​ Researchers from CodiumAI have released a new open-source AI code-generating tool, AlphaCodium. The code generation task is more difficult than other natural language tasks as it requires precise syntax, specific code to the problem, and difficult edge cases. The existing models for code generation… Read More »Codium AI Proposes AlphaCodium: A New Advanced Approach to Code Generation by LLMs Beating DeepMind’s AlphaCode Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​ The struggle to balance training efficiency with performance has become increasingly pronounced within computer vision. Traditional training methodologies, often reliant on expansive datasets, substantially burden computational resources, creating a notable barrier for researchers with limited access to high-powered computing infrastructures. This issue is compounded… Read More »Researchers from the National University of Singapore and Alibaba Propose InfoBatch: A Novel Artificial Intelligence Framework Aiming to Achieve Lossless Training Acceleration by Unbiased Dynamic Data Pruning Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ In handling databases, a challenge is crafting complex SQL queries. This can be difficult, especially for those who may not be SQL experts. The need for a user-friendly solution simplifying the process of generating SQL queries is apparent. While there are existing methods for… Read More »Meet Vanna: An Open-Source Python RAG (Retrieval-Augmented Generation) Framework for SQL Generation Niharika Singh Artificial Intelligence Category – MarkTechPost

​ Recent studies have shown that representation learning has become an important tool for drug discovery and biological system understanding. It is a fundamental component in the identification of drug mechanisms, the prediction of drug toxicity and activity, and the identification of chemical compounds linked… Read More »MIT Researchers Unveil InfoCORE: A Machine Learning Approach to Overcome Batch Effects in High-Throughput Drug Screening Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ A crucial area of interest is generating images from text, particularly focusing on preserving human identity accurately. This task demands high detail and fidelity, especially when dealing with human faces involving complex and nuanced semantics. While existing models adeptly handle general styles and objects,… Read More »InstantX Team Unveils InstantID: A Groundbreaking AI Approach to Efficient, High-Fidelity Personalized Image Synthesis Using Just One Image Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ Large language models (LLMs) have revolutionized various AI-infused applications, from chat models to autonomous driving. This evolution has spurred the need for systems that can efficiently deploy and serve these models, especially under the increasing demand for handling long-prompt workloads. The major hurdle in… Read More »Microsoft AI Research Unveils DeepSpeed-FastGen: Elevating LLM Serving Efficiency with Innovative Dynamic SplitFuse Technique Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ Large Language Models are being used in various fields. With the growth of AI, the use of LLMs has further increased. They are used in various applications together with those that require reasoning, such as answering multiple-turn questions, completing tasks, and generating code. However,… Read More »This AI Paper from Google Unveils the Intricacies of Self-Correction in Language Models: Exploring Logical Errors and the Efficacy of Backtracking Rachit Ranjan Artificial Intelligence Category – MarkTechPost

​ Task-agnostic model pre-training is now the norm in Natural Language Processing, driven by the recent revolution in large language models (LLMs) like ChatGPT. These models showcase proficiency in tackling intricate reasoning tasks, adhering to instructions, and serving as the backbone for widely used AI… Read More »Apple AI Research Introduces AIM: A Collection of Vision Models Pre-Trained with an Autoregressive Objective Sana Hassan Artificial Intelligence Category – MarkTechPost

​ In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of… Read More »Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning Aparajithan Vaidyanathan AWS Machine Learning Blog