The 10 Best AI/ML Apps to Watch in 2022

7 min readSep 28, 2022

Artificial intelligence (AI) and machine learning (ML) are now mainstream. From smart homes to connected cities, from facial recognition to social media — platforms now widely use AI/ML algorithms to process structured and unstructured data, extract insights and automate actions. The few leaders that I have excluded from the top 10 for 2022 are below:

- TensorFlow is one of the most popular frameworks or machine learning libraries, and the best part is that it is open source. Google’s AI department developed it and now has become a favourite AI tool of the tech giants.

- Meta Platforms is a company that creates artificial intelligence for immersive technology and social media platforms. It is working on several artificial intelligence efforts, ranging from artificial intelligence for normalised interactions in virtual reality settings to detectors for dangerous online material.

- IBM is known for Watson, a proprietary artificial intelligence engine for research and commercial products. It incorporates artificial intelligence (AI) into decision-making, intelligent task automation, and language processing. As a result, Watson incorporates into practically every process, from human resource management to finances & accounting and logistics. In addition, customers may benefit from Watson’s pre-built applications.

As per research by Rackspace, AI/ML is among the top two strategic technologies for companies in 2022 (second only to cybersecurity). Over 7 in 10 organisations use AI/ML as part of their business strategy, IT strategy, or both. So, which are the top 10 AI/ML applications that will make a difference in 2022? Here is my roundup.

1. Keras

Keras is a popular AI framework, a neural network library written in Python just like TensorFlow and CNTK, but unlike them, it is not an end-to-end machine learning framework. Instead, Keras is an API exclusively designed for humans and not machines. Furthermore, it provides a high level of abstraction, making the configuration of neural networks easy regardless of the framework it sits on.

The Python deep learning library is a high-level neural network API that can run on top of TensorFlow, Microsoft Cognitive Toolkit, or Theano. It supports modularity and total expressiveness.

2. Theano

It is one of the best AI development frameworks that use GPU transparently for carrying out data-intensive computations instead of a CPU, resulting in high efficiency in its operations. Theano has powered large-scale computationally intensive operations for the same reason. It is how complicated mathematical expressions requiring repeated and fast evaluation create an ideal environment.

Theano gives intense competition to TensorFlow. Its artificial intelligence tool is a Python library that efficiently defines, optimises and evaluates mathematical expressions involving multi-dimensional arrays.

3. Sci-kit Learn

Sci-kit Learn is one of the Artificial Intelligence open-source tools, a commercially usable AI framework. It is a Python library that supports both supervised and unsupervised machine learning.

Source: Sci-kit Learn

It is one of the multipurpose AI development tools. It supports classification, regression, clustering algorithms, dimensionality reduction, model selection, and pre-processing.

Data scientists can quickly access resources on anything from multiclass and multilabel algorithms to covariance estimation using the extensive user guide offered by sci-kit learn. In addition, Sci-kit Learn has many features, such as cross-validation, which helps check the accuracy and validity of supervised learning. On the other hand, unsupervised learning algorithms techniques are like factoring, cluster analysis, principal component analysis, and neural networks.

The multiple supervised learning models toolkits include — Generalised linear models such as Linear regression, Decision Trees, Support Vector Machines, and Bayesian methods.

The toolkit can help build your models for the real world.

4. WaveNet and AlphaFold by DeepMind

DeepMind is an Alphabet subsidiary that does AI research and development. It also creates artificial intelligence for beneficial results in the healthcare industry. Demis Hassabis, Shane Legg, and Mustafa Suleyman, three British academics, launched the firm in 2010.

The business trained its AI algorithms on vintage games from the 1970s and 1980s to make them more intelligent over time. It creates the WaveNet speech technology that underpins Google Assistant and the Google Cloud Platform. Its AlphaFold technology can analyse 3D models of protein structures to speed up medical research.

5. H2O.ai

H2O.ai is a cloud platform that democratises artificial intelligence via pre-built models, an easy-to-use app store, and low-code development. The firm was founded in 2012 and has received $251.5 million in investment, with a market capitalisation of $1.6 billion.

With its automatic machine learning (autoML) features, the flagship H2O.ai cloud platform enables you to construct AI models and applications. Through the H2O.ai Feature Store, customers may augment their AI applications. In addition, it provides a pre-configured artificial intelligence solution for document management that analyses documents, extracts information, and assists in labelling the collected data.

6. C3.ai

C3.ai delivers corporate AI solutions for data consolidation, AI model building, prediction generation, and execution of pre-built or bespoke applications. Thomas Siebel, an American entrepreneur and businessman, launched C3 in 2009. It provides a model-driven AI application development platform from start to finish. C3 AI Ex Machina is a no-code AI development tool for data scientists. Customers may benefit from a collection of pre-built AI applications for sectors such as manufacturing, finance, and government, as well as verticals such as supply chains and customer service.

7. OpenAI

OpenAI has the support of Elon Musk of Tesla, Samuel H. Altman of YCombinator, Greg Brockman of Stripe, and other AI experts. The program developed by OpenAI is deployable through open-source APIs. It mainly consists of language and code creation powered by artificial intelligence. In 2022, it released InstructGPT, a new learning system.

Its artificial intelligence technology is employed in various popular language analysis apps, including the new language software Duolingo. It works to convert the natural language to code in the context of assisted programming. In addition, OpenAI may be used to solve commercial difficulties involving natural languages, such as intelligent copywriting tools, text categorisation, and translation.

8. SenseTime

AI applications from SenseTime are working in commercial operations, Smart Cities, Smart homes, and Smart automobiles. Tang Xiao and Xu Li, academics at the time, started the firm in 2014. The organisation is a founding member of the Global Artificial Intelligence Academic Alliance (GAIAA). The SenseCore universal AI infrastructure, which comprises a hardware computing environment, a deep learning platform, and a model library, is the foundation for its applications. In addition, it is helpful for content-related activities such as content creation and improvement.

9. Microsoft CNTK

Microsoft Cognitive Toolkit (CNTK) is an open-source and deep learning toolkit. In contrast, it uses a directed graph to describe neural networks as a series of computational steps. As a result, it helps support robust, commercial-grade datasets and algorithms.

This library enhances the maintenance of separating computation networks, providing machine learning algorithms and model descriptions. The toolkit can also build, train, and run many deep neural networks. It has its model description language, BrainScript, and works as a standalone machine-learning tool. Not only that, but CNTK can also work with Python, C++ any .NET language, including C# or Java (model evaluation functionality).

The library has been helpful in AI applications that predict house prices. It offers efficient scalability from a single CPU to GPUs to multiple machines without sacrificing a quality degree of speed and accuracy. In addition, it serves big clients like Skype, Cortana, and Bing.

10. NICE CXone

NICE uses artificial intelligence to improve contact centres, enable predictive decision-making, and assist organisations in better understanding their consumers.

The firm recently revealed its Enlighten AI technology, which automates day-to-day customer-facing duties, alongside CXone SmartReach, a conversational AI technology for proactive customer engagement. It aids in the integration of AI-powered self-service across the customer experience. It also offers AI and machine learning-driven customer experience data to help businesses uncover opportunities and pain spots.

AI/ML is a game changer for businesses due to its ability to process massive volumes of information at lightning speed and apply complex statistical algorithms that can learn and adapt. Further, advancements in hi-tech hardware make computing resources for AI readily available and accessible. For instance, Meta Platforms is working on a cutting-edge supercomputer that will process AI 20x faster than currently possible. These Ten applications have made the most significant strides in AI/ML technology and should be on every enterprise buyer’s watchlist.