DeepTech launches a collection of [15 typical application cases of using large AI models in the real world]

The tech world is facing cash shortages, mass layoffs, and investor demands for profits over growth, but you won’t see these phenomena from the generative AI industry.

According to CB Insights data, so far, 13 generative AI companies around the world have reached a valuation of US$1 billion, The vast majority of which have entered the independent stage in the past year or so. The horned beast team. Five more companies have joined the ranks this year, such as Cohere, Runway and more. Some unicorn companies are developing their own Large Language Models (LLM).

Among these 13 generative AI unicorns, the average time to reach unicorn status was 3.6 years. But for the unicorn club as a whole, the average time is seven years, almost twice as long. This rapid funding and high valuation is mainly attributed to the market and investor enthusiasm and excitement for generative artificial intelligence.

OpenAI, a leading player in the industry, has a valuation of $29 billion, a tenfold increase from 2019. It’s followed by Anthropic (valued at $4.4 billion), Cohere ($2 billion) and Hugging Face ($2 billion).

Figure | Unicorn companies in the field of generative AI and their valuations (Source: CB Insights)

In the first 10 years of the 21st century, natural language processing technology appeared in people's vision. The first wave of digital technology changes came with the rise of the Internet and mobile Internet. We have witnessed the rise and growth of a large number of Internet companies. . Starting with deep learning in 2013, digital and computing-related technologies have entered the second decade of rapid iteration. We have also experienced the ups and downs of artificial intelligence applications in the past few years.

It can be said that we are currently at the beginning of the third decade of the development of artificial intelligence. Artificial intelligence will grow in the direction of higher-dimensional, more autonomous, and multi-modal systems. From perceptual intelligence to cognitive intelligence, AI will begin to participate in cognitive and creative tasks.

Technological breakthroughs in recent years have continuously brought machine intelligence closer to "human intelligence". For example, GPT-3 was selected as one of the top ten breakthrough technologies in MIT Technology Review in 2021, and GPT-4, which we are talking to today.

The successful application of large-scale models is an example of generative artificial intelligence technology and reflects the huge potential of this field. From the perspective of underlying technology, the key to which all parties are competing to seize the market is AI large-scale models.

The “most popular” is OpenAI’s use of large-scale language models to build dialogue applications, which demonstrates the application potential of large models in the fields of natural language processing and dialogue systems. Other startups are using generated AI chatbots to support sales and customer support, such as Lightski, Kyber, etc.

Large models are playing an important role in different industries and driving real-world application innovation.

In the financial field, large models are used in risk assessment, transaction prediction and investment decision-making. In the medical field, large models are used for disease diagnosis, drug development and personalized treatment... The application of large models will bring more efficient and intelligent solutions to various industries and promote the development and progress of society.

Standing at the beginning of the third decade of development of artificial intelligence and on the eve of the transformation of the intelligent era, DeepTech launched [15 typical application cases of using AI large models in the real world] research work. We will focus on real cases of AI large models in finance, medical care, education, scientific research and other fields, and explore the application, effects and potential challenges of large models in different industries through detailed analysis and case studies .

We will also summarize the common patterns and trends in each case, put forward suggestions for future research and practice, and provide guidance for the further development and application of AI large models, with a view to providing readers with the opportunity to comprehensively understand and gain insight into this field.

If you are interested in our research and want to have further exchanges and cooperation, you are welcome to contact us at any time. We look forward to in-depth exchanges and cooperation with professionals, scholars and practitioners from all walks of life to jointly explore the future development and application prospects of AI large models.

We look forward to sharing with you the results of our research using large models of AI in the real world and exploring future developments in this exciting field with you. Whether you are an industry practitioner, an academic expert or an individual with an interest, we welcome your participation and contribution. Let us work together to create a new chapter of AI large models in the real world!

The above is the detailed content of DeepTech launches a collection of [15 typical application cases of using large AI models in the real world]. For more information, please follow other related articles on the PHP Chinese website!