Blog #8 Web 2.0

(Web Squared Technology)

'Web 2.0' is a techno-culture term that was coined in 2004. The moniker was born at an O'Reilly Media conference, and describes that the World Wide Web has now evolved into a provider of online software services. There is an ongoing quest to understand where technology is taking us; the milestone serves as an opportunity not so much to look back but to examine the landscape ahead. Whereas the advent of Web 2.0 marked a profound shift in the meaning of the Web, this next phase is less a new direction than an exploration of what becomes possible when the building blocks of Web 2.0 (such as participation, collective intelligence and so on) increase by orders of magnitude. The step is called Web Squared Technology. Web Squared is another way of saying "Web meets World."

An example of Web Squared is smart phones, which contain microphones and cameras, as well as motion, proximity, location, and direction sensors. They have their own eyes, ears, and sense of touch. Revolutionary new applications connect those senses to cloud databases and programs running on massive server farms. Where the Web Squared world gets really interesting, though, is when applications use all the senses of a device, coordinating them much like the human brain coordinates our senses, to draw conclusions that would be difficult with one sense alone. The Google Mobile Application for the iPhone detects the movement of the phone to your ear, and automatically goes into speech recognition mode. It uses its microphone to listen to your voice and decodes what you say by referencing not only its speech recognition algorithms but what it expects to hear you say based on the most frequent search