Expert Panel Discussion: The Role of AI in Aneurysm Detection and Tracking

AI adoption and cloud computing have skyrocketed in recent years, and it’s transforming organizations at every level. From small pilot projects to near-complete automation of key processes, businesses are starting to see the value of AI, and the benefits are significant. Yet, to reap the real rewards of AI and truly see the impact, companies need to learn to scale their solutions up and across the organization.

Is the database available if an instance is up and running, but it is unable to serve any requests? Or if response times are excessively long, so that users consider the service unusable? Is the impact of one longer outage the same as multiple shorter outages? How do partial outages affect database availability, where some users are unable to use the service while others are completely unaffected? Not agreeing on precise definitions with your customers might lead to dissatisfaction. The database team might be reporting that they have met their availability goals, while the customer is dissatisfied with the service.

If you know that you need to get an AI project off the ground quickly, whether it’s due to competitive pressures, to be able to move with greater agility and speed or for testing out different AI scenarios for customer experiences – then deploying the solution via Cloud technologies is probably for you.

Enterprise companies are adopting AI generative tools to streamline their content operations and improve efficiency. But without proper governance, they may find themselves publishing off-brand, non-compliant, and even offensive content.