AI Models Can Hallucinate Or Misfire

RTIFICIAL Intelligence (AI) offers immense potential, but it's not without challenges. Mohit Saxena, Co-Founder & CTO, InMobi & Glance told TNIE that there's the critical need for human oversight and that AI models can hallucinate or misfire, and in today's sensitive digital climate, ensuring responsible output is essential.

- MA KANNAN @Bengaluru

"We're investing in rigorous moderation infrastructure and developing new governance frameworks to mitigate these risks," he said.

He added that deep AI expertise is scarce. "While surface-level applications like RAG (Retrieval-Augmented Generation) are becoming common, true innovation requires depth in data science, ML infrastructure, and systems thinking—talent that's still hard to find."

But our global presence in Bengaluru, San Francisco, and the UK gives us broader access to specialized talent pools, the co-founder said.

Talking about other key challenges, he said that AI infrastructure is expensive. Running advanced models at scale demands significant compute and energy. "Our approach is rooted in frugality—we optimize model usage, leverage pre-processing, explore alternatives like TPUs (Tensor Processing Unit), and work closely with partners like Google to get the most out of every dollar," he said.