What is artificial
and how can it
What is artificial
and how can it
There’s been a lot of talk about artificial intelligence, or A.I. But what is it exactly?
To understand what A.I. is, it helps to first understand what it’s not. Many of the technologies currently referred to as A.I. today are simply “traditional predictive analytics”, that is, analysis based on historical results and data. True A.I. is not just analyzing past results but the ability to simulate future scenarios. By doing so, you’re able to learn faster than you could in real-time.
Daisy’s vision for A.I.
Stanford University defines artificial intelligence as an “activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment.”
This definition aligns with Daisy’s vision of A.I. Specifically, the words “foresight” and “environment” are key.
- Foresight – because it’s about looking into the future.
- Environment – because in order to see into the future, a model of that world needs to exist.
Defining characteristics of A.I.
What differentiates A.I. from predictive analytics is the ability to simulate the future and to learn faster than the pace of time. Some of the key characteristics that define it are as follows.
- True A.I. makes decisions without human intervention.
- Can simulate billions of alternatives to produce the best outcomes.
- Has the ability to “sacrifice” to look for longer term gains.
- Makes recommendations that have never been done in the past.
- Can “learn” and self-adjust the underlying math without any human input.
A.I. is dramatically changing the profitability of many industries. It can be implemented faster, cost less and garner results more quickly. If it can’t, it’s probably not true A.I.
With the ever-increasing power of today’s GPUs, computational analysis that was impractical just a few years ago is not only possible now, for many companies it’s imperative.
This is especially so in disrupted industries such as retail and insurance, where margins are thin, the volume and frequency of transactions are high, and the potential for fraud is magnified.
See what others don’t.
A key that powers A.I. is simulation.
The key that powers A.I. is simulation, or the ability to play out all the possible business scenarios. In order to simulate, you need a model of the environment in which these scenarios would take place. Daisy has modeled both the retail and insurance worlds, measuring the causal relationships between all factors and the ripple effects that can impact a business decision.
Our approach is based on a branch of A.I. referred to as reinforcement learning. This area of artificial intelligence is concerned with reinforcing good and bad decisions, and the process of trial and error – the same way humans learn. A.I.-powered simulations allow for the unknown to be known and for learning to happen faster than real time.
LEARN MORE ABOUT A.I. TODAY –
WHAT IT IS, WHAT ISN’T, AND WHY NOW.
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