:00:00. > :00:08.This week we are back in China on the hunt for innovation.
:00:09. > :00:15.With gassy fabrics, liquid metal, and a good, solid meal...
:00:16. > :01:01.It probably won't surprise you if I tell you China makes a lot
:01:02. > :01:05.of stuff, but would you believe it makes quite this much?
:01:06. > :01:11.In 2011, the country produced 90% of all computers, 80%
:01:12. > :01:12.of all air conditioners and energy-saving lightbulbs,
:01:13. > :01:16.70% of all cellphones, that's just over a billion of them,
:01:17. > :01:23.and they also found time to make 63% of the world's shoes.
:01:24. > :01:26.And much of all of that would have come from this place.
:01:27. > :01:34.Welcome to the city of Shenzhen, in the Guangdong Province.
:01:35. > :01:38.So much of the world's electronics come from Shenzhen.
:01:39. > :01:41.So much of your electronics started life here.
:01:42. > :01:45.Cases, components, chips, circuit boards.
:01:46. > :01:54.Nestled away on the southern coast, it's called the Workbench of China,
:01:55. > :02:02.Less than 40 years ago, only 30,000 people lived here.
:02:03. > :02:13.And that explosive growth is built on foundations of silicon.
:02:14. > :02:16.This week, I'm on a mission to find out how our things
:02:17. > :02:23.And as the saying goes, when it comes to electronics,
:02:24. > :02:34.This is the HAX, Hardware Accelerator, in downtown Shenzhen.
:02:35. > :02:37.Each year, teams of hopeful entrepreneurs make a pilgrimage
:02:38. > :02:40.to this place to plan, prototype and perfect
:02:41. > :02:47.But before I show you around, time for a spot of lunch.
:02:48. > :02:52.We call it micro foods, so it's insects as the new protein.
:02:53. > :02:55.It is something that's been eaten for a very long time in all parts
:02:56. > :03:06.The hive is the smallest possible footprint of producing protein
:03:07. > :03:14.So better than plants, better than owning a cow?
:03:15. > :03:17.Better than plants, definitely better than owning a cow.
:03:18. > :03:23.You don't have to add additional water, they take it out
:03:24. > :03:47.They can actually be mixed into any types of recipes.
:03:48. > :03:54.In this way, we just roasted them, so they are just roasted and crispy.
:03:55. > :03:57.But you can also make them into a meat patty and make
:03:58. > :04:15.It's a shrimp that came on land a really long time ago.
:04:16. > :04:26.Living Farms is only one of the companies currently
:04:27. > :04:30.in residency, and there is no shortage of interesting ideas.
:04:31. > :04:34.There's the roadie auto guitar tuner, the skiing boots that
:04:35. > :04:37.track your skiing style, the orthopaedic foot insert that
:04:38. > :04:39.analyses how you walk, there's the internet
:04:40. > :04:42.of things farm monitor, and the remote control
:04:43. > :04:51.This device takes liquid materials, special formulations,
:04:52. > :04:56.and it converts them into nanofibres using an electric field.
:04:57. > :04:59.What happens is this little spinning needle produces a fabric
:05:00. > :05:05.Primarily, this machine is aimed at researchers right now.
:05:06. > :05:07.We are looking to get into the market and help people
:05:08. > :05:11.bring advanced textiles to a commercially viable
:05:12. > :05:14.point by offering a fast, affordable lab machine.
:05:15. > :05:17.Shenzhen has a wealth of manufacturers and vendors,
:05:18. > :05:21.so for prospective in the bay area, there might be two CNC
:05:22. > :05:26.There's hundreds, maybe thousands in Shenzhen, and they're quick,
:05:27. > :05:29.cheap, they respond to text messages, and it allows us to do
:05:30. > :05:33.work in a short amount of time for cheap.
:05:34. > :05:36.It's high quality work as well, so good for manufacturing
:05:37. > :05:42.HAX has been here since 2011, and over 100 companies
:05:43. > :05:49.It's a little empty today because there is another HAX
:05:50. > :05:52.office over in the US, and at the moment, everyone
:05:53. > :05:55.is over there showing off their creations,
:05:56. > :06:00.It's very bizarre that you're in San Francisco
:06:01. > :06:08.Why do you have a space here and a space in San Francisco?
