Author: Aneesh Tickoo

Aneesh Tickoo is a consulting intern at MarktechPost. He is currently pursuing his undergraduate degree in Data Science and Artificial Intelligence from the Indian Institute of Technology(IIT), Bhilai. He spends most of his time working on projects aimed at harnessing the power of machine learning. His research interest is image processing and is passionate about building solutions around it. He loves to connect with people and collaborate on interesting projects.

This AI Paper Proposes CaFo: A Cascade of Foundation Models that Incorporates Diverse Prior Knowledge of Various Pre-Training Paradigms for Better Few-Shot Learning

Many datasets, convolutional neural networks, and transformers have achieved remarkable success on various vision tasks. Instead, few-shot learning, where the networks are confined to...

Baidu AI Introduces StereoDistill: A Cross-Modal Distillation Method That Narrows The Gap Between Stereo And LiDAR-Based Approaches For 3D Object Detection

3D detectors equipped with LiDAR points for autonomous driving have exhibited outperforming performance. Unfortunately, LiDAR sensors are often expensive and weather-sensitive, restricting their use....

Meet PaLM-E: A New 562-Billion Parameter Embodied Multimodal Language Model That Performs Tasks Such As Robotic Manipulation Planning, Visual QA

Strong reasoning abilities are displayed by large language models (LLMs) in a variety of fields, including conversation, step-by-step reasoning, math problem-solving, and code authoring....

Amazon Research Introduces 3A (Approximate, Adapt, Anonymize): A Framework For Privacy Preserving Training Data Release For Machine Learning

Data synthesis has been presented as a feasible technique to share and analyze sensitive data in a way that is both morally and legally...

Microsoft Introduces Kosmos-1: A Multimodal Large Language Model That Can Perceive General Modalities, Follow Instructions, And Perform In-Context Learning

A general-purpose interface for various natural language activities has been successfully implemented using large language models (LLMs) by a team of Microsoft researchers. An...

Researchers From Oxford Open-Source WhisperX: A Time-Accurate Speech Recognition System With Word-Level Timestamps

Weakly supervised and unsupervised training approaches have shown outstanding performance on various audio processing tasks, including voice recognition, speaker recognition, speech separation, and keyword...

A New AI Research Explains How In-Context Instruction Learning (ICIL) Improves The Zero-Shot Task Generalization Performance For Both Pretrained And Instruction-Fine-Tuned Models

Large Language Models (LLMs) have shown they can adapt to target tasks during inference by a process known as few-shot demonstrations, sometimes known as...

A New AI Research Proposes VoxFormer: A Transformer-Based 3D Semantic Scene Completion Framework

Understanding a holistic 3D picture is a significant challenge for autonomous vehicles (AV) to perceive. It directly influences later activities like planning and map...

Alibaba AI Research Proposes Composer: A Large (5 Billion Parameters) Controllable Diffusion Model Trained on Billions of (Text, Image) Pairs

Nowadays, text-based generative picture models are capable of creating a wide range of photorealistic images. Many recent efforts have expanded the text-to-image models to...

Computer Vision Meets 🫠 Reinforcement Learning: This AI Research Shows that Reward Optimization is a Viable Option to Optimize a Variety of Computer Vision...

Not how effectively the model maximizes the training goal, but rather how well the predictions are matched with the task risk, i.e., the model's...

New AI Research From Anthropic Shows That Simple Prompting Approaches Can Help Large Language Models (LLMs) Trained With Reinforcement Learning From Human Feedback (RLHF)...

Big language models show negative social prejudices, which can occasionally grow worse with larger models. Scaling model size can improve model performance on a...

A New AI Research Introduces Directional Stimulus Prompting (DSP): A New Prompting Framework to Better Guide the LLM in Generating the Desired Summary

Natural language processing (NLP) has seen a paradigm shift in recent years, with the advent of Large Language Models (LLMs) that outperform formerly relatively...

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