Kush Varshney

In this discussion, Kate Soule, Director at Granite, and Kush Varshney, IBM Fellow in AI Governance, dive into the future of open-source AI models. They talk about the latest DeepSeek-V3-0324 release and its implications for model evaluation beyond traditional benchmarks. The conversation shifts to Google's innovative Gemini Canvas and 2.5 feature, enhancing real-time coding experiences. They also explore the rising trends in AI image generation with OpenAI's GPT-4o, analyzing its cultural impact and ethical considerations.

Shobhit Varshney, Head of Data and AI for the Americas, Chris Hay, CTO of Customer Transformation, and Kush Varshney, an IBM fellow on AI governance, come together for a thrilling discussion. They dive into the buzz from LlamaCon and the implications of new AI models like Qwen3 and the rumored DeepSeek-R2. The trio also examines J.P. Morgan's urgent open letter on AI security, raising concerns about the balance between innovation and safety. Join them as they reflect on the past year’s AI journey and key moments from their debut conversation!

Marina Danilevsky, an AI development expert, joins seasoned analyst Kush Varshney and stock market guru Shobhit Varshney in a riveting discussion. They tackle whether we’re in an AI bubble and its connection to recent market crashes. The trio dives into OpenAI's Structured Outputs and their transformative potential for enterprise applications. They also dissect Google's intriguing move to 'acquire' character.ai, pondering the implications for the tech landscape and startup culture. It's a compelling exploration of tech innovation and economic shifts!

Host Bruke Kifle interviews Kush Varshney, a distinguished research scientist at IBM Research. They discuss responsible AI, operationalizing RAI principles, risks of generative AI, and coordinating AI safety. Kush also shares insights from his book 'Trustworthy Machine Learning' and his work with IBM's Science for Social Good initiative.

Join a stellar panel featuring Raid Ghani from Carnegie Mellon, Solon Barrokas of Cornell and Microsoft, IBM's Kush Varshney, startup CEO Alyssa Labgenova, and Harvard's Hima Lakaraju. They tackle pressing issues in the realm of model explainability. Discussions dive into stakeholder-driven approaches, counterfactual explanations, and the impact of legal frameworks on automated decision-making. The experts also highlight vulnerabilities in AI explanations and the critical need for trust and fairness, emphasizing collaboration to enhance understanding and improve outcomes.