Is General Purpose AI Possible?
Recently in Forbes, Dan Woods raised the question, ‘Has Anodot Defined the Principles of General-Purpose AI?’ With the rise in attention to Artificial Intelligence (in all its forms), one of the biggest problems that has come up is: knowing when to apply which type of AI to which problem. Woods explained that he has defined a set of principles that can explain when general purpose AI is possible.
Can AI Software Really be Good at Everything?
So what is general purpose AI anyways? The author established that general purpose AI must be able to solve problems in a wide variety of use cases, be usable by someone who doesn’t really understand the science behind the AI, and should be easy to connect to a business domain.
Yet in addressing the practicality of actually applying general purpose AI, the author asserted, “when someone claims their AI is good at everything, it’s usually not that good at anything.” While skeptical, he held that one of the main criteria for a successful implementation of general purpose AI would be that the solution can address many business use cases.
Ready to Test the General Purpose AI Hypothesis?
Woods explained how Anodot’s approach not only peaked his interest, but also intrigued him for how this could test his criteria for realizing general purpose AI. He wrote, “What’s particularly interesting about Anodot (and what makes it more of a general AI product) is that it is data agnostic. Users feed in their data and it helps to diagnose a problem, but it does this without any context – it doesn’t understand the meaning of your data. So, for instance, it doesn’t need to differentiate between sales or social media data to produce a result. It also can process any kind of data, from structured to non-structured.”
What’s Anodot’s Secret Sauce?
Most traditional analytics solutions may have good collectors (mainly for infrastructure metrics), but fall short when it comes to accurate detection and alerting, with the inevitable result: many legitimate anomalies aren’t detected and too many false positives are reported.
Anodot is an Artificial Intelligence analytics solution that finds subtle issues lurking in the data and proactively identifies business incidents in real time. Using an ensemble approach to identify as many anomalies as possible within a given dataset, Anodot runs many algorithms, constantly refining its detection ability while receiving feedback from the user. Its pattern recognition algorithms are designed to detect anomalies in time series data, making it data agnostic. Anodot detects legitimate anomalies with fewer false positives – allowing organizations to remedy urgent problems faster, and capture opportunities sooner.
Data-driven Organizations Need Real-Time Business Incident Detection
While there are many AI systems in the market that try to find events and data that is not normal, they often fall short. The author asserted, “often these systems fail because they identify too many anomalies (false positives) or not enough (false negatives).”
Anodot’s approach differs from other systems, and is ready to match the scale and speed required by data-driven organizations. “Once these anomalies are identified, a second level of AI evaluates the anomalies, assigning them a score and to correlate them. By using a weighted scale, Anodot tries to surface only major incidents, filtering out low-impact anomalies.”
While comprehensively discovering all anomalies, Anodot may not know what the anomalies are and why it could be important that the failure of one component to function impacts the performance of an app. Anodot brings this information to the attention of the user, highlighting a correlation between the two issues. The person using Anodot can quickly turn this information into valuable insights. “This is the key to general purpose AI,” wrote Woods, “The person doing the searching can quickly discern relationships between the anomalies. The model of the anomalies doesn’t have to be captured in the system.”
Read the full article on Forbes: Has Anodot Defined the Principles of General-Purpose AI?
Written by Anodot
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