Jul 19, 2021

Top 10 AI platforms

AI
Technology
Companies
Data
6 min
AI is continuing to enhance economies across the globe, we take a look at 10 of the top AI platforms

AI is continuing to have a huge impact on the global economy, so we’ve assembled a list of ten of the premier AI platform offerings, taking a closer look at their capabilities in different areas.

1. Google

 

 

Platform: Google Cloud AI

CEO:  Sundar Pichai

Founded: 1998

HQ: Mountain View, California, United States

Employees: on LinkedIn at time of publishing

Follow:  FB / LI / Twitter

Description: 

Google AI Platform allows for the creation of applications that run on both the Google Cloud Platform and on-premises. It targets machine learning developers, data scientists and data engineers with an easier route from the ideas to the production stage, thanks to its flexibility and support for other Google platforms such as Kubeflow.  

With native support for other Google AI products such as TensorFlow, Google’s solution promises an end-to-end approach, with everything from preparing data to validation and deployment contained under one umbrella.

 Fast Facts:

  • In the most recently reported fiscal year, Alphabet's (Google’s parent company) revenue amounted to 182.5 billion U.S. dollars, up from close to 162 billion U.S. dollars in the previous year
  • In the most recently reported fiscal year, Google's revenue amounted to 181.69 billion US dollars.

 

2. Amazon

 

Platform: Amazon AI services

CEO: Andy Jassy

Founded: 1994

HQ: Seattle, WA

Employees: 685,161 on LinkedIn at time of publishing

Follow:  FB / LI / Twitter

Description: 

Amazon emphasises the accessibility of its services, and the potential to add AI to applications without any machine learning skills required.

Amazon touts the capabilities of its advanced machine learning in fields such as video analysis, natural language, virtual assistants and more to enable businesses to get the same level of insight via AI that Amazon itself does. 

Fast Facts:

  • According to recent industry figures, Amazon is the leading e-retailer in the United States with close to 386 billion U.S. dollars in 2020 net sales



 

3. Microsoft

 

Platform: Microsoft Azure AI

CEO: Satya Nadella

Founded: 1975

HQ: Redmond, Washington

Employees: 206,630 on LinkedIn at time of publishing

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Description: 

Microsoft’s AI platform integrates with its Azure cloud product, which it says is suitable for mission-critical solutions. Enabling features such as image analytics, speech comprehension and prediction, Microsoft’s solution claims to be useful for all developers, from data scientists to app developers and machine learning engineers. 

Part of its offering is based around an ethical and responsible approach to AI, with systems to mitigate bias as well as ensure confidentiality and compliance.

 

Fast Facts:

  • In 2021, Microsoft’s global brand value exceeded 410 billion U.S. dollars

 

4. H2O.ai  

 

 

Platform: H2O.ai 

CEO: Sri Satish Ambati

Founded: 2012

HQ: Mountain View, CA

Employees: Around 201-500 employees

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Description: 

H2O.ai describes its mission as being the democratisation of AI and machine learning for everyone. With an open source platform, the company claims to be used by hundreds of thousands of data scientists in over 20,000 organisations across the world, in industries such as financial services, healthcare, retail and insurance.  

The Mountain View, California-based business has raised over $150mn since its 2012 foundation, with its latest Series D in 2019 raising $72.5mn.



 

5. IBM

 


 

Platform: IBM Watson Studio

CEO: Arvind Krishna

Founded: 1911

HQ: Armonk, New York, NY

Employees: 533,006 on LinkedIn at time of publishing

Follow:  FB / LI / Twitter

Description: 

Operating on any cloud system, IBM’s Watson Studio allows for the building and training of AI models. It is one of the core services of IBM Cloud Pak for Data, a multicloud data and AI platform. Together with IBM Watson® Machine Learning and IBM Watson® OpenScale™, Watson Studio provides tools for data scientists, application developers and subject matter experts to collaborate and easily work with data to build, run and manage models at scale.

 

Fast Facts: 

  • You can deploy IBM Cloud Pak for Data in your private clouds (inside the firewalls), hybrid clouds, Amazon Web Services (AWS), Microsoft Azure and Google Cloud
  • In 2020, the revenue of IBM reached more than 73 billion U.S. dollars

 

6. Google Brain team

 

 

Platform: TensorFlow

CEO: Sundar Pichai

Founded: 2015

HQ: Mountain View, California

Employees: Unknown

Follow:  Twitter

Description: 

TensorFlow is a machine learning platform developed by Google and later released on an open source basis. It makes clear its end-to-end nature, facilitating all stages of machine learning from model building with high-level APIs, deployment whether on the cloud, on-premises, in a browser or device and taking ideas from the conceptual to the code level thanks to its flexible architecture.

The platform includes different libraries for its various deployment settings, with a lightweight version for mobile and IOT deployments.

Fast Facts: 

  • You can use it for voice recognition, sentiment analysis, language detection, text summarisation, image recognition, video detection, time series, and more.

 

7. DataRobot

 


 

Platform: DataRobot

CEO: Dan Wright

Founded: 2012

HQ: Boston, Massachusetts

Employees: 1,417 on LinkedIn at time of publishing

Follow: FB / LI / Twitter

Description: 

 

The DataRobot enterprise AI platform accelerates and democratises data science by automating the end-to-end journey from data to value. This allows you to deploy trusted AI applications at scale within your organisation. DataRobot provides a centrally governed platform that gives you the power of AI to drive better business outcomes and is available on your cloud platform-of-choice, on-premise, or as a fully-managed service.

