Ensuring the safety and moderation of user interactions with modern Language Models (LLMs) is a crucial challenge in AI. These models, if not properly safeguarded, can produce harmful content, fall victim to adversarial prompts (jailbreaks), and inadequately refuse inappropriate requests. Effective moderation tools are necessary to identify malicious intent, detect safety risks, and evaluate the… →
It is observed that LLMs often struggle to retrieve relevant information from the middle of long input contexts, exhibiting a “lost-in-the-middle” behavior. The research paper addresses the critical issue of the performance of large language models (LLMs) when handling longer-context inputs. Specifically, LLMs like GPT-3.5 Turbo and Mistral 7B often struggle with accurately retrieving information… →
Concept-based learning (CBL) in machine learning emphasizes using high-level concepts from raw features for predictions, enhancing model interpretability and efficiency. A prominent type, the concept-based bottleneck model (CBM), compresses input features into a low-dimensional space to capture essential data while discarding non-essential information. This process enhances explainability in tasks like image and speech recognition. However,… →
Palo Alto, CA– OpenCV, the preeminent open-source library for computer vision and artificial intelligence, is pleased to announce a collaboration with Qualcomm Technologies, Inc., a global leader in edge computing technologies. Qualcomm Technologies’ commitment to advancing the field of computer vision and AI is demonstrated through their support of OpenCV as a Gold Member, reinforcing… →
Large language models (LLMs) have gained significant attention in recent years, but ensuring their safe and ethical use remains a critical challenge. Researchers are focused on developing effective alignment procedures to calibrate these models to adhere to human values and safely follow human intentions. The primary goal is to prevent LLMs from engaging in unsafe… →
The field of research focuses on optimizing algorithms for training large language models (LLMs), which are essential for understanding and generating human language. These models are critical for various applications, including natural language processing and artificial intelligence. Training LLMs requires significant computational resources and memory, making optimizing these processes a high-priority area for researchers. The… →
CONCLUSION: Our research indicates that this trial design is feasible with modifications such as recruiting with a larger multi-disciplinary organisation, providing velcro shoe fixtures and using a shorter timed walk test. Furthermore, progressing to a larger well-powered randomised control trial is justified considering our preliminary, albeit underpowered, efficacy findings. →
Frontier AI systems, including LLMs, increasingly shape human beliefs and values by serving as personal assistants, educators, and authors. These systems, trained on vast amounts of human data, often reflect and propagate existing societal biases. This phenomenon, known as value lock-in, can entrench misguided moral beliefs and practices on a societal scale, potentially reinforcing problematic… →