News on China's scientific and technological development.

latenlazy said:

The basic technology is probably more significant than the application in this case.

Click to expand...

Yes it is Here is the news pick up by NYT and why is this invention important

And Now, a Bicycle Built for None
It’s not the first self-driving bike. But equipped with an A.I. chip, it may be the nearest to thinking for itself.



Image
A frame taken from a video by researchers in China shows a self-driving bicycle, whose neuromorphic computer chip helps it understand certain commands.CreditCreditPei et al., Nature

By

• July 31, 2019

As corporate giants like Ford, G.M. and Waymo to get their self-driving cars on the road, a team of researchers in China is rethinking autonomous transportation using a souped-up bicycle.

This bike can roll over a bump on its own, staying perfectly upright. When the man walking just behind it says “left,” it turns left, angling back in the direction it came.

It also has eyes: It can follow someone jogging several yards ahead, turning each time the person turns. And if it encounters an obstacle, it can swerve to the side, keeping its balance and continuing its pursuit.

It is not the first-ever autonomous bicycle (Cornell University has ) or, probably, the future of transportation, although it could find a niche in a future world swarming with package-delivery vehicles, drones and robots. (There are out there.) Nonetheless, the Chinese researchers who built the bike believe it demonstrates the future of computer hardware. It navigates the world with help from what is called a neuromorphic chip, modeled after the human brain.

| Sign up for the]

In a paper published on Wednesday in , the researchers described how such a chip could help machines respond to voice commands, recognize the surrounding world, avoid obstacles and maintain balance. The researchers also provided a video showing these skills at work on a motorized bicycle.

or , but the training takes hours to days of trial and error. Even then, the skills are viable only in very particular situations. With help from neuromorphic chips and other new processors, machines could learn more complex tasks more efficiently, and be more adaptable in executing them.

“That is where we see the big promise,” said Mike Davies, who oversees Intel’s efforts to build neuromorphic chips.

Over the past decade, the development of artificial intelligence has accelerated thanks to what are called neural networks: complex mathematical systems that can learn tasks by analyzing vast amounts of data. By metabolizing thousands of cat photos, for instance, a neural network can learn to recognize a cat.

This is the technology that recognizes faces in the photos you post to Facebook, identifies the commands you bark into your smartphone and translates between languages on internet services like Microsoft Skype. It is also hastening the advance of autonomous robots, including self-driving cars. But it faces significant limitations.

A neural network doesn’t really learn on the fly. Engineers train a neural network for a particular task before sending it out into the real world, and it can’t learn without enormous numbers of examples. OpenAI, a San Francisco artificial intelligence lab, recently built a system that could . But the system first spent months playing the game against itself, burning through millions of dollars in computing power.

Researchers aim to build systems that can learn skills in a manner similar to the way people do. And that could require new kinds of computer hardware. and academic labs are now developing chips specifically for training and operating A.I. systems. The most ambitious projects are the neuromorphic processors, including the Tianjic chip under development at Tsinghua University in China.

Such chips are designed to imitate the network of neurons in the brain, not unlike a neural network but with even greater fidelity, at least in theory.

Neuromorphic chips typically include hundreds of thousands of faux neurons, and rather than just processing 1s and 0s, these neurons operate by trading tiny bursts of electrical signals, “firing” or “spiking” only when input signals reach critical thresholds, as biological neurons do.

. Maybe start with helping it learn to ride a bike.

Here is the principle behind this breakthrough via JSCH

Please, Log in or Register to view URLs content!

· 4 min read



Many AI experts believe humanlike artificial general intelligence (AGI) is but a far-fetched dream, while others find their inspiration in the quest for AGI. Speaking at last November’s AI Frontiers Conference, OpenAI Founder and Research Director Ilya Sutskever said “We (OpenAI) have reviewed progress in the field over the past few years. Our conclusion is near-term AGI should be taken as a serious possibility.”

Today, respected scientific journal Nature boosted the case for AGI with a cover story on a new research paper, Towards artificial general intelligence with hybrid Tianjic chip architecture, which aims to stimulate AGI development by adopting generalized hardware platforms.



Typically, researchers have taken one of two paths in pursuit of AGI — proceeding either via computer science or via neuroscience. Each approach however requires its own unique and incompatible platforms, and this has stalled overarching AGI research and development. With an eye on closing that gap, researchers from Tsinghua University, Beijing Lynxi Technology, Beijing Normal University, Singapore Polytechnic University and University of California Santa Barbara have introduced the Tianjic chip. The revolutionary chip can adopt various core architectures, reconfigurable building blocks and so on, to accommodate both computer-science-based machine-learning algorithms and neuroscience-oriented schemes such as brain-inspired circuits.



Tianjic design

A key innovation from the research team is Tianjic’s unified function core (FCore) which combines essential building blocks for both artificial neural networks and biologically networks — axon, synapse, dendrite and soma blocks. The 28-nm chip consists of 156 FCores, containing approximately 40,000 neurons and 10 million synapses in an area of 3.8×3.8 mm2.

(cont)
Tianjic delivers an internal memory bandwidth of more than 610 gigabytes (GB) per second, and a peak performance of 1.28 tera operations per second (TOPS) per watt for running artificial neural networks. In the biologically-inspired spiking neural network mode, Tianjic achieves a peak performance of about 650 giga synaptic operations per second (GSOPS) per watt. The research team also showcased the superior performance of Tianjic compared to GPU, where the new chip achieves 1.6–100 times better throughput and 12–10000 times better power efficiency.


