Artificial Neural Networks & Jina AI

Artificial Neural Networks & Jina AI

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4 min read

Introduction with Why, When, Where, & How??

Before Digging too deep into technical topics let's discuss somethings

Why are we discussing this ???

when, where, and how did it start ?????

Sooooo We have a final year project to submit in college and Indian colleges don't accept your project unless and until it's related to IoT, Machine Learning, or Artificial Intelligence, or has some fancy hardware attached to it. Almost all of my DevOps project ideas were rejected we were not allowed to make any sort of app or website and while searching for my project I came across this neural search framework and Jina AI company. Jina AI is an open-source, cloud-native neural search framework. It is used for building state-of-the-art and scalable deep learning search applications for any kind of modality. For example, videos, images, source code, long text, etc. It's a Germany Based Company.

Disclaimer

Most of the quotes and paragraphs in this blog have been web scrapped as I am a beginner myself & this is just my research to make you understand the term better

What is meant by neural networks?

Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the heart of deep learning algorithms. Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another.

How does it work?

Neural networks are computing systems with interconnected nodes that work much like neurons in the human brain. Using algorithms, they can recognize hidden patterns and correlations in raw data, cluster and classify it, and โ€“ over time โ€“ continuously learn and improve.

Why is it called a neural network?

Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another.

Neural networks in plain English to understand the term better

A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain. It is a type of machine learning process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.

What is Jina AI? ๐Ÿš€

Jina AI is a cloud-native neural search framework for any kind of Data

Jina is an approach to neural search. Itโ€™s cloud-native, so it can be deployed in containers, and it offers an anything-to-anything search. Text-to-text, image-to-image, video-to-video, or whatever else you can feed it. It empowers anyone to build SOTA and scalable neural search applications in minutes. Jina runs on 3 fundamental concepts Document, Executor and Flow.

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What makes Jina different from other players

  • Local & Cloud friendly ๐ŸŒฅ: From the very beginning it had distributed architecture, scalable and cloud-native. Ultimately, which gave the same DX on local, Docker Compose, and Kubernetes.

  • Server, Scale, and Share ๐Ÿš€: It helps you to scale your applications to meet availability and throughput requirements. Serves a local project with HTTP, WebSockets, or GRPC endpoints in just minutes.

  • Time Saver โฑ: Let's quickly build solutions for indexing, querying, and understanding multi or cross-modal documents. The document is the basic data type that Jina operates with. Video, image, text, audio, source code, and PDFs are the types of documents.

  • Own Stack ๐Ÿฑ: Jina empowers you to keep end-to-end ownership of your solution. Avoid integration pitfalls you get with fragmented, multi-vendor, generic legacy tools. Move over, Jina has out-of-the-box integrations with cloud-native ecosystems.

Outro ๐Ÿ’™

Thereโ€™s no better way to test-drive Jina than by diving in and playing with it. Jina's team provides pre-trained Docker images and jinabox.js, an easy-to-use front-end for searching text, images, audio, or video. The purpose of the blog is to create awareness about Jina and similar neural search frameworks. To learn further it is recommended to go through Jina's GitHuband Jina's blogs. In case you have some questions regarding the article or want to discuss something under the sun feel free to connect with me on Twitter๐Ÿ’•

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