Best AI Engines
Best AI Engines

In the early times, AI was much inferior to what it is today. Now there are various industries that are using the concept of Machine Learning and Neural Networks to create a better application. These applications are capable of showing you relevant data based on your interaction with them. Although, getting started with them with the perspective of development could be a little confusing. Therefore, in order to ease you a bit here, we have mentioned some of the best AI Engines for you. 

What is AI and AI Engines?

As per the definition by Google,” the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”

In simple terms, it is basically a machine that imitates human behaviour to solve problems(at least up to an extent). Most of the AI that is being developed caters to sections of intelligence. Below is the list of intelligence that has been bridged by the AI as of now:

  • Speech Recognition
  • Planning
  • Learning
  • Problem Solving

Most of the work that has been done in the department can be encapsulated in these four terms. There are a varied number of AI engines who have been effectively capable of making applications that increases the human ease by miles. The technology is being applied in various sectors such as industries, finance, healthcare, education, transportation, and many more.

Although, let’s throw a little more light on AI Engines.

AI Engines: An AI Engine is a tool that helps you build an Artificially intelligent system. These tools help to reiterate tasks that are repetitive and often difficult to achieve by a human(it might take longer to complete that task by a human generally). There are a variety of tools that are currently present in the market. Some of the most common names are Cortana, Google Assistant, Siri, etc. Although, we will be discussing some of the best tools that are available further in this article.

How App Developer use AI Engines?

AI Engines as mentioned before are tools that can be used to create AI-based applications. There are a variety of AI Engines available currently in the market. All of these AI Engines serves a purpose. Therefore, it depends on the developer what he actually wants to begin with. To start developing an AI-based application, one needs to be good at Algebra and Probability theories. Except there are a couple of languages that support and give liberty to you while developing an app for instance Python, R, Prolog etc. Therefore, if you are thinking of getting started then we have mentioned some of the best AI engines that are out there. So read ahead !!!

Famous Services made using AI Engines

Google Search: A lot of people may not have stressed enough but Google Search is the best example of AI. The service uses deep neural networks to sort the best pages in search. The AI support is the reason we start seeing recommendation as soon as we start to type something in the search box. They are continuously working to improve their services and it is of no doubt that Google is the best search engine out there.

Netflix: Well a lot of great TV series and Movies are pushed by the recommended section on Netflix. Although, the application uses machine learning and Data Science to actually provide you content you may like. Netflix has been working tirelessly to get their customers the best content and things that the most number of people might like.

Amazon: You might be searching for a denim jacket but have you ever figured out why from then onwards you get to see similar products. Well, the answer if the AI integration on the E-Commerce website of Amazon to sell products that are more suited to a particular individual.

Facebook: Facebook is the world’s largest social media website. It has millions of users logging into it daily. Although, how come our chances of watching something truly explicit is seldom. I personally saw anything related to PORN or anything as offensive as a hate speech by Al-Qaeda on FB. Well, the company uses AI to filter content. It also uses tech to solve real-time problems.

Tesla: Tesla and AI are going hand in hand. The company is one of the partners in the project Alpha.Go. It is the AI-based system that defeated the world champion of GO. It is highly intuitive. Although, if we talk about the automotive aspect then they have been working to make driving safer than before. Tesla Autopilot is a driving assistant that has capabilities like switching lanes automatically, lane centering, autopilot, and much more than a usual driver does.

Emergence of AI in the Present World

There is an actual AI that can predict what’s gonna happen in a few seconds based on a still picture. Yes, the emergence is real from artificial bionics to help crippled to predictive AI which can make its own decision(most importantly, they have started to make it correct). There are consistently many AI being made that are way more intelligent than the humans in that particular department. For example, the chess prodigy Gary Kasparov was defeated by IBM’s AI System “Deep Blue”.

From great AI theories about AI from Alan Turing to the latest invention known as Alpha.Go, the AI of the modern world has dramatically changed. We currently have to work effectively on neural networks. The concept imitates the likeness of human brain. In neural networks, there are multiple nodes which act as a neuron that helps the machine to decide what is right based on reinforcement learning.

The tech has become so accessible all thanks to the cheaper hardware that now we can compete with two AI system and leave them to learn from each other. The AI might cause social disruption but many open-source engines have already been put to good use. Predictive AI can help us create a new and better world. This can give us additional advantages in reaching heights where we might not reach unless we receive some decent assistance.

