​[[{“value”:” Scientists studying Large Language Models (LLMs) have found that LLMs perform similarly to humans in cognitive tasks, often making judgments and decisions that deviate from rational norms, such as risk and loss aversion. LLMs also exhibit human-like biases and errors, particularly in probability judgments… Read More »This AI Paper from Princeton and the University of Warwick Proposes a Novel Artificial Intelligence Approach to Enhance the Utility of LLMs as Cognitive Models Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Managing and extracting useful information from diverse and extensive documents is a significant challenge in data processing and artificial intelligence. Many organizations find it difficult to handle various file types and formats efficiently while ensuring the accuracy and relevance of the extracted data. This… Read More »‘RAG Me Up’: A Generic AI Framework (Server + UIs) that Enables You to Do RAG on Your Own Dataset Easily Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The recent release of this open-source project, LlamaFS, addresses the challenges associated with traditional file management systems, particularly in the context of overstuffed download folders, inefficient file organization, and the limitations of knowledge-based organization. These issues arise due to the manual nature of file… Read More »LlamaFS: An Open-Source Self-Organizing File system with Llama-3 Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Transformers are essential in modern machine learning, powering large language models, image processors, and reinforcement learning agents. Universal Transformers (UTs) are a promising alternative due to parameter sharing across layers, reintroducing RNN-like recurrence. UTs excel in compositional tasks, small-scale language modeling, and translation due… Read More »MoEUT: A Robust Machine Learning Approach to Addressing Universal Transformers’ Efficiency Challenges Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Human feedback is often used to fine-tune AI assistants, but it can lead to sycophancy, where the AI provides responses that align with user beliefs rather than being truthful. Models like GPT-4 are typically trained using RLHF, enhancing output quality as humans rated. However,… Read More »Addressing Sycophancy in AI: Challenges and Insights from Human Feedback Training Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Natural language processing (NLP) teaches computers to understand, interpret, and generate human language. Researchers in this field are particularly focused on improving the reasoning capabilities of language models to solve complex tasks effectively. This involves enhancing models’ abilities to process and generate text that… Read More »From Explicit to Implicit: Stepwise Internalization Ushers in a New Era of Natural Language Processing Reasoning Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Llama 3 has significantly outperformed GPT-3.5 and even surpassed GPT-4 in several benchmarks, showcasing its strength in efficiency and task-specific performance despite having fewer parameters. However, GPT-4o emerged with advanced multimodal capabilities, reclaiming the top position. Llama 3, utilizing innovations like Grouped-Query Attention, excels… Read More »Llama3-V: A SOTA Open-Source VLM Model Comparable performance to GPT4-V, Gemini Ultra, Claude Opus with a 100x Smaller Model Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” LLMs like GPT, Gemini, and Claude have achieved remarkable performance but remain proprietary, with limited training details disclosed. Open-source models such as LLaMA-3 have provided weights but need more transparency in training data and methods. Efforts to create fully transparent LLMs, such as Pythia,… Read More »MAP-Neo: A Fully Open-Source and Transparent Bilingual LLM Suite that Achieves Superior Performance to Close the Gap with Closed-Source Models Sana Hassan and Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Genomic language models are a new and exciting field in the application of large language models to challenges in genomics. In this blog post and open source project, we show you how you can pre-train a genomics language model, HyenaDNA, using your genomic data… Read More »Pre-training genomic language models using AWS HealthOmics and Amazon SageMaker Shamika Ariyawansa AWS Machine Learning Blog

​[[{“value”:” Today, we are excited to announce that the first model in the next generation Falcon 2 family, the Falcon 2 11B foundation model (FM) from Technology Innovation Institute (TII), is available through Amazon SageMaker JumpStart to deploy and run inference. Falcon 2 11B is… Read More »Falcon 2 11B is now available on Amazon SageMaker JumpStart Supriya Puragundla AWS Machine Learning Blog