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NO.1 Jensen Huang: Humanoid robots are expected to become popular devices in the future

Nvidia CEO Jensen Huang recently said at the CadenceLIVE Silicon Valley 2024 event that he believes AI will revolutionize three areas: data centers, robotics/autonomous driving, and life sciences. In the near future, humanoid robots are expected to become popular devices, and their manufacturing costs are expected to be much lower than people expect, with prices possibly not exceeding $10,000 to $20,000. In addition, robots may be more agile and versatile in some environments, and are expected to improve productivity.

Commentary: Humanoid robots becoming popular devices will drive the cost-effectiveness of robotics technology and usher in a new era of productivity.

NO.2 3D-printed drug films can "eradicate" cancer cells

Australian scientists have developed the first 3D-printed drug-loaded film. Made from a gel containing specific doses of the anticancer drugs 5-fluorouracil and cisplatin, it can kill cancer cells, significantly reduce the risk of recurrence, and minimize the toxicity of traditional chemotherapy. The research paper was published in the latest issue of the International Journal of Pharmaceutics.

Commentary: This innovation in 3D-printed drug films to fight cancer could change the future of cancer treatment, offering more effective and less side-effect treatments.

NO.3 Apple is rumored to be developing its own device-side large language model

Well-known technology analyst Mark Gurman said in his Power On newsletter that Apple is developing a large language model that runs on devices, aiming to improve the response speed and privacy protection of its upcoming generative AI features. Gurman mentioned that Apple's LLM will be the foundation for the company's future generative AI features. Because it runs on devices, Apple's AI tools may be inferior to cloud-based competitors in some cases.

Commentary: This indicates that Apple is committed to improving the response speed and privacy of AI, despite the potential challenges of competing with cloud-based solutions.

NO.4 AI speeds up Parkinson's drug design by ten times

Researchers at the University of Cambridge in the UK have used AI to significantly accelerate the development of treatments for Parkinson's disease. One way to find potential treatments for Parkinson's disease is to identify small molecules that can inhibit the aggregation of alpha-synuclein (a protein characteristic of Parkinson's disease). In this study, the team used machine learning techniques to quickly screen a chemical library containing millions of entries to identify small molecules that bind to amyloid aggregates and prevent them from proliferating, ultimately identifying five highly effective compounds. Using AI technology, the researchers accelerated the initial screening process by 10 times and reduced the cost to a thousandth, meaning that the development of potential Parkinson's disease therapies could be much faster.

Commentary: The application of AI in drug discovery may significantly improve efficiency and reduce costs, bringing new hope for the treatment of Parkinson's disease.

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