A leading software development company wants to integrate AI-powered chatbots into their customer service platform. After researching various AI models in the market which have been developed by third-party developers, they're considering two options:
Option A - an open-source language model trained on a vast corpus of text data and capable of being trained to respond to natural language inputs.
Option B - a proprietary, generative AI model pre-trained on large data sets, which uses transformer-based architectures to generate human-like responses based on multimodal user input.
Option A would be the best choice for the company because?
CASE STUDY
Please use the following answer the next question:
A mid-size US healthcare network has decided to develop an Al solution to detect a type of cancer that is most likely arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records a radiologist for secondary review pursuant agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has taken the following steps: defined its Al ethical principles: conducted discovery to identify the intended uses and success criteria for the system: established an Al governance committee; assembled a broad, crossfunctional team with clear roles and responsibilities; and created policies and procedures to document standards, workflows, timelines and risk thresholds during the project.
The healthcare network intends to retain a cloud provider to host the solution and a consulting firm to help develop the algorithm using the healthcare network ' s existing data and de-identified data that is licensed from a large US clinical research partner.
In the design phase, what is the most important step for the healthcare network to take when mapping its existing data to the clinical research partner data?
A U.S. mortgage company developed an Al platform that was trained using anonymized details from mortgage applications, including the applicant's education, employment and demographic information, as well as from subsequent payment or default information. The Al platform will be used automatically grant or deny new mortgage applications, depending on whether the platform views an applicant as presenting a likely risk of default.
Which of the following laws is NOT relevant to this use case?
Under the EU AI Act, which of the following compliance actions applies only to General Purpose AI models with systemic risk?
What is the best method to apply to an AI model so that it is statistically unlikely that a specific piece of training data can be identified from a model's output?
