Generative Artificial Intelligence (GenAI), specifically large language models (LLMs) like ChatGPT, has transformed the world of natural language processing (NLP). By using deep learning architectures and extensive datasets, these models can generate text that is contextually relevant and coherent, which can significantly improve applications in content creation, customer service, and virtual assistance. Moreover, developments in…
Artificial intelligence (AI) is continually evolving, with a significant challenge being the creation of systems that can effectively collaborate in dynamic environments. One area of focus in this regard is multi-agent reinforcement learning (MARL), which aims to teach agents to interact and adapt in these settings. However, these methods struggle with complexity and adaptability, especially…
Artificial intelligence (AI) developing systems often encounter several challenges like performing tasks that require human intellect, such as managing complex tasks and interacting with dynamic environments. This necessitates finding and synthesizing information from the web accurately and reliably. Current models face this difficulty, hence pointing out the need for more advanced AI systems. Existing solutions…
Large Language Models (LLMs) like GPT-4 and Gemini-1.5 have revolutionized the field of natural language processing, significantly enhancing text processing applications such as summarization and question answering. However, the long context management required for these applications presents challenges due to computational limitations and cost implications. Recent research has been exploring ways to balance performance and…
AI firm Mistral AI has launched the Mistral Large 2 model, its latest flagship AI model. The new iteration offers significant improvements on its predecessor, with considerable ability in code generation, mathematics, reasoning, and advanced multilingual support. Furthermore, Mistral Large 2 offers enhanced function-calling capabilities and is designed to be cost-efficient, high-speed, and high-performance.
Users can…
Large Language Models (LLMs), widely used in automation and content creation, are vulnerable to manipulation by adversarial attacks, leading to significant risk of misinformation, privacy breaches, and enabling criminal activities. According to research led by Meetyou AI Lab, Osaka University and East China Normal University, these sophisticated models are open to harmful exploitation despite safety…
MIT and Harvard researchers have highlighted the divergence between human expectations of AI system capabilities and their actual performance, particularly in large language models (LLMs). The inconsistent ability of AI to match human expectations could potentially erode public trust, thereby obstructing the broad adoption of AI technology. This issue, the researchers emphasized, escalates the risk…
Large Language Models (LLMs) such as GPT-4, Gemini, and Claude have exhibited striking capabilities but evaluating them is complex, necessitating an integrated, transparent, standardized and reproducible framework. Despite the challenges, no comprehensive evaluation technique currently exists, which has hampered progress in this area.
However, researchers from the LMMs-Lab Team and S-Lab at NTU, Singapore, developed the…
Fundamental large language models (LLMs) including GPT-4, Gemini and Claude have shown significant competencies, matching or surpassing human performance. In this light, benchmarks are necessary tools to determine the strengths and weaknesses of various models. Transparent, standardized and reproducible evaluations are crucial and much needed for language and multimodal models. However, the development of custom…