Top 20 Artificial Intelligence Platforms for 2024
As a new decade starts, much is expected to change in the world of artificial intelligence. During the last decade and beyond, AI technology proved its abilities to even the most fervent critics. Aspects of artificial intelligence, such as machine learning and natural language processing, have been incorporated in many important areas of daily living today that we can no longer live without them.
As for data scientists and other software engineers that build AI projects, the one thing they can’t do without is an artificial intelligence framework. A long list of top AI platforms has been providing this service, and that includes some of the best machine learning and NLP application examples ever (think TensorFlow, Matlab, etc.)
But in 2024, as new updates and improvements take over the field of AI, the ranking of these AI platforms will have to shift. We look at the 20 best artificial intelligence platforms for 2024, and why we think they deserve to be on the list.
1. Google Cloud AI Platform
Google’s Cloud AI platform simply deserves to be on the top of the list. Most of the other platforms below refer to it in one way or another. Millions of users love it for its ease of use, its unique models, its incredible cloud infrastructure, its architecture, its stunning visual interfaces, its library and more.
Organizations looking to further streamline their machine learning and enterprise AI needs can only do worse without the Google Cloud AI platform.
2. Salesforce Einstein
It’s no small honor to be considered one of the best customer service software providers by many companies in the US. Salesforce knows how that feels like thanks to supplying some of the most popular customer service tools ever. The company’s foray into AI will be supported further in 2022 with its own AI platform ‘Salesforce Einstein.’
It is described as being very good at predictions and very spot-on with recommendations, basing on provided data.
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3. IBM Watson Studio (plus IBM Watson Machine Learning Studio)
IBM’s Watson Studio has been an industry leader in the machine learning space and a top choice for enterprise AI solutions everywhere.
The IBM Machine Learning Studio makes it simple to create, train and deploy processes of models through automation and collaboration. IBM’s AI platforms are, therefore worth a look in 2022, as they promise to get even better.
4. Microsoft Azure (plus Microsoft Machine Learning Studio)
From the software giant, Microsoft comes Microsoft Azure Machine Learning, an AI platform that has fast become popular for its enterprise solutions to practical problems. Microsoft Azure Machine Learning specializes in machine learning and the way it can be simplified for business enterprise problems.
Data scientists that employ Microsoft Azure can model their algorithms from Python packages, Xbox, or even R to create instantly deployable web services. Some of its most attractive perks include its cloud-based options, its mobile option and its ability to support most tools, languages and frameworks.
TensorFlow has been a popular AI platform for the last decade or so and will remain popular even in 2022. As one of the best open-source libraries around for machine learning and other aspects of artificial intelligence, it’s easy to see the attraction. But TensorFlow is more than just a cool AI platform.
As one of the many products of Google’s Machine Intelligence Team, TensorFlow is designed for machine learning and neural networks research. Its data flow structure employs mathematical equations and graphs to create an architecture that works wonderfully for computation across platforms.
If you’re new to TensorFlow, you’ll love its flexibility across a wide range of AI solutions, its deep learning framework, its portability and more.
For 2020, organizations already using the Pega AI platform can rest assured knowing they’ll derive more efficiency and automation than they already have.
Pega is a wonderfully built platform designed to make simple the design of applications or programs in the AI space. Users build their own using proven models and can always make swift changes thanks to the agility and flexibility of the platform.
Spark NLP is barely three years old, but it is already one of the most popular open-source AI platforms to consider.
Its emphasis is on natural language processing and it comes with one of the biggest libraries and various NLP examples for data scientists to refer to. It’s built upon Apache Spark and TensorFlow, so its architecture is impressive too.
8. Infosys Nia
Among data scientists today, Infosys Nia and its system offerings are the stuff of legend. Ask one and they’ll highlight its unique core business renovation processes or its deep understanding of people in unique fragments. Its automation, knowledge and information platforms are some of the most referenced in the machine learning world.
Its Aikido framework remains one of the most cost-effective, and many users report it to be an easy AI platform to use. For many enterprises in 2022, Infosys Nia will remain a favorite, thanks to its ability to deploy machine learning’s attributes for more innovation and automation.
9. Rain Bird
In 2022, one artificial intelligence platform to watch out for is Rain Bird, the award-winning software designed to make business operations smarter and more efficient. Rain Bird is the AI platform of choice for enterprises looking to automate the knowledge-work process for efficiency.
