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.… →
CONCLUSION: An ECL immunoassay testing plasma P-tau217 accurately predicts amyloid PET positivity in cognitively unimpaired individuals. Our future analyses aim to determine if use of this assay may reduce the screening burden of preclinical individuals into anti-amyloid clinical trials. →
CONCLUSIONS: The findings suggest that the CDR memory box and the CDR cognitive composite progressed over 240 weeks and were associated with intermediate and advanced stages of amyloid at baseline. Functional changes in community affairs and home/hobbies were relatively stable. These finding suggest that specific CDR box score changes may help refine our measurement of… →
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… →
CONCLUSIONS: Treatment of patients suffering from pre-treated mCRC with FTD/TPI was associated not only with prolonged survival and delayed progression, but also with maintained QoL. Independent of other baseline characteristics such as ECOG performance status and age, low metastatic burden and indolent disease were factors associated with favourable outcome. →
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… →
A significant challenge in the field of visual question answering (VQA) is the task of Multi-Image Visual Question Answering (MIQA). This involves generating relevant and grounded responses to natural language queries based on a large set of images. Existing Large Multimodal Models (LMMs) excel in single-image visual question answering but face substantial difficulties when queries… →