As AI systems become more advanced, ensuring their safe and ethical deployment has become a critical concern for researchers and policymakers. One of the pressing issues in AI governance is the management of risks associated with increasingly powerful AI systems. These risks include potential misuse, ethical concerns, and unintended consequences that could arise from AI’s…
Large language models (LLMs) models, designed to understand and generate human language, have been applied in various domains, such as machine translation, sentiment analysis, and conversational AI. LLMs, characterized by their extensive training data and billions of parameters, are notoriously computationally intensive, posing challenges to their development and deployment. Despite their capabilities, training and deploying…
Long-context understanding and retrieval-augmented generation (RAG) in large language models (LLMs) is rapidly advancing, driven by the need for models that can handle extensive text inputs and provide accurate, efficient responses. These capabilities are essential for processing large volumes of information that cannot fit into a single prompt, which is crucial for tasks such as…
Forecasting Sustainable Development Goals (SDG) Scores by 2030: The Sustainable Development Goals (SDGs) set by the United Nations aim to eradicate poverty, protect the environment, combat climate change, and ensure peace and prosperity by 2030. These 17 goals address global health, education, inequality, environmental degradation, and climate change challenges. Despite extensive research tracking progress towards…
Reinforcement learning from human feedback RLHF is essential for ensuring quality and safety in LLMs. State-of-the-art LLMs like Gemini and GPT-4 undergo three training stages: pre-training on large corpora, SFT, and RLHF to refine generation quality. RLHF involves training a reward model (RM) based on human preferences and optimizing the LLM to maximize predicted rewards.…
DVC.ai has announced the release of DataChain, a revolutionary open-source Python library designed to handle and curate unstructured data at an unprecedented scale. By incorporating advanced AI and machine learning capabilities, DataChain aims to streamline the data processing workflow, making it invaluable for data scientists and developers. Key Features of DataChain: AI-Driven Data Curation: DataChain…
The cybersecurity risks, benefits, and capabilities of AI systems are crucial for the security and AI policy. As AI becomes increasingly integrated into various aspects of our lives, the potential for malicious exploitation of these systems becomes a significant threat. Generative AI models and products are particularly susceptible to attacks due to their complex nature…
Large Language Models (LLMs) have become significantly popular in the recent times. However, evaluating LLMs on a wider range of tasks can be extremely difficult. Public standards do not always accurately reflect an LLM’s general skills, especially when it comes to performing highly specialized client tasks that call for domain-specific knowledge. Different evaluation metrics are…
Because LLMs are inherently random, building reliable software (like LLM agents) requires continuous monitoring, a systematic approach to testing modifications, and quick iteration on fundamental logic and prompts. Current solutions are vertical, and developers still have to worry about keeping the “glue” between them, which will slow them down. Laminar is an AI developer platform…