Artificial intelligence (AI) is a branch of computer science that attempts to understand the essence of intelligence and produce new intelligent machines that can react in a way similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Since its inception, AI has matured in both theory and technology, and its applications have expanded continuously. It is conceivable that future AI-driven technological products will serve as "containers" of human wisdom. AI can simulate the information processes of human consciousness and thought. While AI is not human intelligence, it can think like a human and may even surpass human intelligence.
Artificial intelligence is a very challenging science, and those who work in this field must understand computer science, psychology and philosophy. Artificial intelligence is a very broad science, consisting of different fields such as machine learning, computer vision and so on. In general, a major goal of artificial intelligence research is to enable machines to perform some complex tasks that usually require human intelligence. However, different eras and different people have different understandings of this "complex task". [1] In December 2017, artificial intelligence was selected as one of the "Top Ten Buzzwords in Chinese Media in 2017". [2] On September 25, 2021, in order to promote the healthy development of artificial intelligence, the "New Generation Artificial Intelligence Ethics Code" was released.
If we're talking about the hottest trend on the internet right now, it has to be AI. From AI recognition, AI portraits, and AI voice a few years ago, to AI video and AI anchors, the speed of AI's evolution in recent years has been quite astonishing.
It's no exaggeration to say that AI has gradually permeated the lives of ordinary people, and a simple online search yields a plethora of related content.
Of course, the applications of this technology are not far from us; but the real technological support for AI is something that most of us cannot access.
AI stands for Artificial Intelligence. It uses deep learning to accomplish specific tasks, which requires powerful computing and algorithms.
As AI technology matures, it has inevitably replaced some manual labor jobs, leading to increased unemployment. However, given the needs of global development, some iterative processes are unavoidable.
AI has once again become the focus of public opinion. As a recurring topic, this time AI's popularity is no longer due to "generating intelligence," nor is there a legendary showdown of "winning against fate," but it is still astonishing.
AI-generated art is becoming a trend. Even if you have no artistic talent, simply enter a few keywords into AI drawing software, choose your desired style and perspective, and you can create a high-quality artwork in collaboration with AI. With its astonishing technological level and creative capabilities, AI painting has become one of the top concepts in the technology field both domestically and internationally. In just over a month, countless AI paintings have been produced, and AI is aggressively challenging the realm of human artistic creation, a field we are so proud of.
To some, this might be another form of "AI crisis." Just how far has AI painting progressed? Will it truly become a formidable enemy of human imagination and creativity? With these questions in mind, I opened an AI drawing app and entered keywords like "artificial intelligence," "art," and "creation" into the prompt section. A few dozen seconds later, a surrealist painting appeared before me:
A giant robot stands silently, connected to a complex mechanical device behind it, where vibrant colors and cold steel create a striking contrast.
On August 31, 2022, Jason Allen, an American game designer, won first prize in an art competition at the Colorado State Fair for his work titled "Space Opera." This painting is a standard space opera-style artwork, except it was created by AI.
"Space Opera," created by Jason Allen using the AI drawing software MidJourney, was generated after nearly a thousand attempts. The news quickly sparked heated debate in the global art world, with the use of AI in an art competition drawing criticism against both "Space Opera" and its creator. Coincidentally, also in August, a journalist from the American magazine *The Atlantic* was embroiled in controversy for using MidJourney to create illustrations for an article, thus igniting a global debate on AI-generated art.
While AI-generated art is gaining momentum, applications for AI-generated video are quietly emerging. At the end of September, Metacritic announced its Make-A-Video AI video creation tool. This tool can generate high-quality short videos. Before the news of Meta's AI video creation had even cooled down, Google followed suit, launching two AI-generated video tools: Imagen Video and Phenaki. The former focuses on improving video quality, while the latter emphasizes video logic and length. These AI video creation tools each have their own unique features.
The AI technology for generating images from text has only been popular for a few months, and it has already leaped directly to generating dynamic videos from text. From drawing to video production, the speed of AI's development is astonishing, and it inspires anticipation for the future of digital media. So, what exactly will this leap bring to the future?
AI-generated video is an extension of AI-generated image processing.
Before discussing the changes that AI-generated videos will bring to the future, let's first review the technical principles and application scenarios of AI-generated videos.
Feng Yuan: Yes, artistic creation isn't done with algorithms. This is different from mathematical logic; algorithms based on mathematics may not require emotion. This brings us to a very serious question: if we can create an artificial intelligence that possesses both emotional changes and endocrine mechanisms, then such AI will have a "human mind," and only then can it create art. Otherwise, images processed by algorithms, lacking a human heart, can only imitate but lack the ability to autonomously create and perceive art.
Collection Weekly: It seems difficult for us to distinguish between art created by artificial intelligence and art created by humans.
Models serve as a bridge between the three fundamental elements of computing power, algorithms, and data, and application scenarios. They are both a synthesis of these three elements and a key to solving the needs of application scenarios. Models are a core concept in the field of artificial intelligence. Every AI application addresses the specific needs of the application scenario by building or selecting a suitable model, training and fitting the model using relevant data and algorithms, and then providing the trained and fitted model for inference services, thereby automatically solving the tasks of the specific application scenario.
The models possess strong versatility; the same type of model can be applied across multiple domains to solve specific problems in various scenarios. Companies engaged in model development often need to develop models for specific application scenarios to create corresponding AI application products, while some companies primarily provide model development services. Specific industry applications of the models will be analyzed in later sections, focusing on opportunities inherent in the models themselves.
Professional model development is a core aspect of AI technology, and areas such as large models, multimodal models, and small models deserve special attention.
Specialized models have always been a core area of research and entrepreneurship in the AI field, mainly focusing on visual image processing, speech recognition, natural language processing, and knowledge graphs. Many specialized models were created to solve problems in these areas. In recent years, the emergence and development of large-scale models have also led to the integrated development of multimodal models such as image, speech, and text. Edge computing applications are becoming increasingly diverse, and small models have significant advantages on edge terminals.
In the field of visual imaging, there are companies and research institutions engaged in this work. Visual imaging models are probably the most widely used or most common AI models in industry applications. Not only have the "Four Little Dragons of AI" emerged, but more innovative companies in various sub-fields have also been created. Application areas include OCR, security, autonomous driving, and have also expanded to more fields such as medical care, industry, ports, water conservancy, and energy.
Many companies and research institutions are involved in speech recognition and synthesis, including voiceprint technology. Currently, it is widely used in customer service and interaction. Voiceprint, as a new identity authentication method, is also used in internet and financial account systems. In addition, speech models are beginning to be applied to industrial machine maintenance and other fields.
Natural Language Processing (NLP) aims to enable computers to process and understand human language. In recent years, NLP has become increasingly integrated with knowledge graphs, and its research scope has expanded from basic word segmentation and representation to more complex areas such as knowledge reasoning. Currently, the core of mainstream large-scale model research also revolves around NLP. NLP has wide applications in search, dialogue systems, and public opinion analysis.
The Transformer model originated as a classic model for solving NLP problems and is now widely used in image and speech processing, and even in the discovery of large molecules for drug development. Many large and multimodal models are also based on the Transformer model.