It works by enabling the creation of smart systems that are derived from a combination of business data and existing business information. Users love it for its RBLang language, unique analytics, its controlled learning algorithms and helpful visual user interface.
10. Wipro HOLMES
Wipro HOLMES is Wipro’s Artificial Intelligence (AI) and automation platform, is the bridge between Foundational AI algorithm builders and Applied AI. HOLMES Platform handles all your needs from building, publishing, metering, governance to monetization of heterogenous AI solutions. The offerings of HOLMES have been successfully deployed across industry verticals and functions driving the 3E’s – Efficiency, Economics and Experience.
11. Amazon AI Services
Among the key players in the Artificial Intelligence and cloud computing industry, Amazon has an extensive list of services that businesses can utilize to not only gain better insights into their customers but also simplify a broad range of their regular tasks.
Some of the services offered by Amazon AI include getting personalized recommendations, extracting data from physical copies of documents, generating forecasts using Machine Learning, user identity verification, translation services, and much more. With these services at your disposal, you can be sure to gain advanced analytics and make better decisions.
H2O is another AI platform dedicated to making businesses aware of the numerous benefits of Artificial Intelligence and Machine Learning by giving them access to these services. With its open-source tools, H2O powers major industries in the market, like healthcare, finance, telecommunications, retail, marketing, pharma, and several others.
Symphony AyasdiAI is the world’s leading enterprise platform for automated business value discovery and advanced AI-based insights. Financial services, pharmaceutical research, global intelligence, and telecommunications enterprises rely on Symphony AyasdiAI to revolutionize the discovery of risk and profitability opportunities.
The MindMeld Conversational AI Platform is a Python-based machine learning framework which encompasses all of the algorithms and utilities required for building production-quality conversational applications. Evolved over several years of building and deploying dozens of advanced interfaces, MindMeld is optimized for building conversational assistants which demonstrate deep understanding of a particular use case or domain while providing highly useful and versatile conversational experiences.
15. Vital AI
Vital A.I. provides artificial intelligence software development tools and consulting services. The Vital Development Kit (VDK) addresses the largest source of cost when developing Intelligent Applications – the human labor of data integration – managing the flow of data across people, devices, databases, and data streams of algorithmic processing.
Receptiviti enables AI platforms with emotional intelligence. Receptiviti is a social psychology and data science technology platform that utilizes language, social psychology, and artificial intelligence to uncover insights about people that power predictive models, inform decisions, and optimize interpersonal interactions.
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Lumiata is AI platform for healthcare. Groundbreaking predictive analytics starts with machine learning tools and applications that are custom-built for healthcare. Lumiata is ushering in a new era for teams core to the business and delivery of healthcare –– underwriting, actuarial, care managers, and pharmacists. Lumiata’s superior cost and risk predictions consistently outperform legacy methods. Lumiata is modernizing how risk and care are managed across healthcare.
Infrrd is an award-winning AI firm focused on applying machine learning to improving business processes. The company’s platform employs next-generation AI capabilities to help enterprises transform their businesses. Proprietary technology removes bottlenecks caused by manual data entry and unlocks data from complex documents to power digitization.
Infrrd’s unique ML-first approach can automatically extract data from documents with complex visual elements, surpassing OCR’s performance limitations to help you maximize straight-through processing.
BigML development platform offers robust ML algorithms, both for supervised and unsupervised learning to automate predictive modelling tasks. Software developers can implement instant access to the BigML platform using its REST API, both on-premises and on the cloud. BigML is highly programmable and repeatable, and lets software developers use popular languages like Ruby, Java, Python, Node.js, Swift, etc. to code and scale-up their applications.
Petuum develops the Symphony platform, which is designed to don’t-make-me-think AI work. In other words, if you’re tired of coding and/or don’t want to memorize more libraries and output formats, Symphony will feel like a vacation in the Alps!
A good artificial intelligence platform makes things easier for both designers and the enterprises that use the resulting application. A good AI intelligence platform means your enterprise will make its best bets on big business without unnecessary doubts.
Good intelligence platforms for AI also means better frameworks and bottom-less libraries, plus smarter NLP application examples and smarter machine language development. If you’re thinking of choosing an AI intelligence platform this year or just upgrading from one platform to another, these above platforms have the most potential for 2023.