Fast Facts: 

  • 1.4m person-hours of engineering innovation building the product
  • 1000+ total years of data science experience on customer-facing data science team

 

 

 

8. Wipro Holmes

 

 

Platform: Wipro Holmes AI and automation platform

CEO: Manoj Madhusudhanan

Founded: 1945

HQ:  Bangalore, Karnataka

Employees: 239,842 on LinkedIn at time of publishing

Follow:  FB / LI / Twitter

Description: 

Wipro is a leading global information technology, consulting and business process services company, who harness the power of cognitive computing, hyper-automation, robotics, cloud, analytics, and emerging technologies to help clients adapt to the digital world and make them successful.

The Wipro Holmes AI and automation platform promises to cover all aspects of deploying an AI solution, from building to publishing, metering, governing and monetising, and is offered on a software-as-a-service (SaaS) basis. Among its features are digital virtual agents and process automation, as well as support for robotics and drones. 

Fast Facts: 

  • Over 200,000 employees
  • Serving clients across six continents

 

 

9. Salesforce

 

Platform: Salesforce Einstein

CEO: Marc Benioff 

Founded: 1999

HQ: San Francisco, California, United States

Employees: 52,862 on LinkedIn at time of publishing

Follow:  FB / LI / Twitter

Description: 

Founded in 1999 by internet entrepreneur Marc Benioff, Salesforce is a leader in the customer relationship management space. 

Salesforce Einstein was specifically built for Salesforce’s CRM solution and fills the platform with AI capabilities to enable possibilities such as identifying patterns and trends in customer data. That in turn enables companies to better understand their customers in order to deliver more personalised forms of customer service. 

Fast Facts: 

  • Salesforce has helped 150,000+ companies
  • In 2020 Gartner ranked Salesforce #1 in CRM for the 8th year in a row

 

 

10. Infosys

 

 

Platform: Infosys Nia

CEO: Salil Parekh

Founded: 1981

HQ: Bengaluru, India

Employees: 249,713 on LinkedIn at time of publishing

Follow:  FB / LI / Twitter

Description: 

Infosys Nia is offered by Indian IT multinational Infosys’ subsidiary EdgeVerve. The product supports end-to-end enterprise AI journey from data management, digitisation of document and images, model development to operationalising models.

One of its specialisations is in the automatic digitising of documents in order to unlock the data contained within. EdgeVerve itself is a leader in robotic and intelligent process automation via its AssistEdge platform.

Fast Facts: 

  • 50+ countries where they have trusting clients
  • 106,000 employees trained in new skills

 

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Aug 2, 2021

ManageEngine Survey Finds Global AI Use Increase

AI
manageengine
Data
Analytics
3 min
A global survey by ManageEngine found more than ever before, IT personnel are relying on AI-based tools and analytics to inform their business decisions

ManageEngine, the enterprise IT management division of Zoho Corporation, has announced results from its recent market study, The 2021 Digital Readiness Survey, finding that 86% of organisations worldwide are using artificial intelligence (AI) more than they did two years ago. However, only 35% of the global respondents reported that their confidence in the technology has significantly increased.

The focus of the study was to understand technological changes in a post-COVID world, in areas such as remote work, security, business analytics, and AI. It was found that organisations worldwide mainly increased their use of AI to improve business analytics (63%), increase operational efficiency (62%) and enhance the customer experience (60%). While a majority of global respondents (94%) believe that AI will meet business expectations—and 65% stated AI had delivered measurable business results—some fears remain around the technology’s performance.

“The potential for AI to improve business efficiency and the customer experience was firmly on show through 2020, with AI handling everything from increased customer service volumes to oversight of self-service processes,” said Rajesh Ganesan, vice president at ManageEngine. “While AI is being handed more responsibility and is applied in more business-critical use cases, our research shows this is a double-edged sword and that more work is needed to embrace the technology and lift internal capability to ensure AI achieves its promise.”

 

Is business analytics the key to success?

 

The growing use of AI coincides with a broader trend of using analytics to improve the use of available data and the speed and accuracy of decision-making. In the post-pandemic era, profitability and competition are also driving organisations across the world to invest in business analytics platforms and capabilities.

Business analytics is an umbrella term for several types of analytics—descriptive, diagnostic, predictive and prescriptive. 

The biggest user of business analytics by far is IT. An average of 63% of IT departments worldwide cited this in the survey. However, in North America, 67% of executives noted their use of business analytics, which was higher than their IT departments’ use (61%). Business areas such as marketing, sales, human resources, operations and R&D are also showing interest in business analytics but are well behind IT and executives on adoption and actual use.

 

Other key global findings of the survey

 

– A mighty 96% of organisations are planning to continue supporting remote workers for the next two years. Concerningly, the report also found that 84% of IT professionals believe that remote workers have increased their enterprise’s security risk. 

– More than half (56%) of respondents stated that improving their security infrastructure is a key driver of adopting new technologies.

– 78% of organisations revealed that remote workers download software without obtaining approval from the IT department; this shadow IT mainly included mobile-specific applications (40%), online meeting tools (38%) and document sharing solutions (31%).

– 84% of respondents use more cloud services now than they did before the pandemic began. However, most respondents believe that improved security (56%), performance (52%) and reliability (51%) would increase their company’s confidence in cloud-based solutions.

 

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