In today’s world, businesses are expanding beyond their limits by leveraging Artificial Intelligence (AI), a technology that has the power to automate and revolutionize businesses, enabling them to stay ahead in the global market. Artificial Intelligence (AI) has the potential to influence every facet of the business world, including sustainability, education, entrepreneurship, oil and gas, energy, and various other domains.
In this article, let’s explore the democratization of AI, a concept that empowers all industries to access AI technology frameworks, models, and user-friendly data tools, and how you can seamlessly transform every aspect of your business operations, contributing to a more sustainable world.
Exploring the Concept of AI Democratization
According to a Gartner study, it’s anticipated that 80% of enterprises will have integrated AI by 2026. However, even large companies struggle to effectively incorporate AI technology and machine learning (ML) algorithms due to the lack of expertise and optimization of the appropriate AI solutions.
AI democratization refers to creating an AI ecosystem where individuals can effortlessly access and analyse vast data sets in real time without any knowledge of coding or relying on training.
AI democratization enables you to incorporate AI technology at all levels of your business and experience the benefits of AI capabilities without any specialized training in AI technology.
Increasing the accessibility of AI frameworks and models into more hands enhances the potential of what businesses can achieve. Democratization of AI eliminates the scepticism surrounding its use by empowering you to upskill your employees and increase productivity.
Understanding the Integration of AI Software and Hardware
To successfully deploy AI projects in businesses requires fundamental hardware infrastructure to support AI-driven application solutions and data processing. Integrating AI software and hardware enables the efficient execution of complex algorithms and facilitates optimal performance and functionality.
Partnering with Lenovo, one of the world’s leading PC makers, nybl develops customized and performance-optimised AI ecosystems for various industries such as oil and gas, healthcare, physical and cybersecurity, fintech, and retail.
Lenovo’s purpose-built AI portfolio includes AI hardware solutions ranging from workstations tailored for data scientists to gateways for IoT to powerful GPU-accelerated Edge servers for high-performance computing.
Reducing Data Centre Power Consumption
AI and ML applications use graphic processing units (GPUs) to accelerate the computational tasks, however, they generate enormous amounts of heat, necessitating efficient management of these heat loads.
The use of decentralised AI facilitates decreasing the power consumption of data centres. Distributing computational tasks across multiple nodes instead of relying on centralized servers minimizes the workload on individual systems, leading to more efficient energy utilization and cooling of data centres. It enhances sustainability efforts, contributes to cost savings, and improves environmental impact in data management and processing.
Right Tools and Frameworks Businesses Can Make AI More Accessible
By employing the right AI tools and frameworks like machine learning operations (MLOps), Kubernetes, and TensorFlow, businesses can overcome the technical and skill barriers associated with generating and integrating machine learning algorithms and AI applications for their own business models.
nybl’s AI software product, known as nubyla.ai, allows businesses to leverage optimised ML algorithms to facilitate the management of comprehensive data processing from a single AI platform and predict market trends and challenges without requiring expertise in AI.
Consistency of AI Software Applications Across Different Industries
Although AI has tremendous potential, the consistency of building and utilising AI and ML platforms remains uncertain. Data variability is a significant challenge in maintaining consistency, as different industries generate different data types. For instance, an AI software application designed for data processing in the financial sector may not be suitable for handling datasets in the healthcare industry.
The concerns regarding accountability, data privacy regulations, performance requirements, and other factors across various industries require personalized attention and tailored solutions.
Wrapping Up
AI is evolving and has the potential to disrupt every industry. In order to sustain and keep up with the market trends, every industry must gradually adapt to these changing dynamics. At nybl, enabling various industries to scale and experience the benefits of AI and Machine Learning is an unquestionable priority and the strategic integration of AI with compatible hardware stands as a crucial stride towards realizing this vision.
