Author: Tanushree Shenwai

Tanushree Shenwai
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http://www.marktechpost.com
Tanushree Shenwai is a consulting intern at MarktechPost. She is currently pursuing her B.Tech from the Indian Institute of Technology(IIT), Bhubaneswar. She is a Data Science enthusiast and has a keen interest in the scope of application of artificial intelligence in various fields. She is passionate about exploring the new advancements in technologies and their real-life application.

Microsoft AI Team Unveils NaturalSpeech 2: A Cutting-Edge TTS System with Latent Diffusion Models for Powerful Zero-Shot Voice Synthesis and Enhanced Expressive Prosodies

The goal of text-to-speech (TTS) is to generate high-quality, diverse speech that sounds like real people spoke it. Prosodies, speaker identities (such as gender,...

New AI Research from the University of Maryland Investigates Cramming Challenge for Training a Language Model on a Single GPU in One Day

In many areas of natural language processing, including language interpretation and natural language synthesis, large-scale training of machine learning models utilizing transformer topologies has...

Researchers at Michigan State University Developed ‘DANCE,’ a Python Library to Support Deep Learning Models for Analyzing Single-Cell Gene Expression at Scale

From single-modality profiling (RNA, protein, and open chromatin) to multimodal profiling and spatial transcriptomics, the technology for analyzing single cells has advanced rapidly in...

Meta AI Introduces IMAGEBIND: The First Open-Sourced AI Project Capable of Binding Data from Six Modalities at Once, Without the Need for Explicit Supervision

Humans can grasp complex ideas after being exposed to just a few instances. Most of the time, we can identify an animal based on...

A New AI Research Introduces Multitask Prompt Tuning (MPT) For Transfer Learning

Pretrained language models (PLMs) have significantly improved on many downstream NLP tasks due to finetuning. While current PLMs can include hundreds of millions of...

Do You Really Need Reinforcement Learning (RL) in RLHF? A New Stanford Research Proposes DPO (Direct Preference Optimization): A Simple Training Paradigm For Training...

When trained on massive datasets, huge unsupervised LMs acquire powers that surprise even their creators. These models, however, are trained on information produced by...

Researchers From Stanford And DeepMind Come Up With The Idea of Using Large Language Models LLMs as a Proxy Reward Function

With the development of computing and data, autonomous agents are gaining power. The need for humans to have some say over the policies learned...

LMSYS ORG Present Chatbot Arena: A Crowdsourced LLM Benchmark Platform With Anonymous, Randomized Battles

Many open-source projects have developed comprehensive linguistic models that can be trained to carry out specific tasks. These models can provide useful responses to...

Meet Lamini AI: A Revolutionary LLM Engine Empowering Developers to Train ChatGPT-level Language Models with Ease

Teaching LLM from scratch is challenging because of the extensive time required to understand why fine-tuned models fail; iteration cycles for fine-tuning on small...

Finetuning LLaMA on Medical Papers: Meet PMC-LLaMA-A Model that Achieves High Performance on Biomedical QA Benchmarks

The development of large language models (LLMs), such as OpenAI's ChatGPT and GPT-4, has reshaped artificial intelligence in many fields, including natural language processing,...

Meet RoboPianist: A New Benchmarking Suite for High-Dimensional Control in Piano Mastery with Simulated Robot Hands

The gauging process in the domains of control and reinforcement learning advance is quite challenging. A particularly underserved area has been robust benchmarks that...

Do Models like GPT-4 Behave Safely When Given the Ability to Act?: This AI Paper Introduces MACHIAVELLI Benchmark to Improve Machine Ethics and Build...

Natural language processing is one area where AI systems are making rapid strides, and it is important that the models need to be rigorously...

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