What Are The Common Tools For AI
Software Development
As 2024 is here it is the best time to learn about the best AI tools used for AI software
development. This will help you stay ahead of the competition and keep you
informed about the latest trends. With time so many AI models have been launched
like chat gpt and Gemini. So, AI tools are now doing everything from designing to
writing the code. It does it much faster than a human. Furthermore, they will also
build unique features and functions for you to stand ahead of the competition.
So here in this guide, we will discuss a few common tools every developer must know.
Also, learn in this guide how to use them. Let’s dive in!
Top AI Software Development Tools
With the rise of AI development now businesses are including them in their
operations. Now here let's explore the most common AI tools that you must consider
to use.
TensorFlow
TensorFlow is a free AI software development tool that helps in numerical
computational. It’s mainly used for machine learning in both production and
research. The functionality of this tool is quite good because it is backed up by
community support. Through multi-layer hubs, it enables you to set up, train, and
send counterfeit neural systems with huge datasets quickly.
The only negative part of this tool is that it takes a lot of time to learn it. Additionally,
this ai based software can be deployed on the below-mentioned
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Desktops
Clusters
Mobiles
Edge Devices
CPUs, TPUs, and GPUs.
H20.AI
H20.AO is a powerful learning open-source platform that makes ML accessible and
easy to use. This AI software helps businesses make decisions and enables them to
draw insights. Two open versions of this software are available one is the paid
version known as Sparkling Water and the other is the standard H20. Moreover, this
software helps predict future trends, detect risks and fraud, analyze insurance data,
improve ads, help in healthcare, and better understand customers.
Cortana
Cortana is a smart voice assistant powered by AI that can help you with various tasks.
It helps you in tasks like setting a reminder, asking any query or doing something
else. One of the key benefits of this tool is its voice recognition making things easier
while saving time. Moreover, it is capable of working on different devices like
Windows, iOS, XBOX, and OS. It is like a digital system working on every device that
can help you out.
Cortana offers a variety of helpful features, which include:
 Supporting various tasks like switching on the light to placing an order.
 Takes voice commands to make things easier.
 Uses Bing Search Engine for information.
 Support multiple languages like German, French, English, Japanese, and
much more.
IBM WATSON
This AI software development tool is designed specially to answer queries. Also using
the Apache Hadoop framework, it supports SUSE Linux Enterprise Server 11 OS.
Once you train your model with Watson it gets the key concepts of core things. It is a
strong tool that helps business processes in a smarter way. Some features it includes
are:
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Supports distributed computing.
Can operate with existing tools.
Provides an API for app development.
Infosys Nia
This AI software development tool is responsible for collecting data from your
organization’s legacy system. Then it builds into a self-learning knowledge base.
Further, this knowledge is used by business analysts and software developers to
create high-quality, scalable ML models. The best thing is that it can be done without
requiring any data science expertise.
Some of the key features of this AI tool include the following:
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It allows easy data preparation, visualization, and ML methods
It supports elastic cloud deployments
Its GUI-based functionality lets build precise AI models
It brings together data preparation, deployment, and modelling in one place.
The Infosys Nia Prediction Server provides faster prediction and quick results.
Deeplearning4j
Deeplearning4j is a free, tailorable, deep learning library designed for Java and Scala.
For faster prototyping, it is developed as a plug-and-play. A few key features of
Deeplearning4j AI tools are:
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Works in business environments on distributed GPUs and CPUs.
Customized design to fit into a micro-service architecture.
For scaling on AWS it supports GPU
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Python, Java, and ScalaAPIs.
Scales on Hadoop.
Imports neural net models from other frameworks like TensorFlow, Caffe, and
Theano, via Keras.
It is a cross-team toolkit for the use of data scientists, DevOps, and data
engineers.
Conclusion
So, for today's guide that is it. Now you have an idea of what AI tools are and which
one is available. While there are also more AI tools present, the mentioned ones are
the most common type.
AI is the future of technology so learning more about its tools is very important for
successful business and the future. Moreover, including them in your business will
make it ahead of the competition going on. Wait no more and consult an expert AI
software development company. They will provide you with deep insight into each
tool and select the right one according to your needs.