These are the 8 top technology trends to watch in China

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  • This is a preview of 2019 Technology Trends Report in China from Business Insider Intelligence and EqualOcean.
  • EqualOcean is offering this report for the first time in English through a partnership with Business Insider Intelligence.

5G wireless will be the No. 1 technology to watch in the coming years — with international leaders like Huawei, Qualcomm, and Intel transforming not only industries but entire countries with its broad applications and economic significance.

EqualOcean Top Technologies in China 2019

But it’s not the only technology you should have on your radar.

In the 2019 Technology Trends Report in China, EqualOcean, a leading China-focused industrial tech media and investment innovation research firm, breaks down eight evolving technologies that deserve special attention. These technologies are either currently undergoing or about to undergo major phases of change.

This report represents a guidebook outlining which of China’s technology trends will be most significant in the next two to three years.

The technologies included in this report are:

  • 5G Communication
  • Quantum computing
  • Edge computing
  • Flexible display
  • Natural language processing
  • Immunotherapy
  • Blockchain
  • Immersive technology

Here are some of the key takeaways from the report:

Quantum computing, edge computing, and flexible display are all still in an early period, but will soon begin to attract commercial and enterprise adoption.

  • 5G Communication, natural language processing, and immunotherapy are enjoying a popular period where there will be a breakthrough in commercialization.
  • Now that the cryptocurrency bubble has burst and regulations have tightened, blockchain is entering a stable period where it will permeate enterprises.
  • Immersive technology will transition to a recovery period as giant companies drive growth in applying products to the entertainment and business services markets.

In full, the report:

  • Outlines the progress of new technology in China and how it’s applied, forecasting trends, potential risks, and careless investments for strategic decision-makers.
  • Examines how to effectively use limited financial and material resources in the future and prevent innovation from becoming destructive.
  • Serves as a reference for readers concerned about the merge of tech innovation and the industrial economy.

The companies included in this report are: IBM, AWS, Google, Intel, Alibaba, D-Wave, Regetti, 1QBit, Azure, Tencent, HPE, Cisco, Samsung, LG, BOE, Apple, Xiaomi, Visionx, Microsoft, Facebook, Baidu, ByteDance, iFlytek, NOKIA, ZTE, Ericsson, MSD, Novartis, BMS, Allogene Therapeutics, Junshi, BeiGene, I-Mab Biopharma, Hyperledger, Ant Financial, Mastercard, Ethereum, Ripple, SONY, HTC, Oculus, and Magic Leap.

>> Get the Report Now

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Motorcycle visionary Erik Buell’s new Fuell Fluid electric bicycle with 200 km range begins sales

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There’s no shortage of electric bicycles on the market. New models seem to pop up almost daily. But what we don’t see very often are electric bicycles designed by world-renowned motorcycle industry pioneers. The Fuell Fluid may be the first of its kind, and it goes on sale today. The bike features high-end components, dual batteries, and impressive range – you’ll want to check this one out.

Fuell’s new electric rides

Erik Buell is known in the industry as a pioneer of motorcycle racing technology. A former Harley-Davidson engineer, he founded Buell Motorcycles, which was eventually purchased by Harley-Davidson.

Buell’s latest endeavor has seen him team up with legendary engineer Frédéric Vasseur, the Alfa Romeo Formula 1 team principal and founder of Spark Racing Technology (which builds the Formula E racers), and successful international motorcycle entrepreneur Francois-Xavier Terny.

The team recently unveiled a pair of new electric two-wheelers: the Flow electric motorcycle and the Fluid electric bicycle.

Fuell Fluid electric bicycle

The Fuell Fluid e-bike went on pre-sale today using the Indiegogo platform. We’ve talked about how Indiegogo has been a popular option for launching new e-bikes while remaining a bit hit or miss. But in this case, Erik Buell’s name lends a truckload of credibility to the enterprise. Plus the campaign is already halfway funded in just the first few hours.

The Fuell Fluid offers a long list of high-end specs. It features the highly acclaimed Gates Carbon Drive, which uses a carbon belt instead of a chain drive. That reduces maintenance, increases efficiency, and results in a silent riding experience.

There’s also a custom mid-drive motor that is nominally rated at 100 Nm of torque and 500 W of power, as well as an EU version rated at just 250 W. I’m not saying this is necessarily the case here, but EU versions of international e-bikes often use the same motors and just label them as lower wattage. So you Europeans might be in for a surprise with how powerful the 250 W version is.

fuell fluid

The motor is plenty torquey, but an 8-speed rear internal hub will bump that torque up even more on the low-end. Plus it’s another maintenance-free part.

