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intelligraf by Ascalonic
- 2. The Problem • A.I. (Artificial Intelligence) is becoming a crucial part of business • Currently Cloud services such as Google Cloud and Amazon Web Services (AWS) are being used • What’s the problem with these services? PRIVACY
- 3. Privacy – Ease Trade-off Privacy Ease of Use Eg: Google Compute Engine Eg: Google AutoML
- 4. Our Solution • Integrate A.I. and BlockchainTechnology • Decentralize Machine Learning
- 5. How it works? : MODEL - A Stakeholders User Miner Us
- 6. How it works? : MODEL - A Train request
- 7. How it works? : MODEL - A
- 8. How it works? : MODEL - A
- 9. How it works? : MODEL - A notification
- 10. How it works? : MODEL - A Problem definition
- 11. How it works? : MODEL - A
- 12. How it works? : MODEL - A i) PUBLIC MODEL
- 13. How it works? : MODEL - A ii) PRIVATE MODEL
- 14. Advanced Models/Features • Apply Federated Learning – keep the data in the devices itself and train the model using the device • Apply Meta-Learning techniques to make the system adapt to the problem with few dataset • Trained Model Marketplace and subscription
- 15. Competition
- 16. How intelligraf stands out? • Decentralized Platform – extremely scalable and reliable • Put idle computing power to good use and make real money • Specifically designed and developed for Machine Learning only • Ease of use without compromising privacy
- 17. Marketing • Provide Deep Learning Workshops across colleges introducing/using intelligraf • Introduce to the existing cryptocurrency miners as a way to make ‘real’ money • Provide Low cost service to students and Deep Learning Researchers • Host a website to download and share Deep Learning Models
- 18. Budget and Roadmap • Company Registration : 20,000/- • .com Domain : 600/- • Cloud Back-End : 1,700/- per month • Release first prototype (1 month) (with Model A) (Cost 0/-) • Release second prototype (2 months) (with Federated Learning) (Cost 0/-) • Release MVP (2 months) (Cost 24,000/-)
- 19. Pricing • How much should a miner get? 𝑝 = 𝑣. 𝑡 𝑒𝑥𝑝 𝑡 𝑜𝑏𝑠 • v : Cost for training the model in mid range GPU(t*0.028 ₹) • tobs:Time taken to complete training by the miner • texp:Time taken to train in mid range GPU
- 20. Pricing • How much the user should spend? • 102% of miner’s charge (if adding to private chain) • Free of cost if adding to public blockchain • Typical classification task : 0.45 ₹ • Subscription of the public blockchain : 200₹ per month
- 21. Conclusion • Decentralized Machine Learning offers more data protection and privacy • Its demand will grow exponentially over the next 4 years (CAGR : 65.2%) • The MVP can raise minimum of 125% of initial investment within 2 months if it hits 171 subscribers with the subscription plan alone • Upon integrating meta-learning it will rival giants like Google Cloud, AWS etc and anybody with any background can integrate machine learning into their business