​[[{“value”:” One of the most intriguing challenges is enabling AI agents to emulate human-like planning abilities. Such capabilities would allow these agents to navigate complex, real-world scenarios, a largely unmastered task. Traditional AI planning efforts have primarily focused on controlled environments with predictable variables and… Read More »Meet TravelPlanner: A Comprehensive AI Benchmark Designed to Evaluate the Planning Abilities of Language Agents in Real-World Scenarios Across Multiple Dimensions Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Today, we are excited to announce that Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. Code Llama is a state-of-the-art large language model (LLM) capable of generating code and… Read More »Code Llama 70B is now available in Amazon SageMaker JumpStart Kyle Ulrich AWS Machine Learning Blog

​[[{“value”:” In recent years, LMMs have rapidly expanded, leveraging CLIP as a foundational vision encoder for robust visual representations and LLMs as versatile tools for reasoning across various modalities. However, while LLMs have grown to over 100 billion parameters, the vision models they rely on… Read More »Unveiling EVA-CLIP-18B: A Leap Forward in Open-Source Vision and Multimodal AI Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Graph Neural Networks (GNNs) are deep learning methods that operate on graphs and are used to perform inference on data described by graphs. Graphs have been used in mathematics and computer science for a long time and give solutions to complex problems by forming… Read More »Google AI Releases TensorFlow GNN 1.0 (TF-GNN): A Production-Tested Library for Building GNNs at Scale Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Big Vision Language Models (VLMs) trained to comprehend vision have shown viability in broad scenarios like visual question answering, visual grounding, and optical character recognition, capitalizing on the strength of Large Language Models (LLMs) in general knowledge of the world. Humans mark or process… Read More »Enhancing Vision-Language Models with Chain of Manipulations: A Leap Towards Faithful Visual Reasoning and Error Traceability Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Mathematical reasoning in artificial intelligence represents a frontier that has long challenged researchers and developers. While effective for specific tasks, traditional computational methods often need to catch up when faced with the intricacies and nuances of complex mathematical problems. This limitation has spurred a… Read More »Deciphering the Language of Mathematics: The DeepSeekMath Breakthrough in AI-driven Mathematical Reasoning Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” One of the most exciting developments in this field is the investigation of state-space models (SSMs) as an alternative to the widely used Transformer networks. These SSMs, distinguished by their innovative use of gating, convolutions, and input-dependent token selection, aim to overcome the computational… Read More »Meet MambaFormer: The Fusion of Mamba and Attention Blocks in a Hybrid AI Model for Enhanced Performance Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Prompting Large Language Models (LLMs) has emerged as a standard practice in Natural Language Processing (NLP) following the introduction of GPT-3. The scaling of language models to billions of parameters using extensive datasets contributes significantly to achieving broad language understanding and generation capabilities. Moreover,… Read More »Meta AI introduces SPIRIT-LM: A Foundation Multimodal Language Model that Freely Mixes Text and Speech Janhavi Lande Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The development in the field of Artificial Intelligence (AI) with the introduction of Large Language Models (LLMs) has marked a substantial advancement in the capacity of machines to produce texts that make sense, obey commands, and solve problems in ways that are similar to… Read More »This AI Paper from USC and Google Introduces SELF-DISCOVER: An Efficient Machine Learning Framework for Models to Self-Discover a Reasoning Structure for Any Task Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the evolving landscape of Natural Language Processing (NLP), developing large language models (LLMs) has been at the forefront, driving a broad spectrum of applications from automated chatbots to sophisticated programming assistants. However, the computational expense of training and deploying these models has posed… Read More »Meet OpenMoE: A Series of Fully Open-Sourced and Reproducible Decoder-Only MoE LLMs Adnan Hassan Artificial Intelligence Category – MarkTechPost