Li Deyi: Let cloud computing, big data boost and achievements of artificial intelligence

Chinese Academy of Engineering, physicist. Chinese Artificial Intelligence Institute, Eurasian Academy of Sciences. He first proposed the "control flow - data flow" graph theory and a set of methods implemented in logical language; proposed cloud model, cloud transformation, cloud reasoning, cloud control and other methods for uncertainty and cloud computing, Control "three inverted swing balance" experiment and intelligent driving achieved remarkable results.

In the past ten years, Academician Li Deyi has been paying attention to China's cloud computing industry. For Li Deyi, from cloud computing to artificial intelligence, new forms of technology are bringing an unprecedented boom in applications, involving not only big data, robots (300024), but also smart driving.

At present, the scientist of the recent years is working with the domestic vehicle manufacturers to drive brain cooperation. Driving the Brain - A Cognitive and Control Unit that Manipulates Vehicles for Autonomous Driving instead of Mankind - In Li's opinion, the motivation, thinking, memory and so on of human beings in driving are realized by using the machine to drive the brain. In this process, memory cognition and interaction cognition are more important than computing cognition.

The following is a statement by Academician Li Deyi -

Last year, I and my colleagues and business partners did one thing, using pilotless technology, through precise navigation, the domestic bus from Zhengzhou to Kaifeng, the world's first bus to achieve the Zhengzhou on the road to run, and no one intervention.

The car, the machine that was once called the world changed, is being changed by software. But I do not advocate simply saying that the smart car is a four-wheel plus a cell phone, this sentence is a problem. The difficulty of developing a smart car is not just a sensor. More importantly, a machine driver's brain responds to uncertainty like a driver, making predictive control in a timely manner. Driving activities are predictive control over activities, more about skills and experience than knowledge, Reasoning and calculation, experienced drivers interact with the car perennial, skilled to the car into a part of the body, as the body seamless docking additional external force.

Predictive control is the charm of artificial driving.

For example, the car hurried to the airport on the road, the glare in front of the glare, we had to reduce the speed as soon as possible, and wheeled robot also need to emergencies in the event of an emergency response. For example, a sudden accident at any time, ambient noise or a car suddenly came across, especially the pet cut from the horizontal, which requires predictive control.

However, the basic problem of smart driving, many people have not figure out. Who taught who?

Smart car is not a program-defined machine, really teach the robot to drive should be an experienced driver. For example, Google invited a large number of drivers to drive, we have the same understanding on this issue. Throughout the year, my team hand over the program-equipped technology to third parties, automatically launching the technology program and letting the car open automatically.

In essence, the programmer drives the robot through a program, and the car becomes a software-defined machine that enables autonomous driving. The fundamental difference between autonomous driving is that the robot has no ability to learn online from human pilots. Who teaches who, in my opinion, is not a point programmer teaching a machine, but an experienced driver who teaches a robot.

Next, learn what? Learn to drive. A person's driving process is a person's predictive control in the brain's circuit. Predictive control is one of the strategies to be counter-controlled, and the driver always refreshes this question from the current forecast value after the forecast within the limited time limit or the time scrolls. The first element formed to return the vacancy rate as the car, so having a light sensor is not enough.

Next, how to learn? Wheeled robots are time-varying, non-linear, and sometimes time-lag, and are objective optimization under multiple constraints. Our strategy is to give a Trinity method of machine awareness, interaction awareness, driver perception. Learning driver's perception of the exercise. A good driver safety response is high; the second to be comfortable, can not let the person sit up and back; the third a low fuel consumption.

We want to expand the debug bus into a self-learning bus, create a self-learning board, complete deep learning and evolutionary learning, and let a robot drive like a human being and develop a personalized smart car. Absorb the experience driver's throttle, brake, and steering wheel controls into a cognitive arrow. The use of search engine through the situation map, to map search, real-time approximate memory pixels. The formation of cognitive fragmentation of big data cognition, subdivision Constraints taken by a large number of micro-cognitive formalization to reduce the difficulty of formalization and narrow the scope of online reasoning.

In addition, on intelligent driving technology-related policy and legal fit, now the state-level set up smart facilities demonstration area, the first one in Shanghai, and four, smart driving soon will enter the homes of ordinary people than you Imagine faster.

The concept of cloud computing has landed from the concept through technology, the current problem is how to improve the quality of service, the service should be more refined, more economical. So what is the role of cloud computing in the field of artificial intelligence?

Cloud Perception, Cloud Perception, Cloud Interaction, Cloud Learning, If Driving a Brain, With Cloud Computing Driving the Brain into Driving a Super Brain, With the Wisdom of the Whole, Formal Constraints and Then Making a Model Then Making Algorithms and Writing Program, program + data + document is software, the program revolves around the data, you can use the data definition program, data definition algorithm, data definition model.

Let the wheeled robot form a driving situation in the working memory, covering the specific actions of the steering wheel. Recognize the re-action of such a data recognition, so I think do not always talk about computing, memory is too important, memory does not mean that storage, memory and computing and storage are occurring at the same time.

