SRC’s Human like Artificial Intelligence Comes To The Market

SRC Technologies, Inc. of Antioch, IL www.srcti.com announces the release of its new generation and re-engineered version of Heuristic Artificial Intelligence or HAI. It’s called HIPS (the Heuristic Intelligent Processing System).

The world of Information Technology and computers just took a giant leap forward today with SRC Technologies, Inc.
announcement that it is introducing to the market a unique version of Heuristic Artificial Intelligence. The unique design
provides the ability to be used in most industries and applications without major programming. This engine provides
computers, applications, and systems with capabilities never before achieved. This catapults computer processing to a new
level.

HIPS, SRCs software-design, is a Multi-Layered proprietary architecture incorporating the best features of Artificial Intelligence systems and business processes into a single engine. This provides the IT industry with the technology capable of emulating the actions of humans, which includes making decisions in the same way humans would make them no matter how complex they may be. The engine can learn, reason, solve problems, perceive, and interpret any kind of input. We have added complex algorithms to assist in performing difficult tasks, we do this in parallel. The software is very small 100k in size, and has been written in Java for maximum portability and adaptability.

One of the features of the engine has been extended to handle learning in a manner that is easy to accomplish. In the order of increasing complexity learning can now take place at the data level, the decision controller quantification level, and in the rules and rule structures themselves. There are methods that will handle learning on all of these levels.

Most companies and government bodies have legacy and old client-server systems. Most of these systems provide much
needed information to their respective organizations for decision making. There are rules and methods specifically for
handling the communication with legacy and client server systems. You use API's for this communication. The engine also uses API's to communicate with the existing systems and to accomplish specific tasks needed by management to properly run their business.

The engine can replicate itself when additional processing power is needed. It performs and refines observational analysis
and processes. It self learns and remembers learned processes for future processing calls. The engine is capable of making
predictions. The engine provides operational flexibility and maximum portability/mobility in a user friendly format. The
engine is independent of any CPU or operating system allowing existing applications to run on any system.

The original design dates back to the early sixties and has been installed in multiple locations and used in varied applications.
SRC has re-engineered the technology with many new, innovative design features, and it has reduced the size of the engine
and converted it to the JAVA language. As a result SRC has created the most intelligent and sophisticated AI engine available.
This is an enormously powerful approach. The engine can be easily adapted to a host of new and existing applications. This
engine makes it easy to handle the new generation of adaptability and integration of use.

The following are some applications examples where the technologies was used:

1) Place telephone switching equipment on a telephone company floor-plan 1963. The first use of this decision making was to apply equipment engineering knowledge and people knowledge to place electronic switching equipment onto a telephone
company floor-plan so that the equipment could work electronically. This is like using the computer to make all of the
decisions of component placement for the design of a computer except that the environment is extremely large.

2) Control a complete accounting system through a chart of accounts 1968. Most accounting systems within companies operate from a book called the chart of accounts. The chart of accounts describes all of the different types of accounting transactions that are used within a corporation. The chart of accounts also describes the information that is required for the transaction to be entered onto the company books. It is no wonder then that the chart of accounts can be used as the set of control rules for a complete accounting system. The chart of accounts for a large chemical processing company were indeed used to control theprocessing of all of the accounting entries within this organization.

3) Human directed fraud investigation for an insurance company 1972. Insurance companies are always faced with the problem of detecting fraud within the filing of insurance claims. People are usually the best at determining the different ways in which fraud can be detected. But computer systems are extremely good at being able to collect instantaneous information that can be used to find fraud within an environment. The engine has been able to provide the interrelationship between the human environment and the data environment to identify those claims that were most likely to be fraudulent. Claims are thus identified as fraudulent using both data information and human knowledge about different types of fraud processes that would be used to detect fraud. Then specific insurance claims would be identified as possible fraud for investigation. The system integrated in two different ways with the existing claim processing systems.

4) Automatic creation of bug free systems using the engine to create new systems 1972. The fraud investigation process also
used the same structure to create bug free programs. At that time these systems were created in assembler for main-frame
processing. So the structure can actually be used to create systems. In the current environment it would be much simpler to
create artificial intelligence processing rules that use methods to control the processing of a system.

5) Building inspection system for a large city government 1977. The City of Chicago had provided a large volume of
specifications directed toward handling the different types of inspections that City Government bodies must support for the
safety of their constituents. Although they had this complete set of specifications they did not understand how these
specifications could be turned into a system to support the environment. Again the same type of controlled information
processing was used as the basic architecture of the system. The architecture provided a high level of reuse between the
different inspection bureaus within the city. The first system was produced using modules (in today's terminology that is
methods) that related to the different types of tasks that were required for the process of inspecting. The ways in which
inspections were performed varied from bureau to bureau but there were enough common processes that the modules
methods where highly reusable. This process also shortened the amount of time required to implement the inspection process for the other bureaus.

6) Proactive monitor 400 on-line systems to immediately report problems 1989. The engine structure provided a valid
processing tool to proactively monitor the processing of on-line systems within the legacy environment. The same processing
structure as the engine was used as a portion of the overall system to continuously test for processing within the environment.

7) Proactive monitoring of a billing system for a large telephone company 1992. The same process was used again within the
large telephone company but this time an actual engine was used to perform the processing. Decisions were made as the
legacy systems were running about the duration of each of the steps. If the process ran too swiftly then it was understood that the system ran without the data that it needed for processing. If the process ran too slowly then there were other problems. In either case the computer operators were warned of the discrepancy and the problem was immediately addressed. The engine continuously learned the correct amount of time that it would take for each part of the overall system to run. As the number of items to be processed changed or the way that the system processed changed the system would learn the new information and yet continue to know when processing of the legacy system was within specification.

8) Maximizing contract profitability for outbound call centers 1993. This process also used the existing engine. Contracts
within the outbound call centers cause profit discrepancies. The system understood the discrepancies and took advantage of
the discrepancies to maximize the income per sale thus maximizing the profitability of the contract itself.

9) Control of manufacturing equipment with learning feedback 1994. The engine is fully capable of running a manufacturing
operation through a series of program logic controllers. The program logic controllers and sensory equipment provide the basic knowledge that the system requires to make the decisions about controlling the specific manufacturing process under control of the system. The system is also capable of learning how to better control the manufacturing process. This occurs through two forms of learning. The first form is feedback from the process itself. The second form is from human knowledge about the adequacy of the process. Both processes are used within the learning environment.

10) Customer problem resolution with learning (includes web) 1998. This system uses the engine and has continuously been in
a production environment since 1998. The system uses the engine and engine structure and also continuously learns.

11) Select best candidates for a job with requirements fit and learning 2002. This is a second product that uses the engine
environment to make decisions about better selecting candidates that fit the requirements. The engine is used to control the
basic processing of resumes, requirements, and the matching of the accomplishments within a resume to the expected
accomplishments of a requirement. The system is also capable of learning how better to select candidates from learning
feedback.

SRC Technologies, Inc. is an Artificial Intelligence company focused on the IT markets. It formed its charter as a C class
corporation in March of 2002. SRC has been in the process of re-engineering its Heuristic Artificial Intelligence engine and
developing different technologies which are solutions to meet the needs of the market.

At SRC, we inspire vision. We create adaptability.

Sal Cali CEO/President of SRC Technologies, Inc. can be scheduled for an interview and reached through Brian Sidler of SRC’s Public Relations department by calling him at (847) 838-4436 or logging onto www.srcti.com and clicking the contact us link.