​[[{“value”:” Developers frequently encounter the issue of AI-generated code not working as expected. AI language models can produce code snippets, but these often require multiple rounds of debugging and refinement. This slows down the development, making the process time-consuming.  Traditional tools and methods offer some… Read More »Micro Agent: An AI Agent that Writes and Fixes Code for You Niharika Singh Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In today’s information age, finding specific information you need can feel like searching for a needle in a haystack. Search engines act as a powerful tool for saving time and effort. Despite having access to a vast amount of information, existing search engines fail… Read More »Perplexica: The Open-Source Solution Replicating Billion Dollar Perplexity for AI Search Tools Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Deep learning methods excel in detecting cardiovascular diseases from ECGs, matching or surpassing the diagnostic performance of healthcare professionals. However, due to a lack of interpretability, their “black-box” nature limits clinical adoption. Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt… Read More »xECGArch: A Multi-Scale Convolutional Neural Network CNN for Accurate and Interpretable Atrial Fibrillation Detection in ECG Analysis Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Artificial intelligence (AI) research has long aimed to develop agents capable of performing various tasks across diverse environments. These agents are designed to exhibit human-like learning and adaptability, continuously evolving through interaction and feedback. The ultimate goal is to create versatile AI systems that… Read More »From Limited Tasks to General AI: AGENTGYM Evolves Agents with Diverse Environments and Autonomous Learning Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In large language models (LLMs), choosing the right inference backend for serving LLMs is important. The performance and efficiency of these backends directly impact user experience and operational costs. A recent benchmark study conducted by the BentoML engineering team offers valuable insights into the… Read More »A Comprehensive Study by BentoML on Benchmarking LLM Inference Backends: Performance Analysis of vLLM, LMDeploy, MLC-LLM, TensorRT-LLM, and TGI Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A major challenge in the field of natural language processing (NLP) is addressing the limitations of decoder-only Transformers. These models, which form the backbone of large language models (LLMs), suffer from significant issues such as representational collapse and over-squashing. Representational collapse occurs when different… Read More »Decoding Decoder-Only Transformers: Insights from Google DeepMind’s Paper Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The remarkable performance in different reasoning tasks has been demonstrated by several Large Language Models (LLMs), such as GPT-4, PaLM, and LLaMA. To further increase the functionality and performance of LLMs, there are more effective prompting methods and increasing the model size, both of… Read More »Buffer of Thoughts (BoT): A Novel Thought-Augmented Reasoning AI Approach for Enhancing Accuracy, Efficiency, and Robustness of LLMs Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Dataset distillation is an innovative approach that addresses the challenges posed by the ever-growing size of datasets in machine learning. This technique focuses on creating a compact, synthetic dataset that encapsulates the essential information of a larger dataset, enabling efficient and effective model training.… Read More »What is Dataset Distillation Learning? A Comprehensive Overview Aswin Ak Artificial Intelligence Category – MarkTechPost