'AI models can hallucinate or misfire'
Artificial 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.
'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 specialised 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.
InMobi views AI not just as a tool, but as a foundational shift and its roadmap over the next one to three years is anchored in three key areas. 'First, we are reimagining engineering productivity with AI—helping experienced engineers scale faster and empowering fresh talent to leapfrog traditional learning curves. AI is now embedded into every aspect of how we build—whether it's writing code, improving observability, or boosting efficiency,' he said.
'Second, we are building intelligent automation into our core business processes—moving from simple scripting to AI agents that can deconstruct complex workflows, predict outcomes, and take action. This isn't just automation; it's autonomous decision-making at scale. Third, we're embracing the rise of agentic architecture—where agents talk to agents, not APIs (Application Programming Interface), to get work done. This is the future of system communication, and are actively developing for it,' he further said.
InMobi is setting up a dedicated unit to track and accelerate engineering efficiency with AI, with a goal to complete most of the foundational work by year-end. The company is leveraging AI to generate high-impact formats—ranging from image-based ads to audio creatives—enabling brands to engage users across multiple touchpoints. It also uses AI to generate and summarize content at scale.
In the visual content space, he said the company is leveraging Contrastive Language-Image Pre-training (CLIP) to bridge the gap between AI-generated creativity and real-world commerce through its Glance AI product. 'By using CLIP, we're able to understand and interpret AI-generated fashion looks—essentially decoding the visual style and identifying apparel elements within the image. These elements are then matched to real products from our extensive catalogue of brand and retail partners,' he explained.
Even before the LLM (large language model) wave, the company has been leveraging AI for content generation at Glance. 'We're onboarding fresh engineering talent through structured bootcamps where AI adoption starts from day one—including access to AI assistants and hands-on experience with applied ML tools. Simultaneously, we're deepening our bench strength by hiring top-tier data scientists—we've onboarded over 50 employees in the past year alone, across domains like LLMs, DNNs (Deep Neural Networks), and imaging. We're also shifting our hiring lens—prioritising engineers with a strong aptitude in data science and statistical thinking. Our aim is that 80% of our workforce, both new and existing, to be highly AI- and ML-savvy in the next 1–2 years,' the co-founder and CTO informed.
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