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 struggle to balance training efficiency with performance has become increasingly pronounced within computer vision. Traditional training methodologies, often reliant on expansive datasets, substantially burden computational resources, creating a notable barrier for researchers with limited access to high-powered computing infrastructures. This issue is compounded by the fact that many existing solutions, while reducing the sample…
Powered by jotform.ai Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Google DeepMind’s new AI models Google DeepMind is launching two new AI models designed to help robots “perform a wider range of real-world tasks than ever before.” The first, called…
Self-supervised learning (SSL) has proven to be an indispensable technique in AI, particularly in pretraining representations on vast, unlabeled datasets. This significantly reduces the dependency on labeled data, often a major bottleneck in machine learning. Despite the merits, a major challenge in SSL, particularly in Joint Embedding (JE) architectures, is evaluating the quality of learned…
In the News Google reportedly worked directly with Israel’s military on AI tools Google worked with the Israeli military in the immediate aftermath of its ground invasion of the Gaza Strip, racing to beat out Amazon to provide AI services, according to company documents obtained by the Washington Post. theverge.com Sponsor Discover what the most…
Language modeling, a critical component of natural language processing, involves the development of models to process and generate human language. This field has seen transformative advancements with the advent of large language models (LLMs). The primary challenge lies in efficiently optimizing these models. Distributed training with multiple devices faces communication latency hurdles, especially when varying…
Natural Language Processing (NLP) is one area where Large transformer-based Language Models (LLMs) have achieved remarkable progress in recent years. Also, LLMs are branching out into other fields, like robotics, audio, and medicine. Modern approaches allow LLMs to produce visual data using specialized modules like VQ-VAE and VQ-GAN, which convert continuous visual pixels into discrete…