Global Artificial Neural Network Software Market Overview:
An Artificial Neural Network (ANN) is defined as a bit of computing system that helps to designed and simulate the way human brain analyses and processes information. however, neural network software is mainly used to simulate, research, develop and helps to apply ANN, software concept on biological neural networks. Artificial Neural Network also called as neural networks or simulated neural networks.
Attributes | Details |
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Study Period | 2018-2028 |
Base Year | 2022 |
Forecast Period | 2023-2028 |
Historical Period | 2018-2022 |
Unit | Value (USD Million) |
Customization Scope | Avail customization with purchase of this report. Add or modify country, region & or narrow down segments in the final scope subject to feasibility |
Influencing Trend:
High Adoption of 3D artificial neural network Software
Market Growth Drivers:
Demand for machine learning
Challenges:
Lack of government and compliance issues
Restraints:
High cost of software
Opportunities:
Growing Demand from Applications in areas
Competitive Landscape:
The global market is highly competitive and consists of a limited number of providers who compete with each other. The intense competition, changing consumer spending patterns, demographic trends, and frequent changes in consumer preferences pose significant opportunities for market growth.
Some of the key players profiled in the report are Google (United States), IBM (United States), Oracle (United States), Microsoft (United States), Intel (United States), Qualcomm (United States), Alyuda (United States), Ward Systems (United States), GMDH, LLC (United States) and Starmind (Switzerland). Additionally, following companies can also be profiled that are part of our coverage like NeuralWare (United States), Neurala (United States) and Clarifai (United States). Analyst at AMA Research see United States Players to retain maximum share of Global Artificial Neural Network Software market by 2028. Considering Market by Deployment mode, the sub-segment i.e. On-premises will boost the Artificial Neural Network Software market. Considering Market by Industry Vertical, the sub-segment i.e. Banking, Financial Services, and Insurance (BFSI) will boost the Artificial Neural Network Software market. Considering Market by Component, the sub-segment i.e. Solutions will boost the Artificial Neural Network Software market.
Latest Market Insights:
In October 2020, Qualcomm Technologies announced a laboratory renewal. Qualcomm has teamed up with the University of Amsterdam (UvA) to establish a joint deep vision laboratory called the QUVA lab. Intellectual property, often in collaboration with Qualcomm AI Research, is a solid effort at Qualcomm Technologies with researchers based around the world.
In 2019, IBM announced the first release of Python SDK and Node.js SDK for interacting with IBM’s Cloud Security Advisor service findings Application Program Interface (API) to accelerate the customers’ platform integration with the service.
What Can be Explored with the Artificial Neural Network Software Market Study
Gain Market Understanding
Identify Growth Opportunities
Analyze and Measure the Global Artificial Neural Network Software Market by Identifying Investment across various Industry Verticals
Understand the Trends that will drive Future Changes in Artificial Neural Network Software
Understand the Competitive Scenario
- Track Right Markets
- Identify the Right Verticals
Research Methodology:
The top-down and bottom-up approaches are used to estimate and validate the size of the Global Artificial Neural Network Software market.
In order to reach an exhaustive list of functional and relevant players various industry classification standards are closely followed such as NAICS, ICB, SIC to penetrate deep in important geographies by players and a thorough validation test is conducted to reach most relevant players for survey in Artificial Neural Network Software market.
In order to make priority list sorting is done based on revenue generated based on latest reporting with the help of paid databases such as Factiva, Bloomberg etc.
Finally the questionnaire is set and specifically designed to address all the necessities for primary data collection after getting prior appointment by targeting key target audience that includes Manufactures, Distributors and Suppliers, Venture Capitalists, Government Bodies, Corporate Entities and Government and Private Research Organizations.
This helps us to gather the data related to players revenue, operating cycle and expense, profit along with product or service growth etc.
Almost 70-80% of data is collected through primary medium and further validation is done through various secondary sources that includes Regulators, World Bank, Association, Company Website, SEC filings, OTC BB, USPTO, EPO, Annual reports, press releases etc.