#研究分享#【技术界的“万有理论”】

#研究分享#【技术界的“万有理论”】除了物理界,技术界也有万有理论(Theory of EverythingTOE)。它主张将硬件和软件的关键性趋势联系在一起,形成一个完整的循环,用于解释技术产业的进化及其与社会的关系:各种设备的传感器产生海量数据,以供机器学习,机器学习促进了AIAI使机器人更智能、行动力更强,而机器人行动又触发了传感器。http://www.looooker.com/archives/10264

 

 

The theory of everything (ToE) in physics is a hypothetical framework that connects the very small of quantum mechanics with the very large of gravity to explain the four fundamental forces of the universe.

 

The Technology Theory of Everything:

My “theory of everything” in technology connects critical trends in both hardware and software to explain the evolution of the technology industry and its relationship with society.

 

A lot of people have talked about the trends of “connected devices” and “the Internet of Things” and “big data” and “robotics”. I would propose that all of these trends are interlinked as one megatrend, the “theory of everything”, that is also a positive reinforcing loop that feeds on each prior link in the chain.

 

Sensors from connected devices creates massive amounts of data which feeds machine learning, resulting in more intelligent AI which directs robots to perform more precise actions which triggers sensors and the loop is complete. Here are the six steps:

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1. Sensors generate Data

In 2014, the number of devices connected to the Internet exceeded the number of people in the world. Cisco predicts that by 2020, there will be 50 billion connected devices. Many of these devices will have sensors built-in, perhaps using Electric Imp, or added on externally through an Estimote beacon.

 

Sensors from devices creates a massive amount of data on an unprecedented scale.

 

2. Data feeds Machine Learning

In 2020, an estimated 35 zetabytes of data will be created, which is 44x greater than the amount of data created in 2009. This massive data, both structured and more likely unstructured, can be processed via machines to gain enormous insights. Enter machine learning.

 

3. Machine Learning improves AI

Machine learning relies on processing data and finding patterns to allow computers to learn without being explicitly programmed. While machine learning has been used since the 1950s, it is experiencing explosive growth today.

 

Both the amount of data and the computation power available today is driving the breakthroughs in machine learning.

 

As an example of machine learning’s sheer powers, Google mapped the exact location of every business, every household, and every street number in the entirety of France using it. Instead of sending a huge team to canvass the country for months, Google had a researcher circle the street numbers on a few hundred street view images. The rest of the work was assigned to a machine-learning algorithm to figure out what’s unique about the circled items, find them in the other 100 million street-view images and then read the numbers it finds. The entire project took 1 hour.

 

4. Artificial Intelligence directs Robots

As computers are already better than humans at chess, Jeopardy!, and street signs, there’s reason to expect more in the future. As more sensors picks up more data which optimizes more machine learned algorithms, it’s logical to conclude that computers combined with robotics will become exponentially more capable to performing human tasks.

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There is a difference between artificial intelligence and artificial consciousness. I don’t mean that computers will have emotions anytime soon but they certainly will continue to add more to their repertoire.

 

5. Robots perform Actions

Not only are hundreds of startups and established companies creating robots for every job, these robots will become smarter and capable of performing any number of actions that we can dream up through advancements in AI.

 

6. Actions trigger Sensors

Actions performed by machines triggers more sensors to collect data and the cycle is complete.

 

More sensors collects more data which create more computing intelligence to direct more robots to perform more precise actions which triggers more sensors. That’s my “theory of everything” in technology.

 

While the Industrial Revolution multiplied our physical capacity to do work. We’re now in the early stages of doing the same thing to our mental capacity — infinitely multiplying it by virtue of digital technologies. I guess this is all the prelude to the Singularity.

 

This also poses a more fundamental question: what will humans do?

 

That is a good topic for another post 😉

 

 

文章标题:The “Theory of Everything” in Technology

作者:Li Jiang

来源:medium.com

网址:https://medium.com/global-silicon-valley/the-theory-of-everything-in-technology-c9275f0faf5d


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