Leveraging Computational Thinking in the Era of Generative AI
The importance of computational thinking increases, and becomes essential, as generative AI applications come to the fore.
The importance of computational thinking increases, and becomes essential, as generative AI applications come to the fore.
To what extent can the hallucinations of generative AI models be considered creative?
As the informational needs of the power grid become more complex and the connected “smart grid” expands, so too do the cybersecurity needs of grid operators.
The advantages of phase-chain memory superlattices are clear and demonstrably outweigh potential crosstalk concerns.
We propose an algorithmic security model based on the widely deployed technologies DNSSEC and Web PKI to cover the dimensions of identification, resolution, and transaction.
"A Security Model for Web-Based Communication," by Pouyan Fotouhi Tehrani et al., presents a new study of alerting authorities and their cybersafety measures.
The way we ask a generative AI chatbot a question affects the way it is answered.
If computing science wants to really be a science, we need to think about how we encourage people to defend their scientific claims with reproducible results.
The scaling of LLMs, with their enormous memory-bandwidth requirements, comes at a high cost.