There are two versions available with different top speeds. The Fluid-1 can hit 25 km/h in Europe or a slightly faster 20 mph in the US. The Fluid-1S bumps up the speed to 45 km/h in Europe or 28 mph in the US. Stopping power comes from a pair of Tektro HD-E hydraulic brakes. Again, there’s an emphasis on low maintenance here.

Other nice features include integrated high power (900 lumen) lights, front suspension, Schwalbe Super Moto tires, 3.2″ color display, 5 speed profiles, PIN code unlocking and GPS/LoRa tracker built into the frame for anti-theft.

fuell fluid ebike

A maximum of 200 km (125 mi) of range is possible with the dual 48V battery version, which offers 1,008 Wh. For those needing less range, you can pick up a single battery version to save some cash.

The Fuell Fluid’s multiple versions have MSRPs ranging from around $3,300-$3,700, but they are available for a 30% discount during the pre-order period. The Fluid-1 with a single battery is $2,299, the Fluid-1 with two batteries is $2,599, and the Fluid-1s with two batteries is $2,645. They are also offering extra battery packs for $299, just in case 200 km (125 mi) of range isn’t quite enough for you.

Fuell Flow electric motorcycle

While the Fluid e-bike is stealing the show, Fuell’s electric motorcycle shouldn’t be overlooked either. The Fuell Flow is designed as an urban commuter and comes in an 11 kW or 35 kW option. The max speed is around 90 km/h (55 mph) or up to 140 km/h (85 mph) on demand. That means it could theoretically take you on the highway, but is mostly designed for urban applications.

The Flow has a city range of 240 km (150 mi) from its 10 kWh battery. That’s on par with many Zero motorcycles, which need even larger batteries to reach such range. With a 0-100 km/h (0-62 mph) time of just 2.7 seconds, this is one quick electric commuter. And it charges quickly as well, including Level 3 DC fast charging as standard.

It also has some nice tech built into the bike, include ABS brakes, rear view camera, blind spot detection, and an anti-collision system – though I’m not sure how that last one works.

The Flow is also available for pre-order but won’t be ready for production until the end of 2020. A $500 deposit will hold your place in line for the $10,995 electric motorcycle.

What do you think of Fuell’s new electric bike and motorcycle? Let us know in the comments below.


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Walmart unveils an A.I.-powered store of the future, now open to the public

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Walmart this morning unveiled a new “store of the future” and test grounds for emerging technologies, including A.I.-enabled cameras and interactive displays. The store, a working concept called the Intelligent Retail Lab — or “IRL” for short — operates out of a Walmart Neighborhood Market in Levittown, New York.

The store is open to customers and is one of Walmart’s busiest Neighborhood Market stores containing over 30,000 items, the retailer says, which allows it to test out technology in a real world environment.

Similar to Amazon Go’s convenience stores, the store has a suite of cameras mounted in the ceiling. But unlike Amazon Go, which is a grab-and-go store with smaller square footage, Walmart’s IRL spans 50,000 square feet of retail space and is staffed by over 100 employees.

Plus, in Walmart’s case, these A.I.-powered cameras are not being used to determine what items customers are buying in order to automatically charge them. It still has traditional checkout stations. Instead, the cameras will monitor inventory levels to determine, for example, if staff needs to bring out more meat from the backroom refrigerators to restock the shelves, or if some fresh items have been sitting too long on the shelf and need to be pulled.

The idea is that the A.I. will help the store associates know more precisely where and when to restock products. And this, in turn, means customers will know the produce and meat is always fresh and in stock when they arrive.

Using technology to do this is not simple, Walmart says. It means the automated system will need to be able to detect products on the shelf, recognize the exact product it sees (1 lb of ground beef vs. 2 lbs., e.g.), and then compare the quantities on the shelf to upcoming sales demand.

For store associates, the system allows them to stop constantly walking the store to replace inventory — instead, they’ll know what to bring out from the back room before the doors even open to customers that day.

The cameras and other sensors in the store pump out 1.6 TB of data per second, or the equivalent of three years’ worth of music, which necessitates a big data center on site. At the IRL store, it’s glass-encased, bathed in blue light, and on display to the public.

This could seem a little intimidating — A.I. cameras and giant servers. But Walmart says the data is only stored for less than a week.

There are also informational stations in the store where customers can learn more about the technology in use. A Welcome Center in the store is available too, for customers who want to learn more about the technical specifications and get answers to common questions.

An interactive wall lets customers have fun with A.I. — it demonstrates how an A.I. system can estimate body positioning. But really it’s meant to make all this new technology seem less intimidating.

