Detailed introduction to artificial intelligence related information
Introduction to Artificial Intelligence
Artificial Intelligence (AI). It is a new technological science that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence.
Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and generate a new type of intelligent machine that can respond in a way similar to human intelligence. Research in this field includes robotics, language recognition, image recognition, natural language processing, and expert systems. Since its inception, artificial intelligence has become increasingly mature in theory and technology, and its application areas have been expanding. It can be imagined that the technological products brought by artificial intelligence in the future will be the "container" of human intelligence. Artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but it can think like or surpass human intelligence.
Artificial intelligence is a challenging science, and those engaged in this work must have an understanding of computer knowledge, psychology, and philosophy. Artificial intelligence is a very broad science that consists of different fields, such as machine learning, computer vision, and so on. Generally speaking, one of the main goals of artificial intelligence research is to enable machines to perform complex tasks that typically require human intelligence. But in different eras, different people have different understandings of this "complex work". In December 2017, artificial intelligence was selected as one of the "Top 10 Hot Words in Chinese Media of 2017". On September 25, 2021, in order to promote the healthy development of artificial intelligence, the "New Generation of Artificial Intelligence Ethics" was released.
AI Artificial Intelligence
Definition analysis
The definition of artificial intelligence can be divided into two parts, namely "artificial" and "intelligent". "Artificial" is easier to understand and less controversial. Sometimes we need to consider what humans can do, or whether human intelligence is high enough to create artificial intelligence, and so on. But overall, "artificial systems" are typically artificial systems.
There are many questions about what "intelligence" is. This involves other issues such as consciousness, self, and mind (including unconscious mind). People generally believe that the only intelligence they know is their own intelligence. However, our understanding of the necessary elements of both our own intelligence and human intelligence is very limited, making it difficult to define what "artificial" intelligence is. So research on artificial intelligence often involves the study of human intelligence itself. Other intelligence related to animals or other artificial systems is generally considered a research topic related to artificial intelligence.
Artificial intelligence is receiving increasing attention in the field of computer science. It has been applied in robotics, economic and political decision-making, control systems, and simulation systems.
Professor Nelson defines artificial intelligence as follows: "Artificial intelligence is a discipline about knowledge - how to express knowledge, and how to acquire and use it." Another MIT professor, Winston, believes that "artificial intelligence is the study of how to make computers do intelligent work that only humans could do in the past." These statements reflect the basic ideas and content of artificial intelligence. Artificial intelligence is the fundamental theory, method, and technology that studies the laws of human intelligence activities, constructs artificial systems with certain intelligence, and studies how to make computers perform tasks that require human intelligence in the past, that is, how to apply computer software and hardware to simulate some intelligent behaviors of humans.
Artificial intelligence is a branch of computer science that has been known as one of the world's three cutting-edge technologies (space technology, energy technology, and artificial intelligence) since the 1970s. It is also considered one of the three cutting-edge technologies of the 21st century (genetic engineering, nanoscience, and artificial intelligence). This is because it has developed rapidly in the past 30 years and has been widely applied in many disciplines, achieving fruitful results. Artificial intelligence has gradually become an independent branch, forming its own system in theory and practice.
Artificial intelligence is a discipline that studies how computers can simulate human thinking processes and intelligent behaviors, such as learning, reasoning, thinking, planning, etc This mainly includes the principle of computer intelligence, making computers similar to human brain intelligence, and enabling computers to achieve higher-level applications. Artificial intelligence will involve computer science, psychology, philosophy, and linguistics. It can be said that almost all disciplines of natural and social sciences have far exceeded the scope of computer science. The relationship between artificial intelligence and thinking science is the relationship between practice and theory. Artificial intelligence is at the technological application level of thinking science and is a branch of its application. From a cognitive perspective, artificial intelligence is not limited to logical thinking. Only visual thinking and inspirational thinking can drive the breakthrough development of artificial intelligence. Mathematics is often regarded as the fundamental science of many disciplines, and it has also entered the fields of language and thinking. The discipline of artificial intelligence must also borrow mathematical tools. Mathematics not only plays a role within the scope of standard logic and fuzzy mathematics, but also enters the discipline of artificial intelligence, promoting each other and developing faster.
