Machine Learning Systems by
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What does it mean to master machine learning systems—not just design models?
Machine Learning Systems
a discipline that combines the science of learning with the practical realities of deployment at scale on infrastructure.
It extends beyond model development to encompass the full lifecycle of intelligent systems—from data to deployment, from theory to engineering practice.
It’s used for building AI systems that are powerfull, realiable, efficient and grounded in the real-world constraints.
What are the AI Systems Pervasiveness in Human History, Today ?
19th century - Industrial Revolution shaped by Power of physical energy through steam power and mechaization transfromation
20th centuray - Digital Revolution, where the computer and internet transformed how we process and share information.
21th century - AI Revolution, according to leading thinkers in tech evolutions.
AI Systems
- Manages traffic flows in Cities
- Optimize power distribution across electical grids
- Enable billions of wireless devices to communicate seamlessly.
- Helps doctors to diagnose diseases, via providing insight from anaysis of medical images.
- Accelerates scientific discovery by simulations and processing of vast amount of scientific data in research labs.
- Helps rovers to nevigate distant planets and telescopes to detect new celestial object or events, in space exploration.
We aspire to create systems that can work alongside humanity, enhancing our problem-solving capabilities and accelerating scientific progress.
Systems that understand consciousness, decode the complexities of complex biological systems or uncover the mystries of dark matter and dark energy.
Systems that can help adressing global challenges like climate change, disease or sustainable energy production.
Thus, Build AI systems is not only about automation or efficiency but it’s also about how boundaries of human knowledge and capabilities can be expanded ?
AI Revolution operates at multiple scales Thus, poses multiple implications today such as
- Individual Level -
- Organizational Level -
- Societal Level -
- Government Level -
- Global Level -
AI Revolution Challenge - Learning to Master, how to build systems that can learn, reason and potentially achieve superhuman capabilities in specific domains.
What are the fundamentals of AI and ML Systems ? How can we create these intelligent capabilities ? We first needed to understand the relationship between AI and ML Systems that provides not only theoretical but also practical framework to adress such questions.
AI Systems - Understand and replicate intelligent behaviour such as capcity to learn, reason and adapt new situations.
AI : Nature of Intelligence, Knowledge and Learning How do we recognize patterns ? How do we learn from experiance ? How do we adapt our behaviour based on new information ?
Explores these questions in different fields such as cognitive science, psychology, neuroscience and computer science.
ML Systems - Creating systems that demonstrats intelligent behaviour. Building systems that utilizes data and optimization techniques to identify patterns and relationships automatically rather than some predefined set of rules.
Biological Systems <=> ML Systems
- Human Visual Learning Process - Object Recognition
- Human Language - NLP to process textual data