From Lab to Market: Accelerating Technology Transfer with Gemini 3 & Deep Research

The journey from a raw idea to a market-ready product is known as the "Valley of Death." Most innovations die here, not because the science is flawed, but because the path to commercialization is too complex, expensive, and exhausting.

In this session, we will walk in the shoes of a researcher-entrepreneur trying to bring a "Hard Tech" innovation to life. Through personal testimony and live analysis, I will demonstrate how the new Gemini 3 ecosystem serves as an intelligent assistant for scientists and engineers, moving an idea from a lab notebook to an MVP in record time. Unlike the "Chat" era, Gemini’s agentic capabilities allow us to execute complex, multi-step workflows.

We will move beyond basic prompting to explore the full innovative toolkit:
• The Librarian (NotebookLM & Google Scholar): We will build a trusted "Neural Knowledge Base" by ingesting complex academic papers to identify research gaps, generating instant literature reviews with citations, and turning information overload into clear insights.
• The Strategist (Gemini 3.0 Pro): We will use advanced reasoning to "stress test" our business model and simulate investor criticism before we even pitch.
• The Builder (Google AI Studio): A live demonstration of rapid prototyping. We will build a custom "Patent Examiner Agent" to draft defensible IP claims and generate a physical simulation of an industrial process (Proof of Concept) to validate our engineering logic.
• The Automator (Gemini CLI): I will share practical "hacks" using the Command Line Interface to process bulk research papers and data, saving weeks of manual review.

Expect a fast-paced mix of strategic analysis, technical demonstrations, and actionable hacks. Whether you are a developer, researcher, or founder, you will leave with a blueprint for using Google’s AI stack to turn raw ideas into protected products.

Stop Shipping 'Vibes': A 9-Step Framework to Measure AI powered Apps Maturity

In the GenAI era, creating a "wow" moment is dangerously easy. You paste a prompt into a playground, get a perfect result, and think you have a product. You don't. You have a "Works on My Machine" demo (TRL 3) that will inevitably fail in the real world due to unmeasured hallucinations, latency spikes, and edge cases.

To bridge this gap, we need engineering discipline, not just better prompts. In this practical 15-minute session, I introduce the Technology Readiness Level (TRL) framework—originally designed by NASA—adapted specifically for GenAI software . We will map the exact engineering steps required to move from TRL 3 (The Playground) through the "Valley of Death" (Evaluations & RAG) to TRL 9 (Mission Critical).

You will leave with a concrete diagnostic toolkit to audit your AI projects. Instead of guessing based on "vibes," you will have a clear roadmap to communicate maturity to stakeholders, ensuring you stop shipping fragile demos and start deploying battle-tested software.

Time, Audience & Key Takeaways
In just 15 focused minutes, this session delivers a diagnostic toolkit designed for developers, CTOs, and startup founders. You should attend if you are tired of vague milestones like "it feels ready." You will walk away with a concrete framework to audit your AI projects, giving you the vocabulary to explain to stakeholders why a "cool demo" isn't a product yet. Stop guessing your maturity level and start measuring it.