Adept Enterprise and Deep A.I. Artificial Intelligence

To understand how deep A.I. Artificial Intelligence functions are developed, we first need to understand the technology that makes this possible. The term deep comes from deep learning, a branch of Machine Learning that focuses on deep neural networks.

Neural networks are computational systems that are inspired by the ways a human brain processes certain information. Special cells called neurons are connected to each other in a complex network allowing information to be processed and communicated.

In Computer Science, artificial neural networks are made out of thousands of nodes, connected in a specific manner. Nodes are arranged in layers; the way in which they are connected determines the type of the network and, ultimately, its ability to perform a certain computational task over another one. A traditional neural network might look like this:

Adept Enterprise Deep Artificial Intelligence

Each node from the input layer contains a numerical value that encodes the input we want to feed the network. If we are trying to predict the Dow Jones Industrial Average for tomorrow, the input nodes might contain the future and past price changes, stock splits, divisors, contracts, fear and greed index encoded as numbers in the range.

These values are broadcasted to the next layer; each result-curve dampens or amplifies the values it transmits. Each node sums all the values it receives, and outputs a new value based on its own function. The result of the computation can be retrieved from the output layer; in this case, only one value is produced, the probability of the Dow Jones Industrial Average.

When using Adept Enterprise we use multiple input nodes that are triggered by events, either by humans or by machine code. The Adept Enterprise software outputs the desired result based on the sum of all result-curves via the input layer values it receives. The output layer result is the most desired result. This allows for the software to give and assign unlimited desired results, without a human manually doing it. This allows one human with the software to accomplish the same work load as hundreds of humans without the software, and in some cases based on the job thousands of humans.

Training a neural network means finding a set of weights for all result-curves, so that the output layer produces the desired result. One of the most used technique to achieve this is called back-propagation, and it works by re-adjusting the weights every time the network makes a mistake. The mistake is determined by not accomplishing the desired result, or the desired result is not desired anymore.

The basic idea behind training a neural network is that each layer will represent progressively core complex features. In the case of a workflow task, for instance, the first layer might detect violations, the second layer detects date and time restrictions, which the third layer is able to use to approve or deny an application or task.

In experience, what each layer responds to is far from being that simple. This is based on humans and software creating a library of input layers, and the software producing the desired results for the output layers.

The desired result is a perfect result, eliminating imperfection. This saves money, time and frustration.

Contact us today toll free 1-888-392-9623 to find out more on how Adept Technologies can save you money by utilizing our technology.

Adept Enterprise: Finding what best fits with your organization

Adept Enterprise: Finding what best fits with your organization

We offer Adept Enterprise in 3 flavors. Private Cloud, On Premise, and Hybrid. We know there are certain mission critical systems that can never be placed outside the organization, while other mission systems can.

It really comes down to the requirements of the organization. As a software vendor to numerous government and businesses we are held to strict data security requirements, including where data can be stored, either in a Private Cloud, On Premise, and/or Hybrid storage models.

In some cases where organizations are subsidiary to larger organizations, and are bought and sold every two to five years, it makes sense to have your mission systems stored in a private cloud.

Another interesting flavor is our hybrid systems where On Premise systems and Private Cloud systems work together based on the requirements of the organization.

Adept Enterprise

Adept Enterprise in three flavors

Being a pioneer in enterprise software requires us at Adept Technologies to leverage On Premise, Private Cloud, and Hybrid platforms. Most of our clients have been surprised to find that lower costs have not been the biggest benefit of our private cloud systems, but they come from operational shifts, performance gains, and zero percent down time.

We at Adept Technologies do not leverage 3rd party cloud services such as Amazon Web Services, Microsoft Azure, or Zadara Cloud storage for our Private Cloud services. The reason why is we do not trust the public cloud. We like to know what server stores your data, where that data is and where it goes at all times. We build our servers and we program them and we place them in our server racks (we own the racks too) at our different datacenters via our partner corporation Tierpoint. They provide the redundant space, power and internet communications. We have been working side by side with Tierpoint for over eight years, providing our Adept Enterprise private cloud services to numerous clients, and we have had 100% update time.

Offering Adept Enterprise in 3 flavors, On Premise, Private Cloud, and Hybrid gives our customers the flexibility to manage their systems, that best fits their organization, and prevents critical information from being in the hands of the wrong people.

We mold Adept Enterprise around your organization.