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.
Pose, look, facial expression, hand gestures, etc.—collectively called "body language”—has been the subject of many academic investigations. Accurately recording, interpreting, and creating non-verbal signals may greatly enhance the realism of avatars in telepresence, augmented reality (AR),...
It has always been challenging to launch an annotation effort. A team of researchers introduce The Portable Text Annotation tool (Potato), a web-based application approved for use in the EMNLP 2022 DEMO track. Potato's project hub...

Huawei Researchers Develop Pangu-Σ: A Large Language Model With Sparse Architecture And 1.085 Trillion Parameters

Large Language Models (LLMs) have exhibited exceptional skills and potential in natural language processing, creation, and reasoning. By employing a large quantity of textual...

This AI Paper Proposes COLT5: A New Model For Long-Range Inputs That Employs Conditional Computation For Higher Quality And Faster Speed

Machine learning models are needed to encode long-form text for various natural language processing tasks, including summarising or answering questions about lengthy documents. Since...

Meet Automated Reasoning And Tool-Use (ART): A Framework That Uses Frozen Large Language Models LLMs To Quickly Produce Intermediate Stages In Reasoning Programs

Large language models can swiftly adapt to new tasks utilizing in-context learning by being given a few demos and real language instructions. This avoids...

This AI Paper Proposes UPRISE: A Lightweight and Versatile Approach to Improve the Zero-Shot Performance of Different Large Language Models LLMs on Various Tasks

Large language models like GPT-3, OPT, and BLOOM have demonstrated impressive capabilities in various applications. According to a recent study, there are two key...

Microsoft Researchers Propose A New AI Method That Uses Both Forward And Backward Language Models To Meet In The Middle And Improve The Training...

Language models (LMs) have been extensively utilized for various aided writing activities, including text summarization, code completion, and paraphrasing. LMs are effective tools for...

This AI Paper Proposes A New Method For Fine-Tuning Model Weights To Erase Concepts From Diffusion Models Using Their Own Knowledge

Modern text-to-image generative models have drawn interest because of the exceptional image quality and limitless generating potential of their output. These models may mimic...

Meet ViperGPT: A Python Framework that Combines Vision and Language Models Using Code Generation to Achieve State-of-the-Art Results

The groundbreaking work of Neural Module Networks in prior years aimed to break down jobs into simpler modules. Through training from beginning to finish...

Meet FlexGen: A High-Throughput Generation Engine For Running Large Language Models (LLMs) With Limited GPU Memory

Large language models (LLMs) have recently shown impressive performance on various tasks. Generative LLM inference has never-before-seen powers, but it also faces particular difficulties....

Meet Petals: An Open-Source Artificial Intelligence (AI) System That Can Run 100B+ Language Models At Home Bit-Torrent Style

The NLP community has recently discovered that pretrained language models may accomplish various real-world activities with the help of minor adjustments or direct assistance....

This AI Paper Proposes a Novel Gradient-Based Method Called Cones to Analyze and Identify the Concept Neurons in Diffusion Models

Complex structure of the brain enables it to perform amazing cognitive and creative tasks. According to research, concept neurons in the human medial temporal...

Meet Magnushammer: A Transformer-based Approach to Premise Selection

Artificial intelligence's main focus has been on automating mathematical reasoning. More recently, machine learning has greatly benefited both informal and formal theorem proving. The...

UT Austin Researchers Propose WICE: A New Dataset for Fact Verification Built on Real Claims in Wikipedia with Fine-Grained Annotations

Natural language inference and textual entailment are enduring issues in NLP that can take many shapes. There are some significant gaps when current entailment...

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