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Hi AI Futurists,
Google Finance is rolling out a Deep Search tool powered by Gemini AI, enabling traders to run complex, cited financial analyses directly in the app. The platform now integrates prediction market data from Kalshi and Polymarket, extending its AI ecosystem beyond traditional stock tracking. Let’s take a look.
Here’s our agenda.
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Top AI news
Google’s AI Finance Push
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AI in the wild
Best,
Lex Sokolin
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Ecosystem: AI Venture Fund | Fintech Research | Lex Linkedin / Twitter
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Top AI news
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Google’s AI Finance Push
Google Finance is joining Google’s wider push to infuse AI into all its products with a new feature called Deep Search, built on the company’s Gemini AI models. The tool will allow users to ask complex financial questions and receive fully cited, comprehensive responses within minutes. Robert Dunnette, Google’s director of product management, said Deep Search also presents a “research plan” so users can follow the AI’s reasoning — a step toward making the system more transparent and interactive.
The feature will roll out to U.S. users in the coming weeks, with early access available through Google Labs. Deep Search comes with usage tiers, giving AI Pro and AI Ultra subscribers higher limits. Alongside this, Google Finance is adding prediction market data from platforms like Kalshi and Polymarket, allowing users to see market odds on future events such as GDP growth directly within the search interface. As Dunnette put it, the goal is to “harness the wisdom of the crowds” and make financial forecasting more accessible.
The AI-powered Google Finance will also launch in India this week, supporting English and Hindi, though without the newest features yet. Beneath the product updates lies a larger question about how far AI can go in democratizing financial insight. As the line between human analysis and machine reasoning blurs, the edge may belong not to those who have more data—but to those who know how to ask smarter questions.
Takeaways at a Glance:
Deep Search uses Gemini AI for comprehensive, cited responses.
A research plan view shows the model’s reasoning steps.
Early access via Google Labs; tiered limits for AI Pro and Ultra.
Integration with Kalshi and Polymarket for prediction data.
Expansion to India with bilingual support (English/Hindi).
What We Think About It:
Google is positioning Gemini as a research engine, not just a chatbot. Deep Search could quietly redefine how retail investors and analysts interpret financial data. The prediction market integration hints at a hybrid model—combining machine inference with human collective judgment.
What You Can Do Right Now:
Try Deep Search in Google Labs – You don’t need to be a trader to explore it. Use it to ask bigger, more specific financial questions like “What industries might benefit from rising interest rates?” or “How do prediction markets view next quarter’s GDP?”
Compare AI answers with your own judgment – Treat it like a co-pilot, not a crystal ball. Ask yourself how its reasoning compares to your own or what you might be missing.
Use this as an investing literacy tool – Even if you never trade, Deep Search can help you understand financial trends, company performance, and macroeconomic ideas more intuitively.
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