Few Diverse Global Players Dominate the Market Holding Majority Revenue Share Despite the Presence of about ~150 Competitors Comprising a Large Number of Country-Niche Players and Some Specialist Players, finds a recent market study on the Global Machine Learning as a Service (MLaaS) Market by Ken Research
Machine Learning as a Service
(MLaaS) is a group of services that provide machine learning (ML) tools as a
component of cloud computing solutions. MLaaS enables customers/clients to
benefit from ML without the associated expense, risk, or time required to build
an internal ML team.
MLaaS is used in processes such
as risk analytics, fraud detection, manufacturing, supply chain optimization,
and others. It offers the freedom to build in-house infrastructure from scratch
and manage and store data. It has a synergistic value in engaging data with the
cloud and can revolutionize a paradigm of ML for a specific result.
"Ken
Research shares 3 key insights on competitive landscape in this high
opportunity market from its latest research study."
Country
Niche Players Constitute ~45% of the Total Number of Competitors, While
Regional Companies Represent a 35% Share of Competitors in MLaaS Market
A comprehensive competitive
analysis conducted during the Research
Study found that the Global Machine
Learning as a Service (MLaaS) market is highly competitive with ~150 players,
including globally diversified players, regional players, and a large number of
country-niche players with their niche in cloud-based solutions for multiple
end-user industries. The majority of the top 12 global cloud-based solution
companies, including Amazon, Google, IBM, Microsoft, Oracle, HPE, SAS
Institution, FICO, Yottamine Analytics, LLC, PREDICTION LABS LTD, BigML, and
ersatz Labs, Inc. are expected to maintain their leading positions during the
forecast period. The majority of the country niche players offer end-to-end
solutions to some IoT platform suppliers who use ML technologies to strengthen
their operating management skills in order to secure rein in vast IoT systems.
IBM, Microsoft, Oracle, HPE, and SAS Institution are among the key players in
the Global Machine Learning as a Service (MLaaS) Market.
Regional
Players' Ongoing Efforts to Provide IoT Solutions to End-User Industries Drive
Their Revenue Growth
Detailed comparative analysis of
key competitors available within the Research Study shows that numerous
ML service providers such as Amazon, IBM, HPE, Google, and others are highly
focused on providing a substantial cloud-based solutions and network security
that can be used across several end-user industries. Furthermore, Numerous
companies and organizations are aggressively investing in advanced technology,
software, and network security activities. Major companies collaborate and
launch products for the development of new technology in ML.
- In November 2021, SAS added support for
open-source users to its flagship SAS Viya platform. SAS Viya is for
open-source integration and utility. The software user established an API-first
strategy that fueled a data preparation process with ML.
- In February 2022 - Telecom giant AT&T and
AI Company H2O collaborated and launched an AI feature for enterprises.
This delivers a repository for collaborating, sharing, reusing, and
discovering ML features to speed AI project deployments and improve ROI.
Increasing
Government Initiatives, Strategies, and Investments in Data Visualization, and
Advanced Machine Learning Propels Market Growth.
- In July 2020, Hewlett Packard released HPE
Ezmeral, a new brand and software portfolio developed to assist
enterprises to quicken digital transformation across their organization,
from edge to cloud. The HPE Ezmeral goes from a portfolio consisting of
container orchestration and management, AI/ML, and data analytics to cost
control, IT automation and AI-driven operations, and security.
- In December 2021, AWS announced six new Amazon
SageMaker capabilities. This makes ML more accessible and cost-effective.
This brings new capabilities, including a no-code environment for creating
accurate ML predictions and more accurate data labeling using highly
skilled annotators.
- In March 2022, Google entered into a
partnership with BT, a British telecommunications company. Under the
partnership, BT utilized a suite of Google Cloud products and
services—including cloud infrastructure, ML and AI, data analytics,
security, and API management—to offer excellent customer experiences,
decrease costs, and risks, and create more revenue streams. Google aimed
to enable BT to get access to hundreds of new business use cases to
solidify its goals around digital offerings and developing
hyper-personalized customer engagement.
In April 2021, Microsoft
Corporation released an open dataset for health & genomics, transportation,
labor & economics, supplementary, population & safety, and common
datasets. This dataset aims to increase the accuracy of machine learning models
using publicly accessible datasets. This also enables businesses to use Azure
Open Datasets with its machine learning and data analytics solutions to offer
insights at hyper-scale, which increases sales of these businesses' ML as a
Service.
For More
Information, refer to below link:-
Machine Learning as a Service Software
Tools Market
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