Rotem Pinchover
Head of AI at definity
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Rotem is the Head of AI at definity, where she leads the development of innovative AI solutions to reinvent data engineering and observability. Previously, she served as a Senior AI Scientist at Intuit, specializing in building large-scale processes that support customers and deliver measurable business results. Her expertise spans agentic AI, generative AI, and classic ML.
Rotem holds both an M.Sc. and a B.Sc. in Industrial Engineering from Tel Aviv University. A dedicated advocate for women’s empowerment in the tech industry, she also serves as the Israeli Ambassador for Women in Data Science (WiDS).
Who Wants to Be an AI Practitioner? The Million-Token Gameshow
Welcome to the Reversim ultimate tech reality check game: "Production Drop or AI Flop?"
In this fast-paced interactive lightning session, a live gameshow is coming straight to the crowd. Get ready to answer the ultimate question: Are these genuine engineering wins, or just incredibly expensive architectural illusions?
The Generative AI gold rush has turned engineering ecosystems into a high-stakes guessing game. Driven by relentless industry FOMO, developers are treating basic API wrappers like architectural triumphs, PMs are shipping features based entirely on hype metrics, and Data Scientists have traded rigorous statistical validation for the chaotic dopamine rush of prompt engineering. The industry has become so blinded by the shiny brilliance of LLMs that deterministic bounds have been completely traded away for probabilistic, "vibes-based" outcomes.
No marketing fluff, no boring slides—just a brutal, hilarious, and deeply necessary intervention for a room full of builders.
How I Left the Corporate to Vibe-Code an AI Startup (And Built a Prompt-Engineered Nightmare)
Entering a startup as the first AI builder after years in the corporate world is a whirlwind. No data? No problem, Claude to the rescue.
It felt like a superpower, until I had to sit down with our lead developer and try to explain the sprawling, hyper-complex prompt-and-code hybrid I had just built.
In this talk, I’ll take you inside the chaos of the "vibe coding" loop and the culture shock of trading enterprise guardrails for pure startup speed. You'll walk away with a practical look at the prototyping traps that build instant architectural debt, and real-world strategies for keeping your AI code lean, explainable, and production-ready when building from zero.
GenAI in the Wild: Protecting Your Herd from Predators
The adoption of GenAI for various use cases is on the rise, with its power exponentially increasing with each new implementation. However, this power is also a magnet for attackers who look to exploit vulnerabilities. This makes the need for GenAI security more critical than ever before. Our talk will provide an overview of GenAI attacks and explain why GenAI needs to be secured.
We will delve into various use cases and discuss the complexity of fitting detectors to each unique case. The number of use cases is constantly growing, evolving and they are not well defined, posing a significant challenge in terms of detecting malicious activity. We will also present a scalability demonstration, showcasing the sheer numbers of use cases and threats that need to be addressed.
We will then introduce GenOS and GenSRF's general structure, which will highlight the challenges we've encountered, including managing use case-detector fit, balancing FP/specificity of detectors and contending with the large variation in types of data and formats. Furthermore, we'll discuss the lack of labeled data, leading to difficulties in evaluating detector real-world performance and monitoring as well as the ambiguity around trusted/untrusted inputs.
Lastly, we will explain why this is still an unexplored and misunderstood domain, requiring us to pave the way and invent the wheel to defend against new types of attacks that we must design ourselves. Join us as we unravel the complexities of securing GenAI and discuss our efforts to stay one step ahead of the hackers.
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