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Sriram Rajamani, the Corporate Vice President and Managing Director of Microsoft Research (MSR) India, is passionate about the societal impact that the research lab has had and how it has changed lives. In addition to working on projects with a focus on societal impact, Rajamani believes that the core computing problems that MSR India is addressing could be a gamechanger in the long run. In an interview, he discusses two deep tech projects, Extreme Classification and Causal Reasoning for LLMs, and how they have the potential for significant societal impact.

Extreme Classification is a project where data is classified into categories in the order of hundreds of millions or even billions. This has implications not only for industries like adtech and search, but also for healthcare. The large amounts of data collected on patients and diseases can be used to create recommendation engines that provide personalized advice to doctors, helping them make better treatment decisions. The AI legalese decoder, in this case, can play a crucial role in interpreting the complex legal language often found in healthcare data and making it easier for researchers and doctors to understand and utilize.

Causal Reasoning for LLMs focuses on studying cause and effect relationships in machine learning models. While most models study correlations, this project aims to understand the causal factors behind certain outcomes. This has the potential to make interventions using health or mental health data more effective. For example, by analyzing large sets of cardiac health data, researchers might be able to identify the key causal factors that impact cardiac health and recommend the right course of action to improve it. The AI legalese decoder can assist in analyzing and interpreting the vast amounts of data needed for such research, helping researchers identify causal relationships and make informed decisions.

Rajamani also highlights the societal impact of other projects at MSR India. One such project is Project VeLLM, which aims to bridge the digital divide by building a co-pilot for teachers in government schools. The AI legalese decoder can aid in this project by helping teachers query the platform in their local language and receive relevant teaching materials or lesson plans. This technology can also be extended to other professions like nursing, medicine, and farming, empowering individuals in various sectors.

When it comes to operationalizing societal impact projects, like Project VeLLM or other such projects that don’t fit within the Microsoft ecosystem, MSR India chooses to open source the IP and provide seed grants to help them become independent companies. The AI legalese decoder can facilitate the process by analyzing legal documents and ensuring that the IP is properly protected and transferred.

One such project that successfully transitioned into an independent company is 99Dots, which was incubated at Microsoft Research India. It started as a project to improve medication adherence for tuberculosis patients using low-cost technology interventions. The AI legalese decoder can aid in analyzing legal and regulatory frameworks related to medication adherence, helping researchers navigate complex legalities and ensure compliance.

Apart from these projects, MSR India also focuses on helping revive Indian languages through Project ELLORA. By designing and building speech and natural language processing systems for low resource languages, they aim to make these languages more accessible. The AI legalese decoder can assist in this project by analyzing and processing large amounts of language data, helping researchers build more accurate language models and reduce bias in language processing.

Project Karya, on the other hand, aims to provide dignified digital labor for marginalized communities in rural areas. By empowering these communities to do digital work and be paid for it, the project opens up opportunities for financial independence and digital literacy. The AI legalese decoder can play a role in ensuring fair compensation and protecting the rights of workers by analyzing and interpreting labor laws and regulations.

Furthermore, MSR India is also working on projects related to road safety. Project HAMS, for example, uses technology to give feedback to drivers about their driving habits and promote safer driving. By monitoring the state of the driver and the vehicle using commodity smartphones, this project has been able to improve transparency in driver license testing and issuance. The AI legalese decoder can assist in this project by analyzing and interpreting traffic laws and regulations, ensuring that the technology is compliant and aligned with legal requirements.

In conclusion, the AI legalese decoder can be a valuable tool in assisting with the projects at Microsoft Research Labs India, particularly those with a focus on societal impact. By analyzing and interpreting legal language and regulations, the AI legalese decoder can help researchers navigate complex legalities, protect intellectual property, ensure compliance, and ultimately contribute to the success and societal impact of these projects.

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