Artificial Intelligence
Advancing LLMs, generative AI and applying human centricity to create more meaningful collaboration between people and AI.
Advancing LLMs, generative AI and applying human centricity to create more meaningful collaboration between people and AI.
Designing and optimizing networked systems to further society’s digital transformation.
Paving the way for a secure Web 3.0 environment with self-sovereign identities, decentralized trust, blockchain security, systems security and applied cryptography.
Improving data architectures and frameworks. Developing technology for AI and parallel computing that intersects domain-specific programming languages and software engineering.
Large language models (LLMs) have emerged as a transformative force – but not without significant risk. Understand the scope of LLM’s as we explore their benefits, limitations and safe use – minimizing incorrect output such as hallucinations.
Information is being generated faster than humans can process it. This impedes our ability to acquire knowledge, which is slowing down scientific discovery and the advancement of technology. How can humans absorb information at the pace it is being created?
AI systems perform tasks that normally would require human intelligence, and can accomplish them faster by rapidly consuming and analysing large amounts of complex data. That’s the theory. In practice, many instances of applied AI fail spectacularly. In some cases, we don’t even notice!