:06:09. > :06:15.Yes, the early stage action is there, definitely,
:06:16. > :06:18.and all of the entrepreneurs in the world who go to Shenzhen
:06:19. > :06:22.and work with suppliers to build the best products to get to market,
:06:23. > :06:28.but after investing and accelerating about 145 companies in the last few
:06:29. > :06:36.years, I realised it was important to sell those products,
:06:37. > :06:42.and it is equally difficult to sell a product as to build it.
:06:43. > :06:46.So we have been building the next phase of the programme
:06:47. > :06:53.The big appeal of HAX is that it is within a short walk
:06:54. > :06:57.of some of the best and biggest electronic markets in the world.
:06:58. > :07:00.That means instant access to the cornucopia of components
:07:01. > :07:03.you will need to source if you want your thing
:07:04. > :07:08.There, I said the word "thing" again.
:07:09. > :07:15.The markets of Shenzhen are so vast that it would be foolhardy
:07:16. > :07:24.So we are at Singapore Airport and heading to Hong Kong.
:07:25. > :07:34.Andrew Huang, or Bunny for short, is an MIT alumnus, entrepreneur
:07:35. > :07:39.That's hacker in the breaking and building stuff sense
:07:40. > :07:44.He's a few written books, including Hacking The XBox,
:07:45. > :07:50.and most recently, The Essential Guide
:07:51. > :07:57.Our core product are the peel and stick electronic LEDs.
:07:58. > :08:11.Today, Bunny is making the pilgrimage to Shenzhen,
:08:12. > :08:16.I'm tagging along to find out what it is all about.
:08:17. > :08:19.This is where I come to do a lot of searching
:08:20. > :08:26.to see what is available, what is selling and not selling.
:08:27. > :08:29.There are these cables here, and these cables there.
:08:30. > :08:33.That's the whole idea of this market.
:08:34. > :08:39.Discounts are easily 10-1 over what you can get in online retail
:08:40. > :08:49.They are made here and then resold there.
:08:50. > :08:52.And, I'm afraid to say, it's not long before I succumb
:08:53. > :09:10.So far, we've only walked a couple of levels.
:09:11. > :09:13.So if you can't find it on this floor, don't worry,
:09:14. > :09:20.This guy's selling a variety of switches.
:09:21. > :09:31.These are the battery holders inside toys.
:09:32. > :09:33.Connectors you'd find inside mobile phones.
:09:34. > :09:40.I could come here and ask her today, I want a wire that's a little bit
:09:41. > :09:44.longer, and she'll go ahead and make up 1,000 for me and have them ready
:09:45. > :09:52.A lot of times when I come to Shenzhen, I don't even
:09:53. > :09:56.I buy everything I need as it's such a hassle to get
:09:57. > :10:00.Then I just leave them in the hotel when I leave.
:10:01. > :10:02.It's cheaper than paying for checked luggage.
:10:03. > :10:06.They sell soldering irons, diagonal cutters, development kits
:10:07. > :10:12.Within ten metres of here, you can probably get everything
:10:13. > :10:21.you need to take some simple project and bring it into existence.
:10:22. > :10:28.I've spent a decade here looking around.
:10:29. > :10:34.By the time you walk from one end of the market to the other,
:10:35. > :10:40.the beginning of the market has already reinvented itself.
:10:41. > :10:45.Do you shake on it or have some kind of...?
:10:46. > :10:49.It's a crazy thing where sometimes you say you need 10,000 of these
:10:50. > :10:53.parts, and it's not a small amount of money.
:10:54. > :10:56.A lot of times a person will come along and say, come
:10:57. > :11:01.I could stiff them and not come with the money, and
:11:02. > :11:05.And a lot of time they don't ask for a deposit.
:11:06. > :11:07.Just come back and they will have them for you.
:11:08. > :11:09.Rather you than me, if you do this regularly.
:11:10. > :12:07.China is not all cables and chips, you know.
:12:08. > :12:25.Then you rule books kicking in August. -- the new rules. Microsoft
:12:26. > :12:35.researchers have dealt a high-tech mosquito track to battle outbreaks
:12:36. > :12:44.like this eco- outbreak. -- Zico. They can detect the species and only
:12:45. > :12:51.capture ones that spread diseases. Another algorithm, developed by MIT,
:12:52. > :12:57.they have been using their deep learning systems to predict the
:12:58. > :13:08.future or how humans will respond to events. It can predict whether to
:13:09. > :13:16.individuals will handshake or high five. China is not all cables and
:13:17. > :13:32.chips. It is starting to become known for its fully fledged devices.
