Author: Aneesh Tickoo

Aneesh Tickoo
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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.

Meet Multimodal C4: An Open, Billion-Scale Corpus of Images Interleaved with Text

AI Shorts
Sequence models may adapt to new tasks without parameter updates because of in-context learning. Few-shot learning can be presented as a next-token prediction task...

This AI Paper Demonstrates An End-to-End Training Flow on An Large Language Model LLM-13 Billion GPT-Using Sparsity And Dataflow

AI Shorts
Machine learning system implementation in the academic and commercial domains has been expedited by foundation models in the natural language processing and computer vision...

Researchers From Google AI and UC Berkeley Propose an AI Approach That Teaches LLMs to Debug its Predicted Program via Few-Shot Demonstrations

AI Shorts
Producing accurate code in a single effort for many programming jobs can be challenging. With several applications, including code synthesis from natural languages, programming...

A New Microsoft AI Research Shows How ChatGPT Can Convert Natural Language Instructions Into Executable Robot Actions

AI Shorts
Large language models (LLMs) that can comprehend and produce language similar to that of humans have been made possible by recent developments in natural...

Meet SparseFormer: A Neural Architecture for Sparse Visual Recognition with Limited Tokens

AI Shorts
Developing neural networks for visual recognition has long been a fascinating but difficult subject in computer vision. Newly suggested vision transformers replicate the human...

A New AI Research Integrates Masking into Diffusion Models to Develop Diffusion Masked Autoencoders (DiffMAE): A Self-Supervised Framework Designed for Recognizing and Generating Images...

AI Shorts
There has been a long-standing desire to provide visual data in a way that allows for deeper comprehension. Early methods used generative pretraining to...

GPT-4 Takes the Lead in Instruction-Tuning of Large Language Models: Advancing Generalization Capabilities for Real-World Tasks

AI Shorts
The outstanding generalization skills of Large Language Models (LLMs), such as in-context learning and chain-of-thoughts reasoning, have been demonstrated. Researchers have been looking towards...

Google Introduces TPU v4: A Machine-Learning Super-Computer With Hardware Support For Embeddings That May Be Optically Reconfigurable

AI Shorts
Machine learning (ML) models are still developing in challenging ways, both in terms of size and technique. Large language models (LLMs) serve as instances...

This AI Paper Introduces SELF-REFINE: A Framework For Improving Initial Outputs From LLMs Through Iterative Feedback And Refinement

AI Shorts
Iterative refinement is a key aspect of human problem-solving. Iterative refinement is a process that involves making an initial draught and then improving it...

Meet BloombergGPT: A Large Language Model With 50 Billion Parameters That Has Been Trained on a Variety of Financial Data

AI Paper Summary
The 2020 release of GPT-3 served as a compelling example of the advantages of training extremely large auto-regressive language models. The GPT-3 model has...

This AI Paper Introduces F2NeRF: A New Grid-Based NeRF System For Fast And Efficient Novel View Synthesis

AI Shorts
As the Neural Radiance Field (NeRF) emerged recently, innovative view synthesis research has evolved significantly. NeRF's main concept is to use the differentiable volume...

Nvidia Researchers Introduce BundleSDF: a Novel AI Method for Neural 6-DoF Object Tracking and 3D Reconstruction from a Monocular RGBD Video

AI Paper Summary
Six-DoF ("degree of freedom") position tracking and 3D reconstruction of an unknown object from a monocular RGBD video are two basic (and closely related)...
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