ai

Challenges and Pain Points in Developing AI Applications

Summary:

One of the challenges of developing applications using generative AI is ensuring the quality and reliability of the system.

It's important to avoid situations where poorly built applications with inaccurate calculations are relied upon. Additionally, the lack of documentation and the

SOURCE CODE CONTROL: The attacker might modify the source code of the ML algorithm, such as the random number generator or any third-party libraries, which are often open source.

In a MODEL POISONING attack [185], the adversary controls the model and its parameters.

The Importance of Monitoring and Assessing Generative AI Use Cases

Summary:

The Chief Data and Technology Officer of a large marketing services company emailed about the potential of generative AI within the organization.

They prefer a decentralized approach but want to monitor progress. Only 8% of organizations have such systems in production.

They

The following recommendations are meant to help define real-world tasks:

1. Consider how humans do it : Starting from first principles , think about how the task you would like to evaluate is accomplished by humans, and write down the steps involved. This process will help clarify the task.


2. Use caution with existing datasets: Current evaluations

The rise of AI forces us to consider what it means to be human. The Age of AI addresses the significant question of “whether there is a form of logic that humans have not achieved or cannot achieve, exploring aspects of reality we have never known and may never directly know” (16). For the authors, the advancement of AI could mark a positive step