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Srikanth Velamakanni
Co-founder and Group Chief Executive
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Can you list some interesting client stories?
Certainly! Here are a few interesting client stories that highlight the impact of AI and analytics:
- 1. Novartis: We were on the verge of signing a multi-million-dollar deal with Novartis, a pharmaceutical company, to provide analytics solutions. However, due to a challenging situation at Fractal, they initially decided not to work with us 3.1. But, through our efforts to explain the situation and showcase our capabilities, we were able to regain their trust and eventually secure the partnership.
- 2. Bloomingdale's: We had signed an important project with Bloomingdale's, a renowned retail brand. Unfortunately, the project was canceled due to the challenging circumstances we faced 3.1. Despite this setback, we continued to work hard and build strong relationships with clients.
- 3. ICICI Bank: In the early days of Fractal, we took on a pro bono project for ICICI Bank, a leading Indian bank, to build credit scoring models 2.1. This project helped us gain expertise in consumer lending and risk, and paved the way for serving major private and foreign banks in India.
- 4. Fortune 500 Companies: Fractal has been providing AI solutions to several Fortune 500 companies. Our focus on serving large enterprises has been a key aspect of our business strategy 1.1. By understanding the needs of these companies and investing in their success, we have been able to build long-term partnerships.
These client stories demonstrate our commitment to understanding client needs, overcoming challenges, and delivering value through AI and analytics. Each story showcases the importance of client-centricity and the impact it can have on building successful relationships and driving business growth.
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Can you distill Srikanth's wisdom into the top 10 teachable points of view?
Certainly! Here are the top 10 teachable points of view that encapsulate Srikanth Velamakanni's wisdom:
- 1. Think Bigger & Bolder: Srikanth emphasizes the importance of thinking beyond conventional boundaries and pushing the limits of what is possible.
- 2. Embrace Failure: Srikanth believes that failures provide valuable lessons and opportunities for growth.
- 3. Continuous Learning: Srikanth considers himself a lifelong student and encourages others to embrace learning in various disciplines, including mathematics, economics, neuroscience, and consumer behavior.
- 4. Time Management: Srikanth advises using time effectively rather than just efficiently, and encourages avoiding back-to-back engagements to allow for idle time and creative thinking.
- Importance of Company Culture: Srikanth highlights the significance of understanding company culture before joining a job to avoid potential regrets.
- Embrace AI and ML: Srikanth advocates for embracing AI and ML technologies rather than fearing them, and focusing on their positive outcomes.
- Surround Yourself with Support: Srikanth emphasizes the importance of having friends and family by your side when starting a business.
- Financial Preparedness: Srikanth advises entrepreneurs to have 18-24 months of surplus cash and not to expect immediate monetary returns from their business.
- Client-Centricity: Srikanth believes in the importance of understanding and meeting client needs, and building long-term partnerships with clients.
- Diversity and Inclusion: Srikanth recognizes the value of diversity and inclusion in building a successful organization and serving all stakeholders.
These teachable points of view reflect Srikanth's insights and experiences as an entrepreneur and leader in the field of AI. They provide valuable guidance for individuals and organizations looking to navigate the challenges and opportunities in the AI landscape.
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What are three equations of AI that you often talk about? Can you elaborate them so that someone new to AI can understand?
Certainly! There are three equations that I often discuss when it comes to AI. Let me explain them in a way that is easy to understand:
- The first equation is about reducing errors in AI algorithms. It states that the error in AI systems decreases as we have more data, increased computing power, and improved techniques 1.1. In simpler terms, when we have more data to train AI models, better hardware to process that data, and advanced techniques, the accuracy and performance of AI systems improve.
- The second equation emphasizes the importance of smart algorithms, engineering, and design in achieving successful AI outcomes 1.2. While algorithms play a crucial role in AI, it is equally important to have strong engineering practices and good design principles. This equation highlights that AI results are proportional to smart algorithms, great engineering, and good design.
- The third equation focuses on organizational effectiveness in driving AI success 1.3. It states that the effectiveness of an organization in leveraging AI is determined by the combination of talent, culture, and governance. In other words, having the right people, fostering a supportive culture, and implementing effective governance structures are key factors in achieving AI-driven results.
TThese equations provide a framework for understanding the key elements that contribute to successful AI implementation. By considering data, compute power, techniques, algorithms, engineering, design, organizational effectiveness, and more, we can harness the power of AI to drive positive outcomes in various industries.
Do it the Old Way
The old, hard way is to go through my talks, interviews, and articles, while having to identify & ignore redundancies and then synthesize everything.
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