Building trust and security in AI

Are AI systems really safe?
How can we build trust in a world where AI is everywhere?
What are the best ways to protect sensitive data while still driving innovation?

Do you find yourself grappling with these questions? If so, don’t miss our next AI Talks event:

𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐭𝐫𝐮𝐬𝐭 𝐚𝐧𝐝 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐢𝐧 𝐀𝐈

Join us for an evening of insightful discussions with leading experts as we explore the critical challenges of AI, trust, and security. Discover practical strategies to secure generative AI, protect open-source software, and strike the right balance between privacy and progress in AI.

📅 Date: March 12th 2025
🕕 Time: Doors open at 6:00 PM
📍 Location: Cantersteen 47, Central Gate, 1000 Brussels

Important to know:
To attend, please make sure to fill out the registration form on the page. Completing this form is necessary to secure your spot at the event!

𝐓𝐚𝐥𝐤 #𝟏: 𝐒𝐞𝐜𝐮𝐫𝐢𝐧𝐠 𝐆𝐞𝐧𝐀𝐈 - 𝐆𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬 𝐚𝐠𝐚𝐢𝐧𝐬𝐭 𝐞𝐦𝐞𝐫𝐠𝐢𝐧𝐠 𝐭𝐡𝐫𝐞𝐚𝐭𝐬

Agentic AI is on the rise, powered by the immense capabilities of LLMs. But along with new opportunities come fresh challenges. In this session, we uncover how hallucinations can derail workflow autonomy, why prompt injections pose a growing threat when impactful actions are being taken, and how the sheer breadth of the input-output space makes it tough to cover every edge case. We then share hands-on strategies to keep your AI initiatives secure and resilient. Join us to discuss how we can stay one step ahead in this rapidly evolving landscape.

By Thomas Vissers & Tim Van Hamme (Blue41, KU Leuven)

𝐓𝐚𝐥𝐤 #𝟐: 𝐀𝐈-𝐝𝐫𝐢𝐯𝐞𝐧 𝐟𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠: 𝐇𝐨𝐰 𝐋𝐋𝐌𝐬 𝐜𝐮𝐭 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐟𝐚𝐥𝐬𝐞 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐥𝐚𝐫𝐦𝐬

Static Application Security Testing (SAST) is a vital approach for identifying potential vulnerabilities in source code. Typically, SAST tools rely on predefined rules to detect risky patterns, which can produce many alerts. Unfortunately, a significant number of these alerts are false positives, placing an excessive burden on developers who must distinguish genuine threats from irrelevant warnings. Large Language Models (LLMs), with their advanced contextual understanding, can effectively address this challenge by filtering out false positives. By reducing the number of alarms, developers are more willing to take action and actually solve the real vulnerabilities.

By Berg Severens (AI Specialist at Aikido)

𝐓𝐚𝐥𝐤 #𝟑: 𝐀𝐭 𝐭𝐡𝐞 𝐨𝐭𝐡𝐞𝐫 𝐬𝐢𝐝𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐬𝐩𝐞𝐜𝐭𝐫𝐮𝐦: 𝐬𝐦𝐨𝐥 (𝐯𝐢𝐬𝐢𝐨𝐧) 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 𝐢𝐧 𝟐𝟎𝟐𝟓

Large language models have grown to ever larger sizes, but there’s another interesting development at the other side of the spectrum: small language models (SLMs) that can be self-hosted, which can be a great option for data privacy and protection. In this talk, we’ll briefly discuss what small language models are capable, the tooling around them, and how you can use them to balance innovation with privacy and security in your GenAI projects.

By Laurent Sorber (CTO and Co-founder at Superlinear) & Niels Rogge (Machine Learning Engineer at Hugging Face)

Why join us?

At the AI Talks by Superlinear, you’ll…

• Network with top AI professionals from Belgium
• Dive into practical AI applications shaping industries
• Enjoy great finger food, drinks, and inspiring conversations

Want to be part of this unique event? Be sure to fill out the form on the event page to secure your spot!