The application of wheeled robot shows a problem - the core of artificial intelligence is not just the algorithm but also the learning - giving full play to cognitive and objective forms of big data fragmentation in big data environment, reducing the difficulty of formalization, Generate data-defining software that is valuable artificial intelligence around data rotation and data creation.

Many people worry that the robot will control the human society in the future, but many experts and scholars agree that "people are strong intelligence and the machinery is weak intelligence. In any case, when people dance with machines and people, people must be the leader So, there must be some awe of artificial intelligence, so that the machine can coexist harmoniously with human beings.

Humans want to control the robot, to teach the robot to replace the old robot with a new robot. People will be more important later, the degree of cleverness will be stronger and stronger. In fact, artificial intelligence is the formation of the two most powerful scientific fields of physics and life science. It is bound to bring about tremendous changes to human society.


Blind Flange /Tube Sheet

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Class Rating: 150~2500
Facing: RF(raised face);FF(flat face);RTJ(ring type joint);RJ(ring joint face)
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Manufacturing process: forge,

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Carbon steel:
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Stainless steel:
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304L/UNS S30403/1.4306;
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309S/UNS S30908/1.4833
309H/UNS S30909;
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310H/UNS S31009;
316/UNS S31600/1.4401;
316Ti/UNS S31635/1.4571;
316H/UNS S31609/1.4436;
316L/UNS S31603/1.4404;
316LN/UNS S31653;
317/UNS S31700;
317L/UNS S31703/1.4438;
321/UNS S32100/1.4541;
321H/UNS S32109;
347/UNS S34700/1.4550;
347H/UNS S34709/1.4912;
348/UNS S34800;


Alloy steel:
ASTM A694 F42/F46/F48/F50/F52/F56/F60/F65/F70;
ASTM A182 F5a/F5/F9/F11/F12/F22/F91;
ASTM A350 LF1/LF2/LF3;

Duplex steel:
ASTM A182 F51/S31803/1.4462;
ASTM A182 F53/S2507/S32750/1.4401;
ASTM A182 F55/S32760/1.4501/Zeron 100;
2205/F60/S32205;
ASTM A182 F44/S31254/254SMO/1.4547;
17-4PH/S17400/1.4542/SUS630/AISI630;
F904L/NO8904/1.4539;
725LN/310MoLN/S31050/1.4466
253MA/S30815/1.4835

Nickel alloy steel:
Alloy 200/Nickel 200/NO2200/2.4066/ASTM B366 WPN;
Alloy 201/Nickel 201/NO2201/2.4068/ASTM B366 WPNL;
Alloy 400/Monel 400/NO4400/NS111/2.4360/ASTM B366 WPNC;
Alloy K-500/Monel K-500/NO5500/2.475;
Alloy 600/Inconel 600/NO6600/NS333/2.4816;
Alloy 601/Inconel 601/NO6001/2.4851;
Alloy 625/Inconel 625/NO6625/NS336/2.4856;
Alloy 718/Inconel 718/NO7718/GH169/GH4169/2.4668;
Alloy 800/Incoloy 800/NO8800/1.4876;
Alloy 800H/Incoloy 800H/NO8810/1.4958;
Alloy 800HT/Incoloy 800HT/NO8811/1.4959;
Alloy 825/Incoloy 825/NO8825/2.4858/NS142;
Alloy 925/Incoloy 925/NO9925;
Hastelloy C/Alloy C/NO6003/2.4869/NS333;
Alloy C-276/Hastelloy C-276/N10276/2.4819;
Alloy C-4/Hastelloy C-4/NO6455/NS335/2.4610;
Alloy C-22/Hastelloy C-22/NO6022/2.4602;
Alloy C-2000/Hastelloy C-2000/NO6200/2.4675;
Alloy B/Hastelloy B/NS321/N10001;
Alloy B-2/Hastelloy B-2/N10665/NS322/2.4617;
Alloy B-3/Hastelloy B-3/N10675/2.4600;
Alloy X/Hastelloy X/NO6002/2.4665;
Alloy G-30/Hastelloy G-30/NO6030/2.4603;
Alloy X-750/Inconel X-750/NO7750/GH145/2.4669;
Alloy 20/Carpenter 20Cb3/NO8020/NS312/2.4660;
Alloy 31/NO8031/1.4562;
Alloy 901/NO9901/1.4898;
Incoloy 25-6Mo/NO8926/1.4529/Incoloy 926/Alloy 926;
Inconel 783/UNS R30783;
NAS 254NM/NO8367;
Monel 30C
Nimonic 80A/Nickel Alloy 80a/UNS N07080/NA20/2.4631/2.4952
Nimonic 263/NO7263
Nimonic 90/UNS NO7090;
Incoloy 907/GH907;
Nitronic 60/Alloy 218/UNS S21800


The blind flange is also called the blind plate, which is called the flange cover. It is a flange without holes in the middle to seal the pipe plug. There are many kinds of sealing surfaces, such as plane, convex, concave convex, tenon groove surface and ring connection surface.



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