​ Researchers from UC San Diego, Zhejiang University, Tsinghua University, UCLA, and Stanford University have introduced One-2-3-45++, an innovative AI method for rapid and high-fidelity 3D object generation. The approach leverages 2D diffusion models, initially fine-tuning for consistent multi-view image generation. Multi-view conditioned 3D native… Read More »Meet One-2-3-45++: An Innovative Artificial Intelligence Method that Transforms a Single Image into a Detailed 3D Textured Mesh in Approximately One Minute Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ In payments, understanding transactions is crucial for assessing risks in businesses. However, deciphering messy bank transaction data poses a challenge, as it is expressed in various ways across different banks. Existing solutions like Plaid and ChatGPT have limitations, such as low coverage and wordiness.… Read More »Meet Slope TransFormer: A Large Language Model (LLM) Trained Specifically to Understand the Language of Banks Niharika Singh Artificial Intelligence Category – MarkTechPost

​ While various AI models exist, the recently launched Claude 2.1 by Anthropic addresses some of the prevailing issues. Unlike its predecessors, this model boasts a remarkable 200,000-token context window, allowing it to understand and recall information from extensive documents. This surpasses other models and… Read More »Anthropic Releases Claude 2.1: Revolutionizing Enterprise AI with Extended Context Window and Enhanced Accuracy Niharika Singh Artificial Intelligence Category – MarkTechPost

​ Large multimodal models are becoming increasingly popular due to their ability to handle and analyze various data, including text and pictures. Academics have noticed their knowledge in various multimodal activities, including labeling images, answering visual questions, and more. State-of-the-art models like LLaVA, MiniGPT4, mPLUG-Owl,… Read More »This AI Paper from China Introduces ‘Monkey’: A Novel Artificial Intelligence Approach to Enhance Input Resolution and Contextual Association in Large Multimodal Models Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ AI systems capable of handling multiple tasks or domains without significant reprogramming or retraining are generalist agents. These agents aim to generalize knowledge and skills across various domains, exhibiting flexibility and adaptability in solving different problems. Simulations for training or research purposes often involve… Read More »Meet LEO: A Groundbreaking Embodied Multi-Modal Agent for Advanced 3D World Interaction and Task Solving Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ Recently, deep learning has been marked by a surge in research aimed at optimizing models for dynamic sparsity. In this scenario, sparsity patterns only reveal themselves at runtime, posing a formidable challenge to efficient computation. Addressing this challenge head-on, a group of researchers proposed… Read More »Microsoft Researchers Propose PIT (Permutation Invariant Transformation): A Deep Learning Compiler for Dynamic Sparsity Madhur Garg Artificial Intelligence Category – MarkTechPost

​ Researchers from McMaster University and FAIR Meta have developed a new machine learning (ML) technique for orbital-free density functional theory (OF-DFT). This ML method optimizes the total energy function and successfully replicates electronic density across various chemical systems. The approach has been applied to… Read More »McMaster University and FAIR Meta Researchers Propose a Novel Machine Learning Approach by Parameterizing the Electronic Density with a Normalizing Flow Ansatz Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ Although large language models (LLMs) such as GPT-4 and LLaMA are rapidly reimagining modern-day applications, their inference is slow and difficult to optimize because it is based on autoregressive decoding. The delay of an LLM request mostly depends on the answer length of the… Read More »‘Lookahead Decoding’: A Parallel Decoding Algorithm to Accelerate LLM Inference Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ The development of UltraFastBERT by researchers at ETH Zurich addressed the problem of reducing the number of neurons used during inference while maintaining performance levels similar to other models. It was achieved through fast feedforward networks (FFFs), which resulted in a significant speedup compared… Read More »ETH Zurich Researchers Introduce UltraFastBERT: A BERT Variant that Uses 0.3% of its Neurons during Inference while Performing on Par with Similar BERT Models Sana Hassan Artificial Intelligence Category – MarkTechPost

​ Amazon Elastic Compute Cloud (Amazon EC2) accelerated computing portfolio offers the broadest choice of accelerators to power your artificial intelligence (AI), machine learning (ML), graphics, and high performance computing (HPC) workloads. We are excited to announce the expansion of this portfolio with three new… Read More »Introducing three new NVIDIA GPU-based Amazon EC2 instances Chetan Kapoor AWS Machine Learning Blog