List of Top AI Engines

1.IBM Watson

IBM Watson Best AI Engines

About: IBM Watson is an enterprise solution developed to help the organisation to reach its full potential and make work easy & fast. The system also allows to predict and enhance overall usability. The infrastructure of the AI engine is based on the cloud service by IBM. Most of the organisations that use IBM Watson lie between finance to healthcare. The system can help you analyse your data better making it the best AI Engines in its niche. IBM Watson is capable of controlling data, owning it, data insights, and most importantly making it your intellectual property. This is a formulaic approach to create better strategies and plan.

Features:

  • Has a robust NLD(Natural Language Dialogue) for effective communication.
  • Analyses the data to provide meaningful insights.
  • Automated analyses that are predictive.
  • Get one-click analysis.
  • Comes with a speech recognition system.
  • Capable of analysing images and videos.
  • Helps you analyse more content and concepts.

Pros:

  • Capable of processing unstructured data into useful info.
  • Approaches problems with the decision.
  • Fill the gap what humans can’t.
  • Help in transforming customer service.
  • Capable of handling huge chunks of data.
  • Advantage over your competition
  • Enhance overall performance by providing you with meaningful data.

Cons:

  • The service is only available in English.
  • Can’t process structured data directly.
  • Limited resources.
  • It needs to be maintained.

2.TensorFlow

TensorFlow Best AI Engines

About: TensorFlow was developed by Google brain. It is an open-source library of software that is completely free. The AI Engine can help you with dataflow and differentiable programming. The engine can be applied to a multitude of task making it the best AI Engine out there. It is in its core a maths library that helps you integrate machine learning using neural networks. It was made to be used in house but it is helping people all around the world.

Features:

  • Visualise every part of the graph.
  • It is operable with flexibility.
  • Easy to train using a CPU or GPU.
  • Capable of training multiple Neural Networks at the same time.
  • It has a great community.
  • Components used by the Engine are layered.

Pros:

  • It is open source.
  • Capability to do almost anything.
  • Companies like AMD, Nvidia, UBER, Dropbox etc are all using TensorFlow.
  • Can work hand in hand with Keras.
  • Can be run using a standard hardware library acceleration.
  • Great for people who are studying deep learning.
  • A wide range of tutorials online.
  • Capable of running on Google TPU’s.

Cons:

  • It is a low-level language.
  • The learning curve is steep.
  • Need not have any use for much of the low-level libraries.
  • It is hard to debug.

3.Amazon Lex

Amazon Lex Best AI Engines

About: If you are thinking of making a conversational interface then this may be the best AI engine for you. The engine can be used for both voice and text. This engine advanced deep learning functionalities that help you automatically recognise speech for TTS conversion. It also uses the NLU(Natural Language Understanding) to understand the intent of your text. With Amazon Lex, you can also build an application for Amazon Alexa.

Features:

  • Speech recognition system and the NLU are world-class.
  • It can do multiple conversations at the same time based on intent.
  • Comes with multiple utility prompt.
  • Can be easily connected to Amazon Lambda.
  • Capability of connecting to enterprise systems.
  • Can be easily deployed to multiple platforms in a single click.
  • The intents can be chained using the system.
  • Support Telephony Audio of up to 8kHz.

Pros:

  • Easily scalable and comes with Natural Language Processing.
  • SDK capable of understanding multiple programming languages.
  • Comes with Automated speech recognition and speech to text.
  • It has mobile hub integration.
  • Also supports Amazon Lambda.

Cons:

  • The only language supported by Lex is English.
  • It is essential to have a web-based integration.
  • Preparing the dataset is a little critical.

4.Microsoft Azure Machine Learning

Microsoft Azure Machine Learning Best AI Engines

About: It is a great tool for making a system capable of machine learning. Azure Machine Learning is a drag-n-drop tool that can be used to build, test, and deploy predictive analytics. There are various models and datasets that are integrated into the canvas. It is one of the best AI Engines out there in the market. The system can be easily connected to your experiments. This one will also help if you wish to connect your training experiment into a predictive experiment.

Features:

  • It comes with predictive modelling and anomaly detection.
  • It has intuitive graphical interfaces.
  • Capability of supporting R Language.
  • The tools can be used just by dragging-and-dropping.
  • Comes with Text analytics and disaster recovery.

Pros:

  • Available in most places globally.
  • It is the leader in IaaS Security.
  • It is highly scalable.
  • Made keeping the IT budgets in mind.