:13:33. > :13:38.It sees itself as a global player. The company has 170,000 employers.
:13:39. > :13:46.60,000 work here. It's here that new devices
:13:47. > :13:48.are developed and tested. Welcome to my own private
:13:49. > :13:51.anechoic chamber. This particular box here
:13:52. > :13:57.is where they put their network And after all that stress,
:13:58. > :14:09.it's time for lunch, again. Yeah, it's becoming a bit
:14:10. > :14:12.of a theme really, isn't it? But on a campus this big,
:14:13. > :14:15.the midday meal itself can be Right, so it's 11:38am,
:14:16. > :14:21.and I'm reliably informed in the next few minutes this place
:14:22. > :14:31.is going to fill up like crazy. And now it's 12:00pm,
:14:32. > :14:39.and everybody has eaten. If it looks like everyone's
:14:40. > :14:41.in a rush, well, they are. The quicker they eat,
:14:42. > :14:44.the longer they have I kid you not, having a roll-up bed
:14:45. > :14:50.under your desk is Despite the huge numbers,
:14:51. > :14:55.Huawei's path to world domination It's still trying to lift a ban
:14:56. > :15:00.on providing network equipment to the US,
:15:01. > :15:04.after it and fellow Chinese manufacturer ZTE were accused
:15:05. > :15:06.of building back doors into their networking equipment,
:15:07. > :15:08.which could allow the Chinese It's something Huawei's founder
:15:09. > :15:18.denied in a BBC interview last year. There's no way we can possibly
:15:19. > :15:20.penetrate into other people's systems, and we have never
:15:21. > :15:23.received such a request But the company carries
:15:24. > :15:31.on undeterred, and is still focused Its latest tablet,
:15:32. > :15:35.the MateBook, is set to launch Now, if Shenzhen is the R
:15:36. > :15:46.department, then the neighbouring city of Dongguan, about an hour's
:15:47. > :15:49.drive away, is the factory floor. Time to hook up with Bunny again,
:15:50. > :16:03.as he visits a factory to see if it's suitable
:16:04. > :16:13.to make his new product. All the bits and bobs that you see
:16:14. > :16:17.inside a phone or electronic gadgets They can make different
:16:18. > :16:25.products just by If I go ahead and squeegee that
:16:26. > :16:34.solder right onto the board... And everything gets
:16:35. > :16:36.stuck to that, does it? This machine is called
:16:37. > :16:39.a chip shooter. So it's a robot that's able to shoot
:16:40. > :16:42.chips onto this board. Listen to that, it sounds
:16:43. > :16:45.like a machine gun as well. Once the machines have
:16:46. > :16:46.placed the components, everything goes into a big oven,
:16:47. > :16:49.which melts the solder and sticks It's like one of those
:16:50. > :16:55.hotel toasters, isn't it? Where the bread goes
:16:56. > :17:01.in and very slowly comes round. In fact, if you look at some
:17:02. > :17:04.of the hobbyist DIY crowd, they will actually essentially
:17:05. > :17:06.replicate this at home It's still quite warm,
:17:07. > :17:09.so be careful with it. Machines like these allow even
:17:10. > :17:12.a relatively small factory But humans are still needed
:17:13. > :17:15.in this room, mainly And across the way,
:17:16. > :17:18.there's even more of them. This is your typical assembly-line,
:17:19. > :17:27.your material comes in the front. She's responsible for putting
:17:28. > :17:29.on glue, she's responsible for putting on connectors,
:17:30. > :17:32.she's responsible for putting on diodes, resistors,
:17:33. > :17:37.so on and so forth, It turns out that, for example,
:17:38. > :17:43.it's really hard to build robots that can reach into a box full
:17:44. > :17:46.of components like this, figure out there's a little line
:17:47. > :17:48.here, there's a diode, you have to figure out
:17:49. > :17:51.which way to put it, and then drop it in the board right
:17:52. > :17:56.in the hole. So, even here, the human's
:17:57. > :17:58.days are numbered. Wages are rising in Dongguan
:17:59. > :18:06.as businesses compete Because of that, factories
:18:07. > :18:09.are looking to automate even larger Case in point, Foxconn,
:18:10. > :18:15.manufacturer of the iPhone amongst other gadgets,
:18:16. > :18:17.recently revealed that it had more than halved its workforce in one
:18:18. > :18:19.factory, replacing 60,000 workers There is one task up here though
:18:20. > :18:32.that I think everyone is glad You see that pool of
:18:33. > :18:35.liquid metal? That is the T-1000
:18:36. > :18:38.in there, right now. Well, until the rise
:18:39. > :18:47.of the machines, the humans Oh come on, it does that?
