In the era of technological advancement, artificial intelligence (AI) platforms have become crucial tools for organizations across industries. These platforms enable the creation, evaluation, implementation, and updating of machine learning (ML) and deep learning models in a scalable way, providing speed and precision that surpasses manual efforts. However, selecting the right AI platform can be challenging, as the wrong choice can lead to increased costs and limited access to valuable tools. To help businesses make informed decisions, it is important to consider various factors when evaluating AI platforms.
What Features Do AI Platforms Offer?
AI platforms offer a wide range of capabilities to streamline operations, make data-driven decisions, deploy AI applications effectively, and gain competitive advantages. These features include:
- Orchestration pipelines for streamlined workflows and increased efficiency.
- AutoML tools for faster model creation.
- Decision optimization for selecting optimal action plans.
- Visual modeling for exploring data and identifying insights.
- Automated development for accelerated AI experimentation.
- Synthetic data generator for addressing data gaps.
Generative AI capabilities:
- Content generator for creating text and other content.
- Automated classification for sorting written input.
- Summary generator for summarizing dense text.
- Data extraction for pulling necessary information from large documents.
Key Benefits of an AI Platform
Implementing an AI platform can provide a range of benefits for businesses, including:
Automation speeds up activities throughout the data lifecycle, leading to greater accuracy and usability of data.
AI platforms enable scalability in training and production phases, facilitating the construction and training of robust models.
AI platforms should offer user-friendly integrations with open-source software and libraries, expanding access to innovative technologies.
AI platforms have various security measures in place to protect data, application endpoints, and identity.
AI governance ensures the ethical and compliant development and implementation of AI models, instilling trust and meeting compliance mandates.
Choosing an AI platform with reliable support resources and a strong user community enables effective troubleshooting and knowledge sharing.
Examples of AI Platform Use Cases
Organizations across industries have successfully integrated AI platforms to address specific challenges:
AI aids in radiology by assisting radiologists in image analysis and interpretation, study prioritization, and recommendations from patient records or clinical guidelines.
AI automates credit assessments, fraud detection, money laundering prevention, and claims processing in the banking industry.
AI enables personalized shopping experiences, superpowered store associates, intelligent workflows, efficient operations center monitoring, and scalable store operating platforms.
AI solutions support predictive maintenance, quality assurance through machine vision, and improved inventory management in the manufacturing industry.
Introducing IBM watsonX
IBM watsonX is an AI and data platform that offers a set of AI assistants to scale and accelerate AI impact with trusted data across businesses. Key components include a studio for building models, a fit-for-purpose data store, and a toolkit for responsible and transparent AI workflows. WatsonX AI assistants empower individuals in organizations to automate tasks in various business processes and applications.
Which AI platforms are widely used?
Major cloud infrastructure providers, such as IBM, Amazon AWS, Microsoft Azure, and Google Cloud, offer AI platforms as part of their offerings.
What other factors should be considered when choosing an AI platform?
In addition to the features and benefits mentioned earlier, pricing, deployment strategy (on-premises or cloud), and intended usage (internal or external) should also be considered.
How can AI enhance industry-specific applications?
AI can bring automation, efficiency, and advanced analytics to various industry-specific applications, such as healthcare, finance, retail, and manufacturing.
What role does security play in AI platforms?
Security measures, including network security, data security, and collaborator security, are vital to protect against unauthorized access, cyberattacks, and breaches.
How can an AI platform contribute to governance?
An AI platform with governance capabilities helps improve collaboration, coordination, and compliance in model approvals, monitoring, and data standardization.
What kind of technical support should be expected from an AI platform?
An AI platform should provide assistance with training, bug reporting, issue resolution, and emergency response. A strong user community and support resources are also valuable for troubleshooting and knowledge sharing.