Cons:

  • It requires management to work with.
  • This one requires expertise to make sure all features are working properly.

5.Infosys NIA

Infosys NIA Best AI Engines

About: Infosys NIA is a third-generation artificial intelligence platform. The platform is based on the first-generation system which was Infosys Mana. Infosys NIA services comprise of big data/analytics, machine learning, knowledge management, Cognitive automation abilities from mana. This one acts as a unified, flexible, modular platform that gets you a wide set of industry functions and makes your custom experience better. This is the reason it is among the list of the best AI Engines out there.

Features:

  • Great Machine Learning Platform along with Data Analytics.
  • It comes with knowledge processing.
  • It has the capability of Predictive as well as cognitive automation.
  • This one also has robotic process automation.

Pros:

  • Capable of doing repetitive task and responsibilities using AI.
  • Gives you enough time to solve distinctive problems.
  • Data processing is relatively faster.
  • Capabilities for the organisation from their past data.
  • Lets you spare assets for more workforce and financial aspects.

Cons:

  • Only supports web-based devices.
  • Not ideal for small organisations.
  • There is no free trial.

6.Wipro Holmes

Wipro Holmes Best AI Engines

About: Can you see the obvious joke the name is making?  Holmes and Watson. This is another really great AI engine that uses artificial intelligence and machine learning offering cognitive learning for accelerated behaviour. This is the reason why it fits just right in the list of the best AI Engines. With this engine at support, companies can look forward to more sustainable approaches. This one gives the ease of performing repetitive tasks for any organisation to make them more sophisticated.

Features:

  • Capable of predicting outcomes and trends.
  • Provide cognitive process automation.
  • Supports visual computing applications.
  • Capability to discover patterns.
  • It has the ability to recognise speech.
  • Supports robotic automation, knowledge curation, and natural language understanding.

Pros:

  • Provides immersion for various digital tactics for smart predictions and machine learning logic.
  • It can easily read patterns and understand data making it capable to predict outcomes and trends.
  • Capable of deploying cognitive process automation.
  • Capable of accessing knowledge-based database.
  • Capable of managing Robots and Drones.

Cons:

  • Not compatible using Android.
  • Not adequate for small businesses.
  • Doesn’t have a trial version.

7.Caffe

Caffe

About: The AI engine has been developed using deep learning framework with modularity, speed, and modularity. The framework was developed at the University of California. This is an open-source framework which means anyone can use it making it one of the best AI Engine. It provides deep learning architecture that can get you image classification and image segmentation. It is also capable of supporting multiple designs neural networks, CNN, RCNN, and LSTM. Also, all the calculations can be done easily using CPUs and GPUs.

Features:

  • Capable of Image classification and image segmentation.
  • Supports CNN, RCNN, and LSTM.
  • Capability to connect with multiple neural network designs.
  • Can make calculations using CPUs and GPUs.

Pros:

  • Easy to apply machine learning without writing a single line of code for image processing.
  • The engine is pretty fast.
  • Train GPU with ease.
  • Comes with great features like convolutions, connected, ReLU etc.
  • It is easy to handle data types using the engine.

Cons:

  • It is useless if you go outside for more functionalities.
  • All the layers come in between if you try to define your own.
  • Support multiples inputs but online provide HDF5.
  • Multi-GPU processing is limited.
  • Comes with interesting updates but only in patches.

8.Premonition

Premonition

About: This is one of its kind. The AI Engine actually deals with Law. It has one of the biggest databases of litigations. This engine uses big data to mine important predictions. It can actually predict the attorneys win before the judges conclude it. The engine is capable of doing global searches making it one of the best AI engines to start with. 

Features:

  • Access to the track record of your attorney.
  • Get full-fledged analytics of attorney for results and win rates.
  • Get to know co-counsel to make your victory collateral.
  • Get expert advice based on persuasiveness and previous records.
  • Ranked arbitrators based on previous track records and past records.

Pros:

  • Helps you uncover the background details.
  • Prediction technology really gives the edge.
  • Get great analytics to compare better.
  • Automated documentation.
  • Get to know all the intellectual property.
  • The billing is electronic.

Cons:

  • Huge disadvantages to the opponent in terms of fair play.
  • Can’t operate in every department.

