Gleecus Gazette - February 2025
Gleecus TechLabs Inc.
A Forward Thinking Digital Innovation partner creating impactful business outcomes with Technology & Experience.
Dear Readers,
Hope you are in good spirits! We are back with our latest newsletter catching up on the latest trends in digital transformation under the AI race. As AI continues to grow into powerful models that are able to process large amount of data in a short time frame and the market demand for AI models that responds in realtime keeps soaring, the need of a robust infrastructure is imperative. Cloud platforms once again prove to be the trusted partner for such large-scale computing, distribution, and storage solutions. Check out our articles to learn more about the concept of cloud-native AI and the solutions offered by the largest public cloud providers.
Cloud and AI are both large consumers of electricity owing to the gigantic storage and extrinsic computing power that needs to be supported. What if we are utilizing AI for enhancing energy efficiency and optimizing other workflows in the energy sector? Our whitepaper - AI and Energy - Partners for a Sustainable Future – explores the possibilities.
Gleecus Insights
Enterprises are racing around to adopt these two technologies simultaneously – cloud computing and AI. The first offers flexibility and scalability to workload at a nominal cost while the other offers unprecedented scope of innovation. These two technologies are truly blurring the lines between large and small enterprises in terms of technology adoption and creating a level playing field. Our article takes a deep dive into the possibilities of these two technologies benefiting businesses combinedly in the form of a promising tech – Cloud Native AI (CNAI).
The public cloud is characterized by its scalability, flexibility, and accessibility, making it an ideal platform for deploying AI and ML solutions. It creates a level playing field for the SMEs (Small and Medium Enterprises) in the race of becoming an AI-first organization. Public cloud providers have data centers around the world allowing organizations to deploy AI/ML solutions closer to their users. This ensures low-latency access to services and data, improving performance and user experience. Let us explore the AI stack of the three top public cloud platforms AWS, Azure, and GCP.
The growing adoption of ML solutions in the form of LLMs and AI Agents by enterprises underscores the importance of custom ML pipelines. However, the cost of maintaining a team of data scientists and ML engineers can be discouraging for the adoption of new ML use cases by small and medium enterprises. AutoML (Automated machine learning) lowers the entry level barriers for ML exploration and associated resource cost.
Industries that are aggressively adopting IoT devices as a part of their digital transformation plan generate data on the edge of their device network. This data is valuable for training industry-specific models or for driving real-time insights and decision making. The edge to cloud approach ensures that data flows seamlessly between edges, clouds, data centers, and users in a wide variety of work locations and environments. It is a hybrid approach allowing enterprises to leverage the strength of both paradigms.
As AI and ML gets integrated into the various enterprise workflows the demand for shifting from batch processing to real-time data streaming simultaneously burgeons. AI/ML models can process large amount of data at once, also the validity of an insight generated by a model is directly correlated to the freshness of data. In this article, we will explore why it is important to move towards providing high quality data to an AI model from the traditional batch processing leveraging real-time data streaming.
According to Markets & Markets Research, the global healthcare cloud computing market is projected to reach USD 89.4 billion by 2027, exhibiting a CAGR of 17.81%. The healthcare industry is undergoing a significant transformation under the demand to enhance patient care, streamline operations, and drive cost efficiencies fueled through cloud computing adoption. Cloud computing in healthcare seems to be a driver of this change.
Gleecus Innovation
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About Gleecus TechLabs Inc.
Gleecus TechLabs Inc.(ISO 9001:2015 and ISO 20000-1:2018) is a Forward Thinking Digital Innovation Company that empowers businesses to achieve their Digital Transformation goals. We partner with leading Enterprises, SMES and Startups to realize their true digital potential leveraging our deep focus and expertise on Cloud, Data, AI/GenAI, Automation, Product Engineering & Cyber.
FORWARD THINKING is at the core of our business values, our consulting approach, and our internal workforce. This also makes us the right choice for leading organizations of all sizes, on their path for Digital Transformation.
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