Availability in AI context typically refers to how readily available and accessible a system or service is for use. High availability ensures that the system can operate continuously without a noticeable disturbance or downtime.
Imagine you have a favorite toy shop. Availability would be like how often the shop is open when you want to visit. If the shop is always open when you want to play, it has high availability.
In the context of Artificial Intelligence, availability is an important concept that has to do with ensuring that a system, platform, or service is operational and accessible when it’s needed.
High availability is particularly relevant to Artificial Intelligence systems that are delivering services in real-time environments or having a continuous interaction with the users. These could be recommendation services, real-time decision-making systems, or support chatbots. If the availability of these AI systems is compromised, there could be disruptions in service provision leading to inconveniences on the user’s end. For example, a recommender system could fail to provide personalized suggestions or a chatbot might fail to respond to user queries.
Maintaining high availability often involves strategies like Load balancing techniques, redundant systems, and failover capabilities.
Load balancing refers to the process of distributing workloads across multiple computing resources, thereby minimizing the risk of a single point of failure, optimizing system responsiveness, and maximizing throughput.
Implementing redundant systems means establishing backup or alternative systems that seamlessly take over in the event of a primary system going down. This reduces the disruption of service in the event of an unanticipated failure.
Failover capabilities are mechanisms that automatically and seamlessly reroute or redistribute the workload of a failed system component to a backup system component.
Availability is thus a crucial aspect of AI system design and operation, closely linked to reliability and dependability. It is a key component of the broader concept of system resilience, which also includes adaptability, recoverability, and robustness.
Reliability, Resiliency, Load Balancing, Redundant Systems, Failover, Service Level Agreement (SLA), Downtime, Up Time, System Maintenance.