AI Artificial Intelligence
Introduction to Science
practical application
Machine vision, fingerprint recognition, facial recognition, retina recognition, iris recognition, palm print recognition, expert systems, automatic planning, intelligent search, theorem proving, gaming, automatic programming, intelligent control, robotics, language and image understanding, genetic programming, etc.
Topic categories
Artificial intelligence is an interdisciplinary field that belongs to the intersection of natural sciences and social sciences.
Involving disciplines
Philosophy and cognitive science, mathematics, neurophysiology, psychology, computer science, information theory, control theory, uncertainty theory.
Research category
Natural language processing, knowledge representation, intelligent search, reasoning, planning, machine learning, knowledge acquisition, combinatorial scheduling problems, perception problems, pattern recognition, soft computing in logical programming, imprecise and uncertain management, artificial life, neural networks, complex systems, and legacy algorithms.
Consciousness and Artificial Intelligence
Artificial intelligence is essentially a simulation of human cognitive information processes.
The simulation of human thinking can be carried out in two ways. One is structural simulation, which mimics the structural mechanisms of the human brain and creates "brain like" machines; The second type is functional simulation, which temporarily sets aside the internal structure of the human brain and simulates its functional processes. The emergence of modern electronic computers is a simulation of the thinking function of the human brain and an information process of human brain thinking.
Weak artificial intelligence is developing rapidly now, especially after the 2008 economic crisis. The United States, Japan, and Europe all hope to achieve reindustrialization through robots. Industrial robots are developing at an unprecedented speed, further driving breakthroughs in weak artificial intelligence and related industries. Many tasks that must be done by humans can now be accomplished by robots.
But strong artificial intelligence is currently at a bottleneck and requires the efforts of scientists and humans.
Related achievements
pattern recognition
Using the $TERM pattern recognition engine, there are 2D recognition engines, 3D recognition engines, standing wave recognition engines, and multi-dimensional recognition engines.
The 2D recognition engine introduces fingerprint recognition, portrait recognition, character recognition, image recognition, and license plate recognition. The standing wave recognition engine has introduced speech recognition.
Automation Engineering
Autonomous Pilot (OSO System)
Banknote printing factory (assembly line)
Falcon System (YOD Drawing)
knowledge engineering
This article takes knowledge itself as the processing object and studies how to use artificial intelligence and software technology to design, construct, and maintain knowledge systems.
expert system
Intelligent search engine
Computer Vision and Image Processing
Machine translation and natural language understanding
Data mining and knowledge discovery
Related works
Visual Reading Artificial Intelligence: Can Machines Really Think? Is human thinking just a complex computer program? This book focuses on artificial intelligence, one of the most challenging scientific issues in history, and focuses on some of the main topics behind it. Artificial intelligence is not just a fictional concept. Half a century of research on intelligent agent structures has shown that machines can defeat the greatest chess players, humanoid robots can walk, and interact with humans. Although there has long been a declaration that smart machines are just around the corner, progress in this area is slow and difficult. Consciousness and environment are two challenges that plague research. How should we actually manufacture intelligent machines? Should it work like a brain? Does it need a body? From Turing's profound influence on basic research to the leap of robots and new artificial intelligence, this book presents readers with a clear picture and text presentation of the development of artificial intelligence over the past half century.
The Future of Artificial Intelligence: Explain the connotation of intelligence, explain the working principle of the brain, and tell us how to create truly intelligent machines - such intelligent machines will no longer just imitate the human brain, but their intelligence will far surpass the human brain in many aspects. Hawkins believes that previous efforts to replicate human intelligence, from artificial intelligence to neural networks, have never been successful because people have not truly understood the meaning of intelligence and the human brain. The so-called intelligence refers to the ability of the human brain to compare the past and predict the future. The brain is not a computer and cannot follow the trend, producing output step by step based on input. The brain is a huge memory system that stores experiences that reflect the true structure of the world to a certain extent. It can remember the order and relationships of events and make predictions based on memory. The brain's memory prediction system forms the foundation of intelligence, sensation, creativity, and perception
Artificial Intelligence Philosophy: Artificial intelligence philosophy is a philosophical branch that has emerged with the development of modern information theory and computer technology. This book collects fifteen representative papers from scholars in the field of artificial intelligence research, making groundbreaking contributions to the development of computer science and the establishment of the philosophy of artificial intelligence. These articles summarize the development history of artificial intelligence, the trends of the discipline, and important topics in artificial intelligence. Among these groundbreaking works are: Alan Turing's "Computers and Intelligence", the father of modern computer theory; American philosopher Searle's "Mind, Brain, and Program"; J.E. Hinton et al.'s "Distributed Expression", and M.A. Boden, the editor in chief of this book and a British artificial intelligence scholar, "Escape from the Chinese House".
