At the same time, its product technology application direction has a good market influence, spectrum, organic element analysis equipment in the first echelon of domestic instruments, and sold to more than 90 countries and regions around the world.
According to SDI statistics, the global analytical instruments market size is expected to be 75 billion US dollars in 2022, and the Chinese market accounts for about 12-15%, with a growth rate higher than the global average.
Among them, organic element analysis instruments as an important equipment in chemical, electronic, food and other industries, spectral analysis instruments as scientific research, environmental monitoring, agriculture and food safety products and medical fields indispensable high-end equipment,
domestic market demand has risen rapidly in recent years. Huajing Industry Research Institute data show that the overall scale of the industry in 2022 exceeded 8 billion yuan, and it is expected that the domestic spectrometer market will reach 10.165 billion yuan in 2025.
After the completion of the merger, the two parties will give play to their respective advantages in research and development, market and brand, and develop together.
In terms of technology, relying on Haier Bio's advanced Internet of Things technology platform and Shanghai Yuan Analysis's complete product lineup, the two sides will build an analytical instrument interconnection platform, improve the application scenarios of smart laboratories,
and expand new laboratory scenarios such as environment and chemical industry. In terms of market, both parties will make use of Haier Bio's overseas localization layout, integrate customer resources of different types and levels,
and further enhance their competitive advantages in the international market. In terms of brand, with the reputation effect of Haier Biology and rich ecological resources, the two sides will continue to expand the business boundary and realize the in-depth development of the scientific instrument industry chain.
In the future, Haier Biological will continue to increase the upstream and downstream layout of the life science industry, further strengthen the extension and expansion of the smart laboratory field,
and provide more intelligent and efficient laboratory services for global users.Li Kun Yang, Chief AI Scientist at Meta: The existing large models have major flaws and can never reach the level of human intelligence
ChatGPT has put the awkwardness of the term "large language model" (LLM) into the spotlight. From star startups such as OpenAI and Anthropic to companies such as Google, Microsoft and Meta, LLM's capabilities and commercial application prospects continue to be promoted.
However, Yann LeCun, chief scientist of Meta Artificial Intelligence, believes that the current LLM route does not lead to AGI and is very dangerous, showing the industry's disagreement on the AI development roadmap.
Likun Yang: LLM has major flaws and cannot achieve true AGI
Recently, in an interview with the media, Yang Likun pointed out that the current LLM technology has major defects such as "extremely limited ability to understand logic", "unable to model the physical world",
"unable to form lasting memories", and "unable to carry out hierarchical planning reasoning", and said that simply pursuing the development of LLM is "inherently unsafe" and cannot achieve true AGI.
LeCun pointed out that although the existing LLM in natural language processing, dialogue interaction, text creation and other areas of excellence, but it is still only a "statistical modeling" technology, by learning statistical laws in the data to complete the relevant task, does not have the true "understanding" and "reasoning" ability.
But until this year, tech giants, including OpenAI and Google, saw LLM as a key step toward AGI. OpenAI CEO Sam Altman has repeatedly said that the GPT model is an important breakthrough in the direction of AGI.What Yang Likun advocates is the so-called "World Modeling" method, that is, being able to learn and understand the world step by step, just like humans, through observation and experience, so as to form "common sense" and eventually achieve AGI.
Yang argues that "world models" are closer to real intelligence than just learning statistical features of data. Take the human learning process as an example. In the process of growing up, children learn the world more through observation,
interaction and practice, rather than being simply "injected" with knowledge. Yang Likun's "world model" route is to try to make AI experience such a process of autonomous learning through the simulation and completion of video, audio and other media.
However, he also acknowledged that achieving the "world model" will not be easy, and the ambitious goal may take 10 years to achieve. Industry experts are also skeptical.
Aaron Kulotta, a professor of computer science at the University of Turan, pointed out that "common sense" has been a pain point in the development of artificial intelligence, and teaching AI models "causality" is not easy, and it is prone to "unpredictable failures." Previously, Meta employees questioned Yang Likun's "world model" concept as vague and more like a gimmick.