Chip evaluation and modeling

The research team designed a self-driving bicycle experiment to evaluate the chip’s capability for integrating multimodal information and making prompt decisions. Equipped with the Tianjic chip and IMU sensor, a camera, steering motor, driving motor, speed motor and battery, the bicycle was tasked with performing functions such as real-time object detection, tracking, voice-command recognition, riding over a speed bump, obstacle avoidance, balance control and decision making.



The research team developed a variety of neural networks (CNN, CANN, SNN and MLP networks) to enable each task. The models were pretrained and programmed onto the Tianjic chip, which can process the models in parallel and enable seamless on-chip communication across different models.

In experiments, the Tianjic-powered bicycle smoothly performed all assigned tasks, signaling a huge leap towards the acceleration of AGI development.

The research team also noted that “high spatiotemporal complexity can be generated by randomly introducing new variables into the environment in real time, such as different road conditions, noises, weather factors, multiple languages, more people and so on. By exploring solutions that allow adaptation to these environmental changes, issues critical to AGI — such as generalization, robustness and autonomous learning — can be examined.”



The research team told Chinese media they expect the Tianjic chip to be deployed in autonomous vehicles and smart robots. They have already started research on the next-generation chips and expect to close the R&D stage early next year.

Further information can be found in the paper .

Journalist: Tony Peng & Fangyu Cai | Editor: Michael Sarazen

Hendrik_2000 said:

Here is the principle behind this breakthrough via JSCH

Please, Log in or Register to view URLs content!

Please, Log in or Register to view URLs content!

Please, Log in or Register to view URLs content!

· 4 min read

Click to expand...

but but... Chinese can only steal intellectual properties, not inventing them!!!

now noticed the tweet

·

China's first smartphones will start selling on August 5, announced ZTE, China's telecom giant. The ZTE Axon 10 Pro 5G pre-sale was launched on several Chinese e-commerce platforms for 4,999 yuan (about $727) on July 23.

Typically, researchers have taken one of two paths in pursuit of AGI — proceeding either via computer science or via neuroscience. Each approach however requires its own unique and incompatible platforms, and this has stalled overarching AGI research and development.

Click to expand...

It is a bit more of advertisement by using the word "neuroscience" in AI than pure technical meaning. A common trend these days. Similar to Samsung calling their "LED backlighted LCD panel" a LED screen.

I understand the very different nature of AI from traditional digital computing, BUT whatever fancy names (neuroscience) all AI today are STILL based on and running on CPUs no different from decades ago, binary based adding/subtracting. "Neuroscience" in AI introduce the idea of mimicking neuro-nerves network that is different from traditional sequential executing computer, but every neuro-node is still a typical CPU executing sequential instructions. It is very close to distributed computing without a central-coordinating node, which in my field is still a typical computer.

Chinese buses are magic in Santiago
Electric bus fleet helping to cut down on air pollution and noise and reduce future public expenses

Chinese-made electric buses are winning over commuters in Chile’s capital Santiago.

Incorporating the buses into Santiago’s transportation fleet “has been tremendously positive in many ways,” said Gloria Hutt, Chilean Minister of Transport and Communications, Xinhua reported.

“What mattered most to us was the evaluation of the passengers, which was excellent,” said Hutt, noting that commuters gave the Chinese buses an average 6.3 rating on a scale of 1-7, which surpassed Santiago’s subway.

Some 203 Chinese-made electric buses have joined the city’s transit fleet since December 2018, helping cut down air pollution and noise and reduce future public expenses, the report said.

The red-and-white fleet is 100% electric, air-conditioned, and equipped with Wi-Fi and USB ports.

Passengers “have really taken good care of them … they feel the journey is much better,” said Hutt, noting the lack of scratches and graffiti.

Incorporating Chinese-made electric buses into Santiago’s transportation fleet marked a “very radical” transformation in the quality of the capital’s mass transit system, she said.

The fleet’s operating costs are “significantly lower” than the ones powered by conventional fuel, which is expected to spur other bus operators to turn to electric vehicles. The batch also contributes to the government’s environmental goals, said the minister.

Each bus can cover 260 kilometres with a three-hour full charge, which is enough for a full day’s operation, the report said.

To accommodate the fleet’s charging capacity, the city is updating bus terminals with higher technological features such as better charging stations, according to Hutt.

Another 183 Chinese buses are due to begin operating in October, and the ministry is in talks to purchase 60 more.

Such measures are part of the city’s forward-looking Metropolitan Mobility Network, which comprises electronic buses, subways, suburban trains and a bike-sharing scheme.

The private sector in China and Chile is increasingly interested in electric mobility in Chile, which Hutt called a “gain” for the government. “More and more new brands are arriving, so we have a greater range of supply.”

Click to expand...

Jura said:

let's add


reported
signgraph

Click to expand...

... so did you just report Signgraph for a personal attack because he felt like you had broken rules?



Signgraph, if you feel like a post that someone has made is offensive feel free to file a report and the moderator team will be alerted to it.

Jura, someone else accusing your post of breaking the rules doesn't really constitute a personal attack either. And your post of taking a screenshot and writing "nineteen eighty four" is low effort and borders on being inflammatory for the topic of this thread.

The last few replies are going to be deleted.

vincent said:

but but... Chinese can only steal intellectual properties, not inventing them!!!

Click to expand...

yeapp, Chinese definitely has stolen this technology from the US which doesn't have one ... like 5G