Artificial Intelligence: A Modern Method: This book comprehensively elaborates on the core content of the field of artificial intelligence from the perspective of rational subjects with detailed and rich materials, and provides an in-depth introduction to the main research directions. It is a rare comprehensive textbook. The book is divided into eight parts: the first part is "Artificial Intelligence", the second part is "Problem Solving", the third part is "Knowledge and Reasoning", the fourth part is "Planning", the fifth part is "Uncertain Knowledge and Reasoning", the sixth part is "Learning", the seventh part is "Communication, Perception and Action", and the eighth part is "Conclusion". This book not only provides a detailed introduction to a large number of basic concepts, ideas, and algorithms, but also describes the latest developments in various research directions, collecting detailed historical literature and events. Therefore, this book is suitable for researchers and students at different levels and fields. It can be used as a textbook or teaching guide for undergraduate and graduate students in the field of information and related fields, as well as a reference book for scientific research and engineering technicians in related fields.
Introduction to OpenAI
Artificial intelligence is defining a whole new world that can be touched, applied, recognized, and used by millions of users on a large scale, creating tremendous social positive meaning and making society more perfect and beautiful.
A scientist at the Max Planck Institute said, "Artificial intelligence will change medicine, research, and bioengineering. It will change everything."
Before the birth of ChatGPT, this statement was questioned because AI, as a shining star in the world of technology and the Internet, did not practice the law of "trust based on what you see". But rather, AI entrepreneurs, capital, and media are constantly creating a sense of the future, leading the public world to doubt the prospects of AI. Even in the capital market, the financial reports of AI companies and the curves of the secondary market seem to outline an uncertain scenario.
The lack of a phenomenal AI product and an AI product with explosive power and market education is a microcosm of the global AI market in the past. Until then, OpenAI, the AI intelligent chat robot ChatGPT, was defined as a new paradigm of AI by the global scientific and technological community. Its penetrating market power made ChatGPT once gain millions of users, and even the market thought: "It will subvert the search engine giant Google. Its super emotional intelligence and huge power will form a huge ripple in the field of content and creativity. Perhaps, the existing Internet information system will change as a result."
This is "believing by seeing". OpenAI and ChatGPT have achieved it, and the world is boiling with joy.
According to the latest news, Microsoft has announced a third phase of cooperation with OpenAI, the developer of the online chatbot ChatGPT, and will invest "years and billions of dollars" in OpenAI. The New York Times revealed that Microsoft will invest $10 billion in OpenAI, and the value of OpenAI will reach $29 billion.
Microsoft CEO Setya Nadella said last week, "Artificial intelligence is the next major wave of computing."
In the future, AI will officially announce to the world: "The era of AI has officially arrived. The global public has new ideas and stronger expectations for AI.".
A headwind
Microsoft has invested $10 billion in OpenAI, worth $29 billion.
In fact, in the past, global technology giants have entered a "downward cycle" of declining market value, layoffs, and shrinking ecological business strategies. In many formats, wearable devices, mobile devices, 3D printing, blockchain, Web 3.0, and the metaverse, and even more technology languages and products, have engaged in large-scale competition in this special cycle, competing with the market, capital, and users. After settling down at this moment, the value of artificial intelligence gradually becomes prominent and amplified, and its dominant technological attributes in the next era are emerging.
So at present, AI belongs to the global development trend of upwind flight. Because it's very simple, AI is building the next wave of calculations.