:18:48. > :18:54.Yeah, yeah, yeah. It's got rainbow keys?
:18:55. > :18:56.It feels good. Never mind all this speech
:18:57. > :19:04.recognition, I want to type stuff. I tell you what, blink and you miss
:19:05. > :19:13.a mass movement of people here. They've all gone home.
:19:14. > :19:15.It's 5:30pm. So those keyboards could be
:19:16. > :19:18.in the boxes, into the storage room and then onto the shelf
:19:19. > :19:20.within about a week, But what about a mobile phone
:19:21. > :19:27.in your hands four minutes Let's put four minutes on the clock,
:19:28. > :19:39.because that's what China's biggest They've let us inside their largest
:19:40. > :19:44.robot-run warehouse to show us just how they can deliver,
:19:45. > :19:54.often in hours, sometimes in just JD.com shift 3 million orders
:19:55. > :19:58.a year from the latest Well, you might need those
:19:59. > :20:07.in under four minutes. 20,000 packages an hour
:20:08. > :20:11.are sorted here, not by hand, Robots pack, pick, unpack
:20:12. > :20:16.and shelve, computers track, As you can see, things move pretty
:20:17. > :20:31.quickly around here. Each parcel goes along that
:20:32. > :20:33.conveyor belt, and then It's scanned by that bar coder,
:20:34. > :20:38.which tells the machine which one of these shoots to send
:20:39. > :20:51.that parcel to. That will then be taken to one
:20:52. > :20:54.of over 100 different district Which means that actually now
:20:55. > :21:06.in this warehouse where they used to have 500 people doing this job,
:21:07. > :21:10.just with this row of shoots along This is one of the first places
:21:11. > :21:14.in China where machines could replace workers entirely
:21:15. > :21:16.over the next few years. These are their plans for a fully
:21:17. > :21:18.automated warehouse, And self-driving
:21:19. > :21:21.vehicles we know about. So drones will reach the parts that
:21:22. > :21:26.others struggle to get to. This isn't just talk,
:21:27. > :21:31.last month JD revealed their own prototypes for carrying anything up
:21:32. > :21:35.to the size of a home computer There basically would be 200,000
:21:36. > :21:40.spots on the map where we can They will be responsible
:21:41. > :21:53.for distributing to the villagers. But even if drones were allowed
:21:54. > :21:56.to fly anywhere, and they won't be, it would be still tricky
:21:57. > :21:58.to deliver something That's JD's record,
:21:59. > :22:05.so how did they manage it? Well, this is one of more than 100
:22:06. > :22:07.much smaller delivery What they've found is if you can get
:22:08. > :22:16.one of these packages to one of these local delivery places
:22:17. > :22:18.before it's even been ordered, then you don't have to wait
:22:19. > :22:24.for the package to come You've seen the big data,
:22:25. > :22:32.we analyse the purchase pattern, we predict which small community
:22:33. > :22:37.is going to have And then we deliver before
:22:38. > :22:43.the ordering happens. It's like Minority
:22:44. > :22:44.Report with shopping. We tailed the electric scooter
:22:45. > :22:47.to see if the kettle I'd randomly chosen could be delivered in less
:22:48. > :22:50.time than it would take to boil. Now you see we've caught a red light
:22:51. > :22:54.there, and that's going to cost Underneath that helmet he's
:22:55. > :22:58.going to be absolutely fuming. He's just gone down the bike lane
:22:59. > :23:01.and I think we've lost him. In fairness, this purchase
:23:02. > :23:12.hadn't been predicted, so it had to come all the way
:23:13. > :23:15.from the massive Asia 1 warehouse. Still, a robot and China's
:23:16. > :23:18.very own Stig delivered He's found the place,
:23:19. > :23:23.and he's off the bike. So how much over the
:23:24. > :23:29.four-minute record was he? We finally made it, that one took
:23:30. > :23:32.about two hours and ten minutes. It would be on the sixth
:23:33. > :23:47.floor, wouldn't it? Dan Simmons in the
:23:48. > :23:49.suburbs of Shanghai. And that's it for us
:23:50. > :23:51.in China for this week, In the meantime, you can see
:23:52. > :23:56.loads of backstage photos