Disrupting malicious uses of AI by state-affiliated threat actors
We terminated accounts associated with state-affiliated threat actors. Our findings show our models offer only limited, incremental capabilities for malicious cybersecurity tasks.
We terminated accounts associated with state-affiliated threat actors. Our findings show our models offer only limited, incremental capabilities for malicious cybersecurity tasks.
The Billion-Scale Approximate Nearest Neighbor Search Challenge, part of the NeurIPS competition track, aims to advance research in large-scale ANNS (Approximate Nearest Neighbor Search). BigANN is a collaborative arena where the best minds in the field come together to push the boundaries of vector search technology. Participants face four distinct tracks, each tackling a different…
Numerous challenges underlying human-robot interaction exist. One such challenge is enabling robots to display human-like expressive behaviors. Traditional rule-based methods need more scalability in new social contexts, while the need for extensive, specific datasets limits data-driven approaches. This limitation becomes pronounced as the variety of social interactions a robot might encounter increases, creating a demand…
The field of research focuses on integrating machine learning (ML) in healthcare for personalized treatment. This innovative approach aims to revolutionize how we understand and apply medical treatments, shifting from one-size-fits-all solutions derived from traditional clinical trials to more nuanced, individualized care. The essence of this research lies in predicting treatment outcomes tailored to individual…
Large language models (LLMs) face a hurdle in handling long contexts due to their constrained window length. Although the context window length can be extended through fine-tuning, this incurs significant training and inference time costs, adversely affecting the LLM’s core capabilities. Current LLMs, such as Llama-1 and Llama-2, have fixed context lengths, hindering real-world applications….
Powered by global.ntt In the News Google survey: 63% of IT and security pros believe AI will improve corporate cybersecurity AI could have an outsize impact on corporate cybersecurity, as well, according to a new study of 2,486 information technology and security professionals zdnet.com Sponsor GenAI can transform business operations GenAI presents immense opportunities for…
In recent times, Large Language Models (LLMs) have gained popularity for their ability to respond to user queries in a more human-like manner, accomplished through reinforcement learning. However, aligning these LLMs with human preferences in reinforcement learning from human feedback (RLHF) can lead to a phenomenon known as reward hacking. This occurs when LLMs exploit…