mpyllan

Machine Learning. Cryptography. CTO @

[Wodan AI @wodan_secure_ai]

The final short video by Robbe Van Roey and @BobTheBuilderAI!
▶ Homomorphic encryption represents a significant advancement in data security, enabling computations on encrypted data without the need to decrypt it first.
#WodanAI #CyberSecurity #AI #Encryption #AISecurity

[Wodan AI @wodan_secure_ai]

I'm excited to announce that @GoogleStartups has chosen Wodan AI, to join Growth Academy: AI for Cybersecurity. With the help of this program, our business has a fantastic potential for growing significantly and continuing its contribution to the sector. https://t.co/EFS3bmQB05

[Wodan AI @wodan_secure_ai]

Interesting article by @mpyllan, about how Fully Homomorphic Encryption (FHE) differs from Partial Homomorphic Encryption (PHE).
Don't miss out—read now!
#WodanAI #HomomorphicEncryption #DataSecurity #PrivacyProtection #AdvancedEncryption #Cybersecurity
https://t.co/36LtPgczhv

[Wodan AI @wodan_secure_ai]

Best Practices for Developing Secure AI Systems AI is transforming various industries, but as it develops, the responsibility for ensuring secure and ethical practices in its creation increases.
https://t.co/UE6xCvfx0Y

[mpyllan @mpyllan]

Linear Congruential Generators in Python | https://t.co/9d2VmHldTg

[Wodan AI @wodan_secure_ai]

Balancing Innovation and Safety: Navigating AI's Potential Risks
How can we harness AI's transformative potential while minimizing its associated risks?
https://t.co/EmjBUhM6Hm

[Wodan AI @wodan_secure_ai]

Take your compliance and risk management to the next level with our advanced Enhanced KYC, KYB, and KYT solutions.
Leveraging encrypted data, we provide secure, efficient, and AI-powered verification processes tailored to your business needs.
https://t.co/ifJpfDafIx

[Wodan AI @wodan_secure_ai]

@Aravaca_innolab : The Hub of Cybersecurity at the #ForoMadridCyberStartup!
An exciting roundtable discussion recently took place at Aravaca Inlob (AIL), where @mpyllan served as the moderator. #WodanAI #Cybersecurity

[mpyllan @mpyllan]

LLM-based agentic systems in medicine and healthcare - Nature Machine Intelligence https://t.co/UDksmwXn3s

[mpyllan @mpyllan]

3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction? - https://t.co/gDOlWVAu8n

[mpyllan @mpyllan]

Bias remaining after adjusting for pre-treatment variables. https://t.co/9crQDnxIVp

[mpyllan @mpyllan]

Breaking the Scaling Code: How AI Models Are Redefining the Rules https://t.co/6wxrrPyjZ2

[mpyllan @mpyllan]

Task-Specific LLM Evals that Do & Don't Work https://t.co/SUE6baYxxx

[mpyllan @mpyllan]

AI for Math fund https://t.co/Zw6QtHMVX4

[mpyllan @mpyllan]

Introducing Wake Vision: A High-Quality, Large-Scale Dataset for TinyML Computer Vision Applications https://t.co/1TFtKniGYt

[mpyllan @mpyllan]

Evaluating generalizability of artificial intelligence models for molecular datasets - https://t.co/IxS0XXIFRx

[mpyllan @mpyllan]

5 Free Courses for Mastering LLMs - https://t.co/W5BzAVDOTk

[mpyllan @mpyllan]

Prompt Engineering: From Zero to GenAI Hero - https://t.co/jNBnwoi4aA

[mpyllan @mpyllan]

How good are LLMs at fixing their mistakes? A chatbot arena experiment with Keras and TPUs https://t.co/ID213pRxpt

[mpyllan @mpyllan]

GenCast predicts weather and the risks of extreme conditions with state-of-the-art accuracy https://t.co/FwSZFKbWJY