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.
Artificial Intelligence (AI) and Machine Learning (ML) have grown significantly over the past decade or so, making remarkable progress in almost every field. Be it natural language, mathematical reasoning, or even pharmaceuticals, in today’s age, ML is the driving factor behind innovative solutions in these domains. Chemistry is also one such field where ML has…
Powered by onehouse.ai In the News NEA led a $100M round into Fei-Fei Li’s new AI startup, now valued at over $1B World Labs, a stealthy startup founded by renowned Stanford University AI professor Fei-Fei Li, has raised two rounds of financing two months apart, according to multiple reports. techcrunch.com Sponsor Bridging AI, Vector Embeddings…
A key challenge in text-to-music generation using diffusion models is controlling pre-trained text-to-music diffusion models at inference time. While effective, these models can only sometimes produce fine-grained and stylized musical outputs. The difficulty stems from their complexity, which usually requires sophisticated techniques for fine-tuning and manipulation to achieve specific musical styles or characteristics. This limitation…
In the dynamic field of Artificial Intelligence (AI), the trajectory from one foundational model to another has represented an amazing paradigm shift. The escalating series of models, including Mamba, Mamba MOE, MambaByte, and the latest approaches like Cascade, Layer-Selective Rank Reduction (LASER), and Additive Quantization for Language Models (AQLM) have revealed new levels of cognitive…
Model Predictive Control (MPC) has become a key technology in a number of fields, including power systems, robotics, transportation, and process control. Sampling-based MPC has shown effectiveness in applications such as path planning and control, and it is useful as a subroutine in Model-Based Reinforcement Learning (MBRL), all because of its versatility and parallelizability, Despite…
Despite the astonishing developments and achievements in the technology field, classical diffusion models still face challenges in image generation, particularly because of their slow sampling speed and the need for extensive parameter tuning. These models, used in computer vision and graphics, have become significant in tasks like synthetic data creation and aiding multi-modal models. However,…