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Top 8 AI Development Platforms Tools

Microsoft Azure Machine Learning StudioTensorFlowOpenVINOPyTorchIBM Watson Machine LearningCaffeGoogle Cloud AI PlatformAmazon Augmented AI
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    Azure's AutoML feature is probably better than the competition.I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model.
  2. leader badge
    Edge computing has some limited resources but TensorFlow has been improving in its features. It is a great tool for developers.It is open-source, and it is being worked on all the time. You don't have to pay all the big bucks like Azure and Databricks. You can just use your local machine with the open-source TensorFlow and create pretty good models.
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  4. The initial setup is quite simple.The inferencing and processing capabilities are quite beneficial for our requirements.
  5. I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code.
  6. It is has a lot of good features and we find the image classification very useful.The most valuable aspect of the solution's the cost and human labor savings.
  7. Caffe has helped our company become up-to-date in the market and has helped us speed up the development process of our projects.
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  9. Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture.

AI Development Platforms Articles

Sojy Sn
Marketing and Communication Specialist at ZiniosEdge
May 10 2021
The success stories of large business organizations do not happen in a day but are the results of optimized management of business operations, HR practices, robust internal auditing practices, and much more. Among the essentials for a successful organization, internal auditing plays a vital role… (more)

The success stories of large business organizations do not happen in a day but are the results of optimized management of business operations, HR practices, robust internal auditing practices, and much more. Among the essentials for a successful organization, internal auditing plays a vital role as it gives the in and out conditions of the business, like profitability, operation constraints, decision making, opportunities, and similar traits. Expert and experienced internal auditors handle such organizations to give fruitful results to the management. But there is always a scope of human error which may creep into internal audit reports and even a small, missed opportunity may become fatal for an organization. With the advancement of technology, Artificial Intelligence is finding its way into all aspects of our life and internal auditing is not an exception.

What is AI? Role of AI in Internal Auditing

Artificial Intelligence makes use of machine learning, deep learning, and NLP technologies by which a set of algorithms is formed. This governs all the internal processes of the business, collects all the data, analyses it, and draws patterns to give value-added reports regarding profitability, business constraints, risk assessments, periods of high and low and more. NLP along with other capabilities helps in reading and comprehending vast amounts of texts in loads of documents. These business documents are then classified into different types for data extraction and analysis.

Advantages of Use of AI in Internal Auditing

  • Error Free Auditing
  • Speeding up the Auditing Process
  • Data Collection and Analysis Reports
  • Useful Data Insights
  • Segregation of Data
  • Improved Coverage
  • Increased Efficiency
  • Aid for Internal Auditors

Challenges at Present to Adopt AI in Internal Auditing

Technology is critical for increasing the productivity and efficiency of the internal audit functions. According to an excerpt from the 2017 International Standards for the Professional Practice of Internal Auditing: “Internal auditors must have sufficient knowledge of key information technology risks and controls and available technology-based audit techniques to perform their assigned work” With reference to the Bryden Report of 2019, there is an increased line of separation among clients and auditors and companies are changing auditors often. So, automating existing data for audit tasks is underway and inevitable.

To Conclude

Internal auditing using AI is the necessity of modern-day organizations and is a must for achieving efficiency in auditing and to get fruitful insights and reports. It will surely help organizations to achieve their full potential in their respective fields.

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Find out what your peers are saying about Microsoft, TensorFlow, OpenVINO and others in AI Development Platforms. Updated: October 2021.
542,721 professionals have used our research since 2012.