Build a Product that your users can't live without it Says Sriram Natarajan.
Meet Sriram, a TEDx Speaker, Former Engineering Lead at Google, and now building Yuni , a GenAI Startup, Ph.D. in Computer Science from the University of Massachusetts Amherst | Research, and LEAD from Stanford University Graduate School of Business.
It was such a great opportunity to learn about OpenAI, LLM models and building AI products from Sriram.
He presented a case study on predicting a final exam score using AI, covering everything from prototype design and pilot testing to production with Llama 3.1.
We discussed the policies, guradrails and the billions of parameters required to build AI models, and how domain-specific datasets are essential for developing AI products.
Even though I don't have an engineering background, I was able to understand the design concepts you talked about at the event.
Sriram also explained some challenges in AI, such as predicting simple math problems, where AI incorrectly predicted 9.11 as greater than 9.9.
There's still a lot to improve in AI. However, AI is the next big reality, and it will be exciting to see how it evolves in the coming years.
I really liked your answer about monetizing AI products.
You explained it well with an example: Two years ago, hardly anyone used ChatGPT, but now if you ask people, many would be willing to pay if the free usage stopped. So, the key is to create a product that your users love and encourage users to pay for them.
As you all know, Bangalore is an IT city, and our software engineers had many questions about building great AI products.
If you're building AI products and seeking expert guidance, connect with Sriram Natarajan.
I sincerely thank Sriram for coming and making the event great.
Key Takeaways from the Recent Event with Sriram Natrajan:
✅ Understanding the complexity of AI development and the importance of robust datasets in building effective AI products.
✅ Insights into overcoming AI challenges, such as improving accuracy in simple tasks, highlighting the ongoing need for AI refinement.
✅ Strategies for creating product dependency and effective monetization, ensuring users see the indispensable value in AI solutions.
✅ Networking with industry leaders and gaining valuable perspectives on fostering innovation and collaboration within multidisciplinary teams.
A special thanks to eChai Ventures, Draper Startup House , Mansi Baheti, and Jatin Chaudhary for organizing such an insightful event.
P.S: Follow Bhavik Gupta and Startups Manch for startup ideas and exploring opportunities.
Meet Sriram, a TEDx Speaker, Former Engineering Lead at Google, and now building Yuni , a GenAI Startup, Ph.D. in Computer Science from the University of Massachusetts Amherst | Research, and LEAD from Stanford University Graduate School of Business.
It was such a great opportunity to learn about OpenAI, LLM models and building AI products from Sriram.
He presented a case study on predicting a final exam score using AI, covering everything from prototype design and pilot testing to production with Llama 3.1.
We discussed the policies, guradrails and the billions of parameters required to build AI models, and how domain-specific datasets are essential for developing AI products.
Even though I don't have an engineering background, I was able to understand the design concepts you talked about at the event.
Sriram also explained some challenges in AI, such as predicting simple math problems, where AI incorrectly predicted 9.11 as greater than 9.9.
There's still a lot to improve in AI. However, AI is the next big reality, and it will be exciting to see how it evolves in the coming years.
I really liked your answer about monetizing AI products.
You explained it well with an example: Two years ago, hardly anyone used ChatGPT, but now if you ask people, many would be willing to pay if the free usage stopped. So, the key is to create a product that your users love and encourage users to pay for them.
As you all know, Bangalore is an IT city, and our software engineers had many questions about building great AI products.
If you're building AI products and seeking expert guidance, connect with Sriram Natarajan.
I sincerely thank Sriram for coming and making the event great.
Key Takeaways from the Recent Event with Sriram Natrajan:
✅ Understanding the complexity of AI development and the importance of robust datasets in building effective AI products.
✅ Insights into overcoming AI challenges, such as improving accuracy in simple tasks, highlighting the ongoing need for AI refinement.
✅ Strategies for creating product dependency and effective monetization, ensuring users see the indispensable value in AI solutions.
✅ Networking with industry leaders and gaining valuable perspectives on fostering innovation and collaboration within multidisciplinary teams.
A special thanks to eChai Ventures, Draper Startup House , Mansi Baheti, and Jatin Chaudhary for organizing such an insightful event.
P.S: Follow Bhavik Gupta and Startups Manch for startup ideas and exploring opportunities.
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