AI Expedition- Session 7: Software 2.0

In this new webinar, David discussed the importance of decomposing complex problems into smaller, manageable parts, which he illustrated using the example of the TCP/IP stack and the AWS stack. David also touched on the project management aspect, highlighting the need for a clear project definition, requirements, design, implementation, testing, and maintenance. He then moved on to deep learning, explaining how it revolutionized computer vision in the 1990s. He described how deep learning algorithms can learn their own rules without extensive feature extraction, and how they can be optimized using the scientific method. David also explained the concept of a neural network, where neurons are connections of activations, and how the architecture of a neural network can be determined through experimentation. He demonstrated how a machine learning algorithm can predict data, using a simple example of a line characterized by two parameters. He highlighted the importance of data collection and the role of machine learning in identifying patterns. David Cardoso presented software 2.0, emphasizing the importance of having a baseline and iterating to improve performance. Finally, he also discussed the potential costs of using large language models like Chat GPT and Gemini, advising the benefits and costs.