is
01:05 actually quite being uncomplicated to
01:07 keep the tool fluid and responsive you
01:09 actually need quite a lot of compute
01:11 power and that's why having a powerful
01:12 workstation is essential for our
01:14 workflow it's very important that we
01:15 work with partners like Lenovo they
01:17 share our vision for really taking
01:19 technology out into the world we have a
01:21 very open ecosystem and we think that
01:23 the more people that have access to that
01:25 ecosystem the faster the capabilities of
01:27 the robot will develop in terms of
01:29 research the most fascinating problem is
01:33 how to create an algorithm that can
01:35 learn to learn in making a robot can
01:37 deal with the real world there's a huge
01:38 amount of data that you need to process
01:40 in fact one of the things we had to do
01:42 in the latest generation of robots is
01:44 update from canvas - EtherCAT so we have
01:47 a hundred megabit links to get the data
01:49 from the joints back into the computer
01:50 fast enough and with low enough of
01:52 latency so we use on bun 2 Linux because
01:54 we can use it from our embedded
01:56 environments on our robot through to our
01:58 workstations and our machine learning
02:00 platform building cart official
02:01 intelligence for robots is actually
02:03 extremely difficult not because of the
02:06 mathematics or the algorithms but
02:08 because of the high expectation level of
02:11 the general public to achieve
02:13 human-level intelligence and human level
02:16 of motor skills we need the best
02:18 possible hardware and the best possible
02:20 computing power it I think station we're
02:22 using NVIDIA Quadro r-tx GPUs with
02:25 tensor cores to accelerate our machine
02:26 learning because the faster your
02:28 graphics card the faster you can train
02:29 your algorithms are faster you can
02:30 iterate it's a really exciting time to
02:32 be in robotics and artificial
02:33 intelligence things are happening every
02:35 day which change what is possible and
02:36 with partners like the novo to help us
02:38 along the way who knows what we'll
02:39 achieve -


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