Ikigai Resources
Learn more about Ikigai and the world of AI with our growing library of resources.
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Data scientist
Developer
Business user
Executive
April 15, 2024
Dealing with structured, numerical and timestamped data is a huge challenge for individual and businesses. AI models urgently need to rise above their limitations and analyse data to create profound, actionable insights. This article considers some of the challenges of current language models.
Data scientist
Developer
Business user
Executive
April 9, 2024
In today's fast-paced and unpredictable business landscape, traditional forecasting and planning methods fall short. Global disruptions, supply chain fluctuations, and ever-changing consumer preferences demand a more adaptive approach. That's where probabilistic forecasting shines.
Report
The Hidden Language of Numbers: How Large Graphical Models Unlock Business Outcomes from Tabular Data
Business user
Data scientist
Developer
Executive
IT
April 4, 2024
Traditional and machine learning methods of forecasting and planning can fall short in today's dynamic - and often uncertain - business landscape. Large Graphic Models (LGMs) address the complexities inherent in tabular and time series data, enabling more accurate analysis and decision making in complex and volatile business environments.
Data scientist
IT
Executive
March 29, 2024
There’s value for LLMs in just about every organization. However, they are limited in their ability to connect disparate enterprise data sources and generate accurate forecasts and scenario-based plans. Ikigai Labs identified that gap and introduced a new generative AI technology designed for predicting business outcomes leveraging tabular and time series data: Large Graphical Models (LGMs).
Business user
Data scientist
Developer
Executive
IT
March 28, 2024
While LLMs are certainly at the forefront of generative AI news, enterprises are quickly finding that they are not the answer to fundamental business planning use cases which depend on enterprise-specific, tabular and time series data.
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