Syllabus: GS3/ Science and Technology
Context
- Researchers at the Indian Institute of Science (IISc) have developed a brain-inspired analog computing platform capable of storing and processing data in an astonishing 16,500 conductance states within a molecular film.
About
- This new technology represents a significant advancement from traditional binary computing systems, venturing into the domain of neuromorphic or brain-inspired analog computing.
- Unlike conventional computers, which follow predefined programming, neuromorphic systems have the capability to learn from their environment, potentially elevating artificial intelligence to new levels.
Revolutionizing AI hardware
- This neuromorphic platform could potentially bring complex AI tasks, such as training Large Language Models (LLMs) — like ChatGPT — to personal devices like laptops and smartphones.
- The technology addresses two major hurdles in AI development: lack of optimal hardware and energy inefficiency.
- The molecular system at the heart of this innovation utilizes the natural movement of ions to process and store data in a manner similar to the human brain, creating a “molecular diary” that functions like a computer but with far greater energy efficiency and space-saving capabilities.
Precision and efficiency
- The innovation overcomes significant challenges to achieve the precision needed to measure the molecular states.
- A custom circuit board has been designed capable of measuring voltages as tiny as a millionth of a volt at very fast sampling rates, setting a new benchmark for electronic accuracy.
Future Prospects
- Researchers feel that the breakthrough could position India as a leader in global technology innovation, particularly in AI hardware development.
- In the context of the India Semiconductor Mission, this development could be a game-changer, revolutionizing industrial, consumer and strategic applications.
| Large Language Models (LLMs) – A large language model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content. – Deep learning involves the probabilistic analysis of unstructured data, which eventually enables the deep learning model to recognize distinctions between pieces of content without human intervention. – It helps to understand how characters, words, and sentences function together. |
Source: TH
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