How addressing accumulated technical debt can lead to substantial cost savings and operational efficiencies for your organisation.
DevOps. MLOps. LLMOps. Do IT teams need yet another buzzword? While it may be tempting to think of large language model ops (LLMOps) as a subset of machine learning ops (MLOps), that would prevent us from exploiting the real benefits of building enterprise applications with large language models (LLMs) – scale and speed of development.
Legacy systems are typically challenging for CIOs – they often support critical business processes; they are expensive to replace and increasingly don’t meet business needs. As a result, they have been historically placed into the too hard basket. CIOs with significant legacy issues need to develop a deliberate strategy to address these challenges, rather than the squeaky wheel approach.
Maximise your artificial intelligence (AI) investments by strategically aligning platform choice with your organisation’s AI maturity level.
To truly harness the transformative power of artificial intelligence (AI), enterprises must shift their focus from standalone AI applications to comprehensive AI systems that are deeply integrated into their existing workflows and processes.
6G is set to enable greater mobility speeds, Internet of Things (IoT) and ubiquitous connectivity from 2028–2030, as 3G is turned off.
As large language model (LLM)-based virtual assistants continue to permeate various aspects of enterprise operations, measuring their effectiveness becomes crucial and more complex. The key lies in developing a holistic measurement framework that combines traditional metrics with novel approaches tailored to each specific use case.
Unlock the power of seamless data integration for AI agents, enhancing customer service and operational efficiency.
Discover how Jeena & Company transformed its logistics operations by developing tailored in-house solutions that enhance efficiency and elevate service excellence.
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