As a global technology giant with a market value of $1.8 trillion, Microsoft's business covers operating systems, office software, tablets, gaming consoles, cloud services, and investments. This strategic investment in OpenAI can be said to be a milestone in the field of artificial intelligence. It is precisely in this "technological winter" that the strongest and hottest signal has been sent, that artificial intelligence will dominate the future computing wave, and of course, it also has many meanings:
1. Market resonance, world giants investing in phenomenon level AI applications.
In the AI market, many companies, such as the Internet giant AI camp headquartered in China, the retail giant AI camp, the technology giant AI and the vertical AI giant, have formed Chinese AI battleships, and there is also a lot of capital for strategic investment, making Chinese AI shine globally. Microsoft's strategic investment in OpenAI is a heavyweight giant. For phenomenon level AI applications, strategic investment itself has a huge global market resonance effect, which can bring a lot of imagination and guidance to the market in the absence of technology borders. Even for China, the world's second largest economy, it has brought a "guiding force for building the future"
2. Guiding the direction, the ultimate significance of AI belongs to serving users.
In the past, AI was mostly limited to the B-end market and applied in some special scenarios, while AI aimed at C-end users, especially products with large-scale applications, was relatively scarce. The birth of ChatGPT has reshaped the AI world, and it is widely used by users. During use, ChatGPT has become increasingly intelligent, and the market believes that ChatGPT will soon overturn Google. So Microsoft's $10 billion investment in OpenAI points out a direction and has good guidance and educational significance for the market. The ultimate significance of AI lies in serving a wide range of users. So far, there are not many AI products with Internet product attributes, and ChatGPT is the brightest star.
The value of $29 billion is the current value of OpenAI, and this value will continue to expand with the continuous use of ChatGPT. Under the empowerment of large-scale capital, there will be billions of unicorns in the future AI market.
Of course, these billion dollar unicorns will also appear in China.
2 Smile curves
Deep brain chain GPU empowers AI with new laws, making AI more efficient.
At present, China and the United States are competing comprehensively, and Chinese AI entrepreneurs are also constantly innovating. The most noteworthy is that major Chinese technology giants have set up "AI platforms" to cover large-scale scenarios.
As is well known, artificial intelligence (AI) refers to the technology of simulating, expanding, and enhancing human intelligence through computers and related technologies.
The research fields of artificial intelligence include machine learning, natural language processing, image recognition, visual recognition, and robotics technology. Therefore, China is gradually realizing the commercialization and scenario based application of AI technology, which makes the Chinese market gradually have a very strong future of AI applications.
As an important participant in Chinese AI, DeepBrain Chain's strategic approach is to participate in a distributed and decentralized manner. DeepBrain Chain is an artificial intelligence (AI) computing platform driven by distributed technology, with the goal of becoming the "cloud computing platform in artificial intelligence.". Established in November 2017, our vision is to build the world's largest distributed high-performance computing network based on decentralized technology, becoming the most important infrastructure in the 5G+AI era.
Obviously, on the AI track, giants are keen on centralizing capital and services, storing products in the CPU processor layer, and ultimately completing the processing of information and programs; For startups, DeepBrain Chain enters the AI arena, adopting a decentralized product form and centralized service model, and empowering artificial intelligence products and developers with GPUs.
In my opinion, there are many differences between CPU and GPU, and DeepBrain Chain has made good use of the advantages of GPU and ultimately gained market favor:
1. GPU is designed based on high throughput, making AI more efficient.
For artificial intelligence products, all products require more powerful computing. The current general practice is to use the CPU approach to complete calculations. For example, when content creators publish their works on the platform, AIGC technology will calculate and generate visual video content. During this process, the GPU played a significant role.
When facing large-scale data systems, when AI needs to process billions of terabytes of data, GPUs designed based on high throughput are put into use. The characteristic of GPU is that it has more alus and less cache. The purpose of caching is not to store data that needs to be accessed in the future, which is different from CPU, but to improve thread service. Unlike CPUs that excel in logic control, serial operations, and general data operations, GPUs excel in large-scale concurrent computing, so in addition to image processing, GPUs are increasingly involved in computing.
Overall, GPUs are more suitable for processing large-scale data, leveraging the advantages of distributed computing systems to make AI more intelligent and efficient.
2. GPU and AI have a natural coupling, making AI smoother.
As is well known, the Central Processing Unit (CPU) refers to the central processing unit that determines the running speed of mobile phones and hardware. GPU (Graphics Processing Unit) refers to an image processor used to render game graphics on a mobile phone. Usually, the newer the GPU model and the higher the frequency, the faster the display speed of the game screen.
For AI, AI products are based on language and computational algorithms, language recognition, image recognition, and natural language processing. The CPU is the heart of the entire computer, and the GPU is the heart of the graphics card. Naturally, GPU and AI have a natural coupling, which can make AI products smoother and their computational efficiency completely superior to CPU.