“Technology enables us to understand so much more – in real time – about our business.” says Mike Hanrahan, CEO of IRL. “When you combine all the information we’re gathering in IRL with Walmart’s 50-plus years of expertise in running stores, you can create really powerful experiences that improve the lives of both our customers and associates.”

There’s an interest at Walmart for using A.I. for more practical purposes in retail  — and the CEO makes what is perhaps a veiled reference to Amazon Go, in a statement.

“You can’t be overly enamored with the shiny object element of AI,” Hanrahan said. “There are a lot of shiny objects out there that are doing things we think are unrealistic to scale and probably, long-term, not beneficial for the consumer.”

Instead of focusing on automated checkout solutions, the future concepts Walmart will test at IRL after meat inventory levels, are using the A.I. system to ensure that there are shopping carts available at all times and that registers are open and staffed.

The company insists that the tech isn’t replacing jobs, but instead frees up staff to interact with customers. That’s the same claim it made as it rolled out more robots to its stores. But it’s hard to see how, over time, more efficiently run stores would require as many associates as they do now.

IRL is a concept designed by Walmart’s tech incubator Store N8, which runs several ventures to test new ideas in retail. Earlier this year, it launched a startup which offers VR tours to enhance the shopping experience, and in 2017 it began testing a personal shopping service called Code Eight in NYC.

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Scientists pull speech directly from the brain

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In a feat that could eventually unlock the possibility of speech for people with severe medical conditions, scientists have successfully recreated the speech of healthy subjects by tapping directly into their brains. The technology is a long, long way from practical application but the science is real and the promise is there.

Edward Chang, neurosurgeon at UC San Francisco and co-author of the paper published today in Nature, explained the impact of the team’s work in a press release: “For the first time, this study demonstrates that we can generate entire spoken sentences based on an individual’s brain activity. This is an exhilarating proof of principle that with technology that is already within reach, we should be able to build a device that is clinically viable in patients with speech loss.”

To be perfectly clear, this isn’t some magic machine that you sit in and its translates your thoughts into speech. It’s a complex and invasive process that decodes not exactly what the subject is thinking but what they were actually speaking.

Led by speech scientist Gopala Anumanchipalli, the experiment involved subjects who had already had large electrode arrays implanted in their brains for a different medical procedure. The researchers had these lucky people read out several hundred sentences aloud while closely recording the signals detected by the electrodes.

The electrode array in question

See, it happens that the researchers know a certain pattern of brain activity that comes after you think of and arrange words (in cortical areas like Wernicke’s and Broca’s) and before the final signals are sent from the motor cortex to your tongue and mouth muscles. There’s a sort of intermediate signal between those that Anumanchipalli and his co-author, grad student Josh Chartier, previously characterized, and which they thought may work for the purposes of reconstructing speech.

Analyzing the audio directly let the team determine which muscles and movements would be involved when (this is pretty established science), and from this they built a sort of virtual model of the person’s vocal system.

They then mapped the brain activity detected during the session to that virtual model using a machine learning system, essentially allowing a recording of a brain to control a recording of a mouth. It’s important to understand that this isn’t turning abstract thoughts into words — it’s understanding the brain’s concrete instructions to the muscles of the face, and determining from those which words those movements would be forming. It’s brain reading, but it isn’t mind reading.

The resulting synthetic speech, while not exactly crystal clear, is certainly intelligible. And set up correctly, it could be capable of outputting 150 words per minute from a person who may otherwise be incapable of speech.

“We still have a ways to go to perfectly mimic spoken language,” said Chartier. “Still, the levels of accuracy we produced here would be an amazing improvement in real-time communication compared to what’s currently available.”

For comparison, a person so afflicted, for instance with a degenerative muscular disease, often has to speak by spelling out words one letter at a time with their gaze. Picture 5-10 words per minute, with other methods for more disabled individuals going even slower. It’s a miracle in a way that they can communicate at all, but this time-consuming and less than natural method is a far cry from the speed and expressiveness of real speech.

If a person was able to use this method, they would be far closer to ordinary speech, though perhaps at the cost of perfect accuracy. But it’s not a magic bullet.

The problem with this method is that it requires a great deal of carefully collected data from what amounts to a healthy speech system, from brain to tip of the tongue. For many people it’s no longer possible to collect this data, and for others the invasive method of collection will make it impossible for a doctor to recommend. And conditions that have prevented a person from ever talking prevent this method from working as well.

The good news is that it’s a start, and there are plenty of conditions it would work for, theoretically. And collecting that critical brain and speech recording data could be done preemptively in cases where a stroke or degeneration is considered a risk.

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