9.Rainbird

Rainbird

About: This is another really great AI engine that helps organisations to better decision making. Rainbird is an award-winning engine which means it is among the best AI engines out there. It is great that it automatically takes up the solution and solves them by human intuition. That is how it fixes complex responsibilities. The engine is also quite transformative allowing the companies to dig out more innovational approaches for better sustainability. By using Rainbird, you are not only sorting the work done by an organisation using a cognitive approach but also serving your customers better. 

Features:

  • In this, the user can define their own set of rules. 
  • Capability to run multiple processes at the same time.
  • Get access to visual interfaces.
  • It can be infused with topics like concepts, relationships, facts, and decision-making rules, they give birth to a Knowledge Map.
  • It uses RBLang as the language.
  • With this developers can create their model visually.
  • It has an open architecture, therefore, can be easily used with a third-party app.
  • It can interact with the system based on context.

Pros:

  • Helps you stay away from wrong decision making.
  • Capability to think like experts without having them.
  • Better connections with customers.
  • Give more free-time to your team for more sustainable work.
  • Build a simple yet tailored experience as per your likeness.

Cons:

  • Only Supports English as the language.
  • No support for Android or iOS.
  • There is no trial version.

10.Vital AI

Vital.AI

About: Vital AI provides Vital Development Kit to make applications using the Haley AI agent Platform. It is an intelligent platform that creates intelligent interaction with people, devices, and data. The kit can be used to develop any AI-based applications faster and more efficiently. It is among the best AI engines that are out there. It is capable of working for Application Development, Artificial Intelligence, Data Science, Predictive Analysis, Data Governance and much more. It is a great tool if your head is towards the development of an AI-based application.

Features:

  • It provides great tools for consulting and developing services.
  • Creates a data model that makes the work more effective and fast.
  • The AI algorithm can process the data and easily automate the process.
  • Haley AI Platform is very effective in making business processes automated.
  • Can be integrated with Apache Spark.

Pros:

  • Leaves less room for error.
  • Get you an effective decision that overall optimises the process.
  • Can be applied if there is a risky situation.
  • It can be made to work 24*7.

Cons:

  • The area of work is limited.
  • Increases your dependency over it.

11.Wit

Wit.AI

About: Wit.AI is a great framework for developing chatbots. A lot of websites are already using them to increase the efficiency of processes. This helps in active communication with your customers and helps them engage better with you. Wit.AI is an open library that comes with extensible NLP engine. It can help you build conversation along with devices. It gets you an easy API to work with and understand human communication. This one can also help you predict the coming events after gathering data.

Features:

  • It is one of the most powerful API out there to build chatbots.
  • Capable of understanding natural language.
  • Gets you a free SaaS environment to build applications.
  • Create powerful chatbots capable of handling both text and voice.
  • Can work on new commands by the users.
  • Supports languages like node.js, Python, Ruby, HTTP API.

Pros:

  • Provides a diverse range of functionality.
  • Natural Language processing eases a lot to the use.
  • The SaaS environment are free.
  • Chatbots created using the app are world-class.

Cons:

  • It does not support third-party integration of applications.
  • The engine can take time processing data based on the task.
  • It requires invoking of logic every time you run a new interaction.
  • With the increase in the number of cases, the engine slows down since the resources are limited.

12.SciKit Learn

SciKit Learn

About: It is a free software learning library. The kit was developed for Programming in Python. It was initially a project in Google Summer of Code started by David Cournapeau. In fact, some of the code of the kit has been written in Cython other than Python to achieve better performance. The initial version of the kit launched in August 2013 although there has been a recent update in May 2019. It is truly among the best AI Engines that are available out there.

Features:

  • It is a free platform that comes with minimal restrictions.
  • It can predict human behaviour hence is considered for industrial use.
  • It provides regression and clustering.
  • With this, the user can select their model of choice.
  • Has the capability of preprocessing.
  • Comes with great documentation.

Pros:

  • The user doesn’t have to pay a single penny.
  • The Engine is very easy to use relatively.
  • Can be used to solve a plethora of problems.
  • It has a great community.
  • The library has been properly documented.

Cons:

  • Does not support web-based and android applications.
  • No customer support via phone.

So this was the list of some of the best AI engines that one can use for development. AI has taken the world by storm by reducing work and capability to perform better than humans. Now we can concentrate on things that are more important for our sustainability. In case, if you are looking forward to get an application made then maybe we can help. To send us an enquiry mail us at sales@agicent.com. In order to read our article on Top Fantasy Football app, click on the link provided. We hope this article may have been of some help to you. Also, thank you for reading until the end.

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