Research in AI, human-robot interaction, autonomous vehicles, and machine learning at MIT.

Lex Fridman

The power of AI agents comes from:
1. intelligence of the underlying model
2. how much access you give it to all your data
3. how much freedom & power you give it to act on your behalf

I think for 2 & 3, security is the biggest problem. And very soon, if not already, security will become the bottleneck for effectiveness and usefulness of AI agents as a whole (1-3), since intelligence is still rapidly scaling and is no-longer an obvious bottleneck for many use-cases.

The more data & control you give to the AI agent: (A) the more it can help you AND (B) the more it can hurt you.

A lot of tech-savvy folks are in yolo mode right now and optimizing for the former (A - usefulness) over the the latter (B - pain of cyber attacks, leaked data, etc).

I think solving the AI agent security problem is the big blocker for broad adoption. And of course, this is a specific near-term instance of the broader AI safety problem.

All that said, this is a super exciting time to be alive for developers. I constantly have agent loops running on programming & non-programming tasks. I'm actively using Claude Code, Codex, Cursor, and very carefully experimenting with OpenClaw. The only down-side is lack of sleep, and an anxious feeling that everyone feels of always being behind of latest state-of-the-art. But other than that, I'm walking around with a big smile on my face, loving life 🔥❤️

PS: By the way, if your intuition about any of the above is different, please lay out your thoughts on it. And if there are cool projects/approaches I should check out, let me know. I'm in full explore/experiment mode.

IONOS

Security and Compliance Engineer

Werkstudent (Information Security Analyst)

Brandenburg University of Technology

Research Thesis Title: Comparative Analysis of Anomaly Detection in Ultrasonic Wireless Sensor Networks, using BigQuery ML

Internship Topic: A Review of the Multi-Standards Compliance Framework

Master of Science (M.Sc.) in Cyber Security

- Return Oriented Programming (ROP)
- Machine Learning, Deep Learning
- Supervised and Unsupervised Clustering Analysis
- Embedded System Security

Research Scientist

KPMG Malaysia

Assistant Manager, Information Protection and Business Resilience (Cyber Security)

Senior Associate, Information Protection and Business Resilience (Cyber Security)

Aegis Malaysia

IT Security and Compliance Specialist

IT Security, Compliance Analyst

Coming from an academic IT Networking background with a considerable years of experience in InfoSec areas to define, educate, design and implement the latest IT security baselines for organizations. Practical years of experience in IT Security standards (PCI-DSS, OWASP, ISAE, Security Management alongside with ISO 27001 27002, IT-Grundschutz, GDPR). Practical experience in NLP, machine learning and AI. 

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