Author: Nikhil

Nikhil
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Nikhil is an intern consultant at Marktechpost. He is pursuing an integrated dual degree in Materials at the Indian Institute of Technology, Kharagpur. Nikhil is an AI/ML enthusiast who is always researching applications in fields like biomaterials and biomedical science. With a strong background in Material Science, he is exploring new advancements and creating opportunities to contribute.

CMU Researchers Introduce OWSM v3.1: A Better and Faster Open Whisper-Style Speech Model-Based on E-Branchformer

AI Shorts
Speech recognition technology has become a cornerstone for various applications, enabling machines to understand and process human speech. The field continuously seeks advancements in...

Apple Researchers Introduce LiDAR: A Metric for Assessing Quality of Representations in Joint Embedding JE Architectures

AI Shorts
Self-supervised learning (SSL) has proven to be an indispensable technique in AI, particularly in pretraining representations on vast, unlabeled datasets. This significantly reduces the...

Meet CompAgent: A Training-Free AI Approach for Compositional Text-to-Image Generation with a Large Language Model (LLM) Agent as its Core

AI Shorts
Text-to-image (T2I) generation is a rapidly evolving field within computer vision and artificial intelligence. It involves creating visual images from textual descriptions blending natural...

Google Deepmind and University of Toronto Researchers’ Breakthrough in Human-Robot Interaction: Utilizing Large Language Models for Generative Expressive Robot Behaviors

AI Shorts
Numerous challenges underlying human-robot interaction exist. One such challenge is enabling robots to display human-like expressive behaviors. Traditional rule-based methods need more scalability in...

Researchers from ETH Zurich and Microsoft Introduce SliceGPT for Efficient Compression of Large Language Models through Sparsification

AI Shorts
Large language models (LLMs) like GPT-4 require substantial computational power and memory, posing challenges for their efficient deployment. While sparsification methods have been developed...

Meet WebVoyager: An Innovative Large Multimodal Model (LMM) Powered Web Agent that can Complete User Instructions End-to-End by Interacting with Real-World Websites

Applications
Existing web agents face limitations that stem from the fact that these agents often rely on a single input modality and are tested in...

Enhancing Low-Level Visual Skills in Language Models: Qualcomm AI Research Proposes the Look, Remember, and Reason (LRR) Multi-Modal Language Model

AI Shorts
Current multi-modal language models (LMs) face limitations in performing complex visual reasoning tasks. These tasks, such as compositional action recognition in videos, demand an...

This AI Paper from Adobe and UCSD Presents DITTO: A General-Purpose AI Framework for Controlling Pre-Trained Text-to-Music Diffusion Models at Inference-Time via Optimizing Initial...

AI Shorts
A key challenge in text-to-music generation using diffusion models is controlling pre-trained text-to-music diffusion models at inference time. While effective, these models can only...

This AI Paper Proposes COPlanner: A Machine Learning-based Plug-and-Play Framework that can be Applied to any Dyna-Style Model-based Methods

AI Shorts
One of the critical challenges in model-based reinforcement learning (MBRL) is managing imperfect dynamics models. This limitation of MBRL becomes particularly evident in complex...

Meet VMamba: An Alternative to Convolutional Neural Networks CNNs and Vision Transformers for Enhanced Computational Efficiency

AI Shorts
There are two major challenges in visual representation learning: the computational inefficiency of Vision Transformers (ViTs) and the limited capacity of Convolutional Neural Networks...

Can We Optimize AI for Information Retrieval with Less Compute? This AI Paper Introduces InRanker: a Groundbreaking Approach to Distilling Large Neural Rankers

AI Shorts
The practical deployment of multi-billion parameter neural rankers in real-world systems poses a significant challenge in information retrieval (IR). These advanced neural rankers demonstrate...

This Paper from LMU Munich Explores the Integration of Quantum Machine Learning and Variational Quantum Circuits to Augment the Efficacy of Diffusion-based Image Generation...

AI Shorts
Despite the astonishing developments and achievements in the technology field, classical diffusion models still face challenges in image generation, particularly because of their slow...
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