India's digital businesses are innovating faster with Data + AI, says Databricks founder
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India's digital-native businesses are artificial intelligence (AI)-hungry and ahead of the curve from global peers when it comes to innovation with data and AI , said Ali Ghodsi, founder and chief executive of Databricks 'India's great because when the rest of the world is talking about recession, India is on the upswing. And in the last decade, they've built a lot of digital infrastructure in India, which is a game-changer. India's ahead on digital infrastructure compared to most other countries in the world,' Ghodsi said while addressing the media at the Databricks Data + AI Summit in San Francisco on Wednesday.The Silicon Valley's data and AI company Databricks recently committed a $250 million investment in India over the next three years towards local R&D, talent development, and enterprise adoption of AI."We're doubling down on Bangalore. We hired a huge engineering team. We target the IITs," he said, mentioning an instance where the company received 700 applications from IIT graduates for just four open positions in Bangalore.Ghodsi said that the company is extremely bullish on Asian markets, including India, South Korea, Australia and New Zealand, which are moving faster than the rest of the world on AI because of the relaxed regulatory environment.'We're investing ahead of the game there. We're not just looking at how much revenue we get? Is the ROI there? Instead. We're saying, let's put even more there than the numbers justify, because we're so bullish on what's happening in Asia,' he said.At the annual conference on Wednesday, Databricks made a slew of bold announcements challenging traditional players in database management, AI apps and agents. Here's a rundown of key announcements:Taking a fresh approach to agentic AI, Databricks is focusing on the quality and cost of productising agents with 'Agent Bricks', an offering that directly challenges Salesforce's Agent Force and Google's Agent Space.'There are a lot of challenges in the industry around building agents. We can't evaluate the quality of the agents. We don't know how these agents are doing in production,' Ghodsi said, adding that there are no evaluations or benchmarks for judging the performance of agents.Hence, Databricks is introducing LLM judges for automated evaluations. Agent Bricks' auto optimisation techniques, such as knowledge extraction and multi-agent supervisor can refine the agent for the best quality output, sometimes at 10 times lower cost.Challenging the traditional database platforms like Oracle Database, MySQL, Microsoft SQL Server, and PostgreSQL, Databricks announced Lakebase, a first-of-its-kind fully-managed Postgres database built for AI.'We think that's going to disrupt the existing database market, which has really not changed much in 40 years. But I think now is the time where it's actually under a lot of pressure with agents coming in,' Ghodsi said, adding that the company is targeting a $100 billion total addressable market with Lakebase.Databricks, last month, announced the acquisition of Neon, a leading serverless Postgres company, which showed that over 30% of the databases at Neon were actually created by agents, not by database administrators. 'So next year, it's probably 99% plus.'Therefore, in the new AI era, enterprises need different types of databases where compute and storage are completely separated, he explained. 'You just store the database on very cheap cloud storage in an open format so you're not locked into anyone (single vendor).'Over 300 Databricks customers are already using Lakebase, and this transition is going to be the most important marathon for the next five years, he said.To close the AI talent gap, Databricks also announced the free edition of its platform, along with a $100 million global investment in data and AI education. This initiative gives students, professionals, and institutions free access to Databricks tools and training.Among other notable announcements made was the Lakeflow Designer, a new no-code capability that lets non-technical users create data pipelines using a visual drag-and-drop interface and a natural language GenAI assistant.(The reporter was in San Francisco at the invitation of Databricks)
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