At present, while global artificial intelligence is advancing rapidly, DeepBrain Chain has adopted a very high-quality strategy to empower the AI market. At the same time, we have persisted for more than five years and continuously innovated and made breakthroughs, which have been recognized by the market. At this moment, the market has shown a smiling curve towards the DeepBrain chain.
three
Longevity ism
Deep brain chain leads the future market of AIGC, gaining favor through persistence.
After the popularity of ChatGPT, another AI technology, AIGC (AI Generated Content), began to flourish and was widely applied.
AIGC (AI Generated Content) is content generated by AI, characterized by automated production and high efficiency. With the maturity of natural language generation technology NLG and artificial intelligence models, AIGC has gradually attracted people's attention. Currently, text, images, audio, video, and even 3D models and code can be automatically generated. AIGC will greatly promote the development of the metaverse, where a large amount of digital native content requires the assistance of AI to complete its creation.
Obviously, a large amount of AI in AIGC processes graphic and textual video content, and when AIGC products are integrated into the Deep Brain Chain AI cloud platform, their distributed GPU system will quickly process the content, making it smooth, clear, and more excellent. Currently, a large number of AIGC artificial intelligence products are choosing to integrate into deep brain chain AI cloud platforms.
Users who have witnessed the development of DeepBrain Chain can see the innovation and efforts of the founding team of DeepBrain Chain. It can be said that I believe the intervention of distributed technology can help deep brain chains avoid direct competition with centralized technology giants at the development level, and thus achieve rapid growth in this field.
At present, Deep Brain Chain DBC serves more than 30 countries worldwide, with nearly 50 manufacturers deploying high-performance GPU cloud platforms based on Deep Brain Chain networks, serving hundreds of enterprises and tens of thousands of AI developers. For example, from Tuyun, DBChain, Yousanai, Deep Eye GPU Cloud Platform, AINLP, 52CV, Ant Mining, Windywinter, Fanchuangai, DIMI Artificial Intelligence, TeuringCloud from Singapore, Hycons Cloud from South Korea, and so on. For DBC deep in the brain chain, there is also a top-level scientific team. For example, Harbin Institute of Technology's AI ranked first in the SMP2017 Chinese human-machine dialogue evaluation business, with more than 30 top domestic artificial intelligence teams participating; Silicon Valley provides artificial intelligence and blockchain research centers to conduct cutting-edge research on distributed technology and artificial intelligence. These achievements are sufficient to demonstrate the advantages of DeepBrain Chain technology:
1. High performance DeepBrain Chain GPU cloud platform.
The reason why it can serve large-scale users and manufacturers lies in the high-performance DeepBrain Chain GPU cloud computing platform, high throughput, stable distributed cloud computing capabilities, smoothness, storage, processing, and computing capabilities, which maximizes GPU computing power. At present, the platform has been running steadily for 428 days, with 2035 GPUs and a rental rate of 88.50%. Its sustainability is a dimensionality reduction blow to traditional remote operation apps.
2. Infinite expansion of deep brain chains based on blockchain
The main network of deep brain chain is developed based on Boca substrate. Deep Brain Chain is also one of the few high-performance computing projects in the blockchain industry to achieve large-scale implementation. Since its establishment, Deep Brain Chain has been committed to improving the availability of Deep Brain Chain computing networks and promoting commercialization. It is possible to achieve market separation based on distributed cloud computing capabilities, algorithms, and data. Compared to the centralized giant aggregation model of data, algorithms, and computing power, distributed will promote the market separation of data, algorithms, and computing power. Ensure the security of data, block the possibility of uncertainty caused by centralization, and thus achieve more stable system services.
Pragmatism, innovation, exploration and innovation in the AI world, global AI entrepreneurs optimize the world with wisdom and code, making the world a better place. The explosion of ChatGPT and billions of dollars in strategic investment have illuminated the beacon of the future world for global technology entrepreneurs. DeepBrain Chain is located on the AI track and uses a unique GPU calculation method to outline the AI. After five years of persistence, it has been favored by large-scale users. This is also the simplest and most long-term output of a group of AI entrepreneurs.
So, is there any reason to believe that the AI era will become better due to the involvement of DeepBrain Chain?
Li Anwei, a well-known technology We Media, loves the Internet, technology, retail, manufacturing, real enterprises and new business civilization. He is known for his scarce vision and insight into the next second of business trends, with enormous dissemination power. Each article will be synchronized with dozens of top columns.