Artificial intelligence as a service refers to off-the-shelf AI tools that enable companies to implement and scale AI techniques at a fraction of the cost of a full, in-house AI.
The concept of everything as a service refers to any software that can be called upon across a network because it relies on cloud computing. In most cases, the software is available off the shelf. You buy it from a third-party vendor, make a few tweaks, and begin using it nearly immediately, even if it hasn’t been totally customized to your system.
For a long time, artificial intelligence was cost-prohibitive to most companies:
- The machines were massive and expensive.
- The programmers who worked on such machines were in short supply (which meant they demanded high payments).
- Many companies didn’t have sufficient data to study.
As cloud services have become incredibly accessible, AI is more accessible: companies can gather and store infinite data. This is where AI-as-a-service comes in.
Now, let’s detour into AI so that we have the right expectations when engaging with AIaaS.
Understanding AI
We hear it repeated over and over: artificial intelligence is a way to get machines to do the same kind of work that human brains can accomplish. This definition is the subject of significant debate, with technology experts arguing that comparing machines to human brains is the wrong paradigm to use. It may promote fear that humans can be taken over by machines.
The term AI can also be used as a marketing tactic for companies to show how innovative they are—something known as artificial AI or fake AI.
Before we start worrying about the technological singularity, we need to understand what AI actually is.
“Intelligence is the efficiency with which you acquire new skills at tasks you didn’t previously prepare for… Intelligence is not skill itself, it’s not what you can do, it’s how well and how efficiently you can learn new things.” — Francois Challot, AI Researcher at Google and creator of Keras
