​AI failures can collapse businesses, drain millions, and break customer trust. Many of these failures stem from poor evaluation methods, inadequate testing, and a lack of performance visibility. In this session, we’ll explore real-world AI failures, the pitfalls of traditional evaluation techniques, and how smart AI evaluations can mitigate risks, improve performance, and ensure success for your business.

​💡What you’ll learn

• ​Why AI failures happen and their financial impact

• ​Limitations of traditional evaluation methods

• ​Case studies and successful evaluation strategies

• ​Practical insights to future-proof your AI systems

​About the Speaker

​Rishav Hada, an Applied Scientist at Future AGI, specializes in AI evaluation and observability. Previously at Microsoft Research, he developed frameworks for generative AI evaluation and multilingual language technologies. His research, funded by Twitter and Meta, has been published in top conferences like EMNLP, ACL, and NAACL and integrated into AI products. His recent work on mitigating bias in language technologies won the Best Paper Award at FAccT’24.

​To know more about Rishav, visit his LinkedIn profile

​About Future AGI

​Future AGI is an advanced AI Lifecycle Management platform designed to streamline experimentation, evaluation, and real-time observability. Traditional AI tools often rely on guesswork due to gaps in data generation, error analysis, and feedback loops. Future AGI eliminates this uncertainty by automating the data layer with multi-modal evaluations, agent optimizers, and synthetic data tools—cutting AI development time by up to 95%. By removing manual overhead, it brings software engineering rigor to AI, enabling teams to build high-performing, trustworthy systems—faster.

​To know more about Future AGI, visit here

​Other Required Details

​📅Date: 11th March, 2025, Tuesday

​⌚Mode & Time: Online at 9:30 A.M. PDT

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​REGISTER NOW!

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