Author: Tanushree Shenwai

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.

Deepmind Open Sources Tracr: A Tool for Compiling Human-Readable Code to the Weights of a Transformer Model

As deep learning models grow in size and complexity, it becomes more difficult to articulate why and how they arrive at a given result....

A Study on Various Deep Learning-based Weather Forecasting Models

Due to its impact on human life worldwide, weather forecasting has drawn the interest of several researchers from various research communities. Many studies have...

Microsoft Research Proposes SMART: A Generic Pretraining Framework For Multi-Task Sequential Decision Making

Many linguistic and visual difficulties have been helped by self-supervised pretraining. In the language and vision domains, where a unified model may be easily...

Stanford AI Releases Stanford Human Preferences (SHP) Dataset: A Collection Of 385K Naturally Occurring Collective Human Preferences Over Text

Machine learning and deep learning models are pervasive in almost every sector today. Model improvement is one of the main obstacles in these ML...

Google AI Introduces FRMT: A New Dataset And Evaluation Benchmark For Few-Shot Region-Aware Machine Translation

In recent years, machine translation (MT) has made great strides, with outstanding results for many language pairs, particularly those with many parallel data available....

Meta AI Introduces GenAug: A New System That Uses Text2Image Models To Enable Robots To Transfer Behaviors Zero-Shot From A Simple Demonstrated Scene To...

Robot learning techniques have the ability to generalize over a wide range of tasks, settings, and objects. Unfortunately, these strategies call for extensive, diverse...

Google AI and Tel Aviv Researchers Introduce FriendlyCore: A Machine Learning Framework For Computing Differentially Private Aggregations

Data analysis revolves around the central goal of aggregating metrics. The aggregation should be conducted in secret when the data points match personally identifiable...

This AI Research Analyzes The Zero-Shot Learning Ability of ChatGPT by Evaluating It on 20 Popular NLP Datasets

By conditioning the model on suitable prompts, large language models (LLMs) have been proven to do a number of NLP tasks with zero-shot learning....

Why Deep Learning is Always Done on Array Data? New AI Research Introduces ‘Spatial Functa,’ Where From Data to Functa is Treated Like...

Implicit neural representations (INRs) or neural fields are coordinate-based neural networks representing a field, such as a 3D scene, by mapping 3D coordinates to...

A New AI Research Investigates The Benefits of Training Expert Language Models Over Instruction Tuning

Multitaskprompted fine-tuning (MT), also known as instruction-tuned Language Models (LMs), has recently demonstrated the ability to generalize to unseen tasks. It was once believed...

A New Artificial Intelligence Study Shows How Large Language Models LLMs Like GPT-3 Can Learn A New Task From Just A Few Examples Without...

Based on the previous text, large language models (LMs) like GPT-3 are trained to predict the next token. A very flexible LM that can...

Google And Columbia University Researchers Introduce Mnemosyne Optimizer: A Learning-To-Learn System To Train Transformers With Transformers

While it may seem appealing to train ML optimizers, doing so is costly because the examples used to train these systems are optimization issues....

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