Today, with the rapid development of science and technology, human beings are moving towards the top of Maslow's hierarchy of needs. Thanks to the significant increase in computer computing power, the field of artificial intelligence has experienced breakthrough growth. Open AI's products such as Chat GPT and SORA launched for two consecutive years, as well as the high-precision motion display of humanoid robot care, have had a wide impact on the world. The application of these AI technologies not only significantly improves work efficiency, but also effectively improves the quality of life, fully meets people's dual needs for substantive services and concept presentation, and realizes the instant experience of formal results.
From Maslow's needs model, these innovations not only meet people's basic needs, but also play a role at the highest level of self-realization.
The development of the field of artificial intelligence is due to the rapid increase in computer computing power. Whether it's chat GPT, SORA, or service robots, they all rely on powerful computing power behind them. In the near future, we will witness the birth of more disruptive products to meet people's growing and diverse needs, and AI tools will continue to help human beings realize their self-worth.
The next highlighted need will be health and longevity. Although this pursuit has always been throughout human history, it is only with the support of powerful computer computing power that we can expect revolutionary breakthroughs in research in the field of life sciences. The development of biotechnology plays a crucial role in realizing the dream of human health and longevity, yet the research results of biotechnology do not cause a stir as often as artificial intelligence. The reasons behind this are complex and varied, but they can be boiled down to two key factors: first, biotechnology research relies on biological tissues, and the specificity of these tissues leads to the challenge of insufficient data volume and difficulty in data collection, from basic experiments to clinical research, thus prolonging the development cycle; Second, disease** outcomes tend to attract only a smaller range of attention than healthy people.
Together, these factors have shaped the general public perception of the progress of biotechnology, which is slow and has limited impact. However, advances in computing power will bring two major leaps forward in biotechnology.
The first stage (this stage) is the development and introduction of GPU technology, which greatly improves the efficiency of image processing and data analysis. With the support of this computing power, a number of high-end microscopic observation tools will emerge, such as the emergence of structured light microscopy with the advantages of ultra-high-resolution observation of in vivo compared with cryo-EM, and the emergence of biochemical detection systems that can perform Raman signal analysis and processing in the case of "no labeling". These high-end tools make it possible to observe and analyze the in vivo state of organelles with nanoscale spatial resolution, which will have far-reaching implications for verifying how drugs affect organelles. In the second stage, with the maturity of artificial intelligence technology, we may usher in an era of "digital life" for all, which will be accompanied by the explosion of biomedical technology achievements. Through comprehensive physical examination and medical data analysis, a digital life model of each person will be established. Using tools such as structured light microscopy and Raman analysis systems, researchers can import experimental data into digital life systems, and the experimental data will be supported by powerful computing power to obtain scientific verification results and various expected impact guesses. It transforms large amounts of experimental data into actionable knowledge, which greatly shortens the technology development cycle. At this stage, the achievements of biomedical technology will usher in a large-scale explosion period, just like today's artificial intelligence.
With the assistance of artificial intelligence, it is very likely that more high-end label-free cell observation tools will be developed in future biomedical research. These tools can avoid the interference of traditional labeling methods on cell behavior, and provide long-term panoramic observations, thus providing more realistic biological information, and scientists can track the dynamic changes of cellular endosomes and organelles in real time without changing the biological environment. This technological advancement will provide a revolutionary approach to disease mechanism studies and drug screening. From artificial intelligence to biomedicine, the development of science and technology presents a logical and progressive relationship. The maturity of artificial intelligence technology not only improves the efficiency of life, but also provides powerful data processing capabilities for the biomedical field. As biotechnology moves into deeper research, our understanding of life will reach unprecedented heights. This is not only a technological breakthrough, but also a profound exploration of the value and meaning of human life.
This is an introductory article on the three Raman analysis systems in the previous issue:
Raman signal analysis technology supports "label-free" to lead a new paradigm of biochemical detection.
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