Irene Terpstra ’23 and Rujul Gandhi ’22, two MIT engineering students, are leveraging natural language for AI systems. Terpstra’s team is using language models to assist in chip design, while Gandhi is developing a system to convert natural language instructions for robots. Gandhi is also working on speech models for low-resource languages, seeing potential in expanding language technology applications globally.
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Using Natural Language to Build AI Systems
Natural language is a valuable source of data for training machine-learning systems. At MIT, Irene Terpstra and Rujul Gandhi are working on practical AI solutions using natural language in collaboration with the MIT-IBM Watson AI Lab.
AI in Chip Design
Terpstra and her team are developing an AI algorithm to assist in chip design by using large language models and reinforcement learning algorithms. This will streamline the circuit design process and potentially lead to the automatic design of chips.
Improving Communication with Robots
Gandhi is working on a system that converts natural language instructions into a machine-friendly form, enabling smooth communication between humans and robots. This approach allows for more flexible instruction phrasing and logical dependencies, making it easier for users to interact with AI systems.
Language Processing for Low-Resource Languages
Gandhi’s research also focuses on language processing for low-resource languages, aiming to efficiently use limited data for speech recognition and understanding. This has potential applications in improving voice assistants, translation, and interpretation.
Practical AI Solutions for Middle Managers
For middle managers looking to leverage AI in their organizations, consider the following practical steps:
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
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