Welcome to the Parallaxis Blog
Explore our latest thoughts on all things related to AI, Machine Learning, and the importance of data .
Find by Tag
- AI 4
- AI4Dev 2
- BusinessValue 3
- CitizenCoder 1
- CitizenDeveloper 3
- Cloud 1
- Community 3
- Compliance 1
- DataEthics 2
- DataFitness 3
- DataGovernance 11
- DataManagement 7
- DataMesh 5
- DataMess 4
- DataScience 9
- DataSwamp 5
- DataWarehouse 3
- DevOps 1
- GDPR 1
- InfrastructureAsCode 4
- MLOps 2
- MachineLearning 6
- Metrics 2
- ModelDevelopment 2
- ModelEvaluation 2
- ModelTraining 2
- PII 1
- PlatformEngineering 1
AI - The Rote Machine
AI's perceived intelligence is often overstated. It is only as “intelligent” as the data it's trained on. Poor quality and unfit data lead to “incorrect”, unsupported, and potentially reputational affecting decisions. Actual progress in AI requires a relentless focus on data fitness, quality, governance, and fairness.
5 Key Indicators That AI Isn't The Answer
This post outlines five key considerations for deciding whether to pursue AI: the existence of clear rules, data volume and variability, significant regulatory requirements, static environments, and unclear ROI. AI should be a multiplier for disciplined thinking and well-designed processes, not a replacement. Focusing on data quality and automation maturity should precede any AI adoption.
The Illusion of Just Knowing
Introducing AI/ML in your business emphasizes the importance of data for understanding business operations and driving growth. Relying on assumptions hinders progress and creates an illusion of competence. The document advocates metrics, experimentation, and the scientific method to create a data-driven approach to doing business.