Back in the 2000s, code lived in one execution thread. Database queries, user interactions, and data pipelines were all managed by the same processes. The problem? Everything was interconnected and interdependent. Fixing one thing might break another. Releases were all or nothing. We call this monolith hell. Your ticket out? Microservices.

Back in the 2000s, code lived in one execution thread. Database queries, user interactions, and data pipelines were all managed by the same processes. The problem? Everything was interconnected and interdependent. Fixing one thing might break another. Releases were all or nothing. We call this monolith hell. Your ticket out? Microservices.

Back in the 2000s, code lived in one execution thread. Database queries, user interactions, and data pipelines were all managed by the same processes. The problem? Everything was interconnected and interdependent. Fixing one thing might break another. Releases were all or nothing. We call this monolith hell. Your ticket out? Microservices.

Are we in an AI bubble? We can't stop talking about AI in tech. It's at every conference and in every startup pitch. But is the rest of the world as enamored as we are? In this conversation, we explore AI’s impact beyond the echo chamber of the tech industry. We look at attitudes toward AI in other spaces, from healthcare to finance, weighing the risks and benefits of its application. We also look to the future, questioning whether we’ve reached the limits of AI given compute power constraints.

Are we in an AI bubble? We can't stop talking about AI in tech. It's at every conference and in every startup pitch. But is the rest of the world as enamored as we are? In this conversation, we explore AI’s impact beyond the echo chamber of the tech industry. We look at attitudes toward AI in other spaces, from healthcare to finance, weighing the risks and benefits of its application. We also look to the future, questioning whether we’ve reached the limits of AI given compute power constraints.

Are we in an AI bubble? We can't stop talking about AI in tech. It's at every conference and in every startup pitch. But is the rest of the world as enamored as we are? In this conversation, we explore AI’s impact beyond the echo chamber of the tech industry. We look at attitudes toward AI in other spaces, from healthcare to finance, weighing the risks and benefits of its application. We also look to the future, questioning whether we’ve reached the limits of AI given compute power constraints.

Are we in an AI bubble? We can't stop talking about AI in tech. It's at every conference and in every startup pitch. But is the rest of the world as enamored as we are? In this conversation, we explore AI’s impact beyond the echo chamber of the tech industry. We look at attitudes toward AI in other spaces, from healthcare to finance, weighing the risks and benefits of its application. We also look to the future, questioning whether we’ve reached the limits of AI given compute power constraints.

Are we in an AI bubble? We can't stop talking about AI in tech. It's at every conference and in every startup pitch. But is the rest of the world as enamored as we are? In this conversation, we explore AI’s impact beyond the echo chamber of the tech industry. We look at attitudes toward AI in other spaces, from healthcare to finance, weighing the risks and benefits of its application. We also look to the future, questioning whether we’ve reached the limits of AI given compute power constraints.

Imagine a world where every piece of digital content can be verified and traced back to its source. Lindsay Walker, Product Lead at Starling Lab for Data Integrity, walks us through the emerging tools that could make this possible. While AI tools hold incredible potential for good, Lindsay also warns against threats and countermeasures needed to keep our virtual representations safe. She emphasizes the need to build provenance into tools, discusses blockchain use cases, and shares systems that implement hashes for security.

Imagine a world where every piece of digital content can be verified and traced back to its source. Lindsay Walker, Product Lead at Starling Lab for Data Integrity, walks us through the emerging tools that could make this possible. While AI tools hold incredible potential for good, Lindsay also warns against threats and countermeasures needed to keep our virtual representations safe. She emphasizes the need to build provenance into tools, discusses blockchain use cases, and shares systems that implement hashes for security.