TLDR:
– Artificial intelligence (AI) is the theory and development of computer systems that can perform tasks requiring human intelligence.
– AI has been around since the 1950s but has become more popular due to advancements in data volumes, algorithms, computing power, and storage.
The article provides a brief history of AI, starting with neural networks in the 1950s. Neural networks are interconnected nodes that mimic the human brain’s processing. They can recognize patterns, classify data, and continuously learn and improve over time. Neural networks are now used in various industries such as life sciences, manufacturing, banking, public sector, and retail.
Machine learning, a subfield of AI, focuses on building systems that improve their performance based on the data they consume. It has been used in applications such as self-driving cars, facial recognition, and online recommendation offers. Machine learning is used in industries such as financial services, government, healthcare, retail, oil and gas, and transportation.
Deep learning is a subset of machine learning that trains computers to perform human-like tasks using layers of processing. It has applications in retail, banking, manufacturing, healthcare, government, transportation, and logistics.
Generative AI is focused on creating new and original content, chat responses, designs, synthetic data, and deepfakes. It uses existing data to learn and generate data with similar characteristics. Generative AI is being used in industries such as banking, insurance, life sciences, manufacturing, retail, and the public sector.
The article emphasizes that AI has the potential to boost productivity and mentions that the global market for generative AI is expected to reach $110.8 billion by 2030. However, it also highlights the mixed feelings of excitement and fear associated with generative AI. It is important to avoid automation bias when interacting with conversational AI systems.