ProductNation/iSPIRT

India's 2024 Budget signals a strong commitment to innovation and economic growth, with key themes focused on research and development (R&D), ease of doing business (EoDB), and leveraging digital public infrastructure (DPI). The budget allocates ₹1 lakh crore for private R&D, including investments in strategic areas like Small Modular Nuclear Reactors and the Space economy. It also eliminates the "angel tax" to boost the startup ecosystem and announces plans to simplify regulations and improve EoDB. Further, the budget emphasizes utilizing DPI for various sectors, from agriculture to education, to drive digitalization and economic growth. These measures aim to foster a vibrant innovation landscape, attract investment, and propel India towards its goal of Viksit Bharat 2047. #IndiaBudget2024 #Innovation #Startups #EoDB #DPI #R&D #product_nation Sharad Sharma https://lnkd.in/g733i3sD

Easily accessible Digital Public Infrastructure for AI applications like developing Machine Learning models is needed because most companies lack the resources to do so while Big Tech dominates For more - https://lnkd.in/gXiQ4mxk

One picture, one massive story of how India has frogleaped using the rails of Digital Public Infrastructure. That too in a short span of ten years or so That remaining question mark? That's DEPA helmed by security and privacy, to unlock India's treasure chest of data to benefit society For more, check this out - https://lnkd.in/gXiQ4mxk

India is ranked 40th in the latest Global Innovation Index 2023. Nearly ten years ago when India was ranked 76th, Rishikesha Krishnan said "India’s Achilles heel continues to be what is represented by the Human Capital and Research (HCR) parameter of GII [Global Innovation Index]" Is education quality still holding back India? Let us know your views in the comments https://lnkd.in/gjKkaeEJ

Learn how DEPA for Training has security + privacy by design, minimizing risk of re-identifying user data Real-time granular consent from data principal may not be practical at all times, but DEPA for Training keeps user data secure + private by design https://lnkd.in/duNuUcXW

The first instance of DEPA (Data Empowerment and Protection Architecture) in the financial domain was called 'account aggregator' and is giving millions of citizens very fine granular control of their financial data and creating a trustworthy digital ecosystem. DEPA will play a very similar role in other ecosystems such as Commerce and Healthcare. DEPA has been extended to create a new architecture for responsible training of AI models. The new architecture is called DEPA for Training. DEPA for Training addresses scenarios like training models for detecting fraud, for example, using data sets from multiple banks, or helping study diagnose diseases without compromising privacy of individuals whose data is used in training these models Watch for more: https://lnkd.in/duNuUcXW

Do you feel these words from 2015 still ring true? Creative inventors with creative ideas need creative capital “As a first-gen entrepreneur and professional by training, I have become contemptuous of the local investor community—it uses a cookie cutter approach with very limited imagination. They would rather blow their cash on an app (without proof of concept) than on a good service model that has growth potential. We pretend in India to be like the Silicon Valley guys, but we don’t really have the b****s!” https://lnkd.in/gYq6DMgW

Digital Public Infrastructure like DEPA for Training is designed to ensure critical issues like person’s (data principal’s) privacy is maintained if the data principal’s data is used as part of a data set, that is used to train an AI model which could be of large-scale benefit to society in areas like healthcare and finance. Training Data Providers (TDPs) are entities who collect aggregated large data sets. Think of TDPs as being banks, hospitals, insurance companies, and social media companies and so on.   A Training Data Consumer (TDC) is any organization that use these data sets to train models . A TDC could be a fintech or a healthtech that wishes to train models to detect fraud or a research lab that wishes to build an AI model to diagnose diseases. For this data sharing to happen, a relationship of trust must be built between TDCs and TDPs. This trust can be built through a digital contract. In DEPA for Training, for TDPs and TDCs to enter into any sort of collaboration and share data sets, the TDCs must first register their data sets with a service called the Contract Service. This is a service we expect to be set up by self-regulatory organizations (SROs) which might be sector specific. The contract will define data sets being shared, the terms of sharing the data sets, the frequency and duration of data sharing, and whether TDPs expect a payment, and security and privacy requirements.   The contract service is fully transparent so all contracts are recorded in a verifiable tamper proof ledger. -- The second building block of DEPA for Training is a Confidential Clean Room (CCR).   A Confidential Clean Room is a secure blackbox environment where data sets from multiple TDPs can be processed.   The AI model a TDC wishes to train can be trained in this CCR. In this framework, the TDPs never actually share their data sets directly with the TDCs. Only encrypted data sets are released to these Confidential Clean Rooms which are safe and secure environments. Most importantly TDCs never get access to the raw data and once the model has been trained, the clean room environment can be taken down.  -- The final building block of DEPA for Training is called Differential Privacy. If you train models on private data, there is a possibility that we can learn a lot about a certain set of individuals, just by looking at the data set.   To avoid this, and to ensure privacy is protected, DEPA for Training adopts Differential Privacy. Here, we can train models in a way that the receiver of the model cannot tell if any specific individual’s data was included in Training.   This ensures that the model can still learn broad patterns, like whether a specific group of people are more likely to suffer from a disease or not but the models cannot retain information that is too specific to individuals which could cause a privacy breach. https://lnkd.in/gWuK-xeu

Interested in knowing about DEPA and Responsible AI? The full Open House Session #1 explainer is here: https://lnkd.in/duNuUcXW

We are excited to announce that Sharad Sharma, Founder of iSPIRT Foundation, will be delivering a keynote on "AI Opportunities for Entrepreneurs in India" at InnovAI 2024! 🎉 Gain insights from one of the most influential leaders in the tech industry. 🌟 📅 Date: June 22, 2024 🕘 Time: 9:00 AM to 5:00 PM 📍 Venue: Auditorium, IIM Bangalore Don't miss this chance to learn, network, and be inspired by the future of AI. Sharad Sharma | ProductNation/iSPIRT | #InnovAI2024 #AIInnovation #IIMB #AIEntrepreneurship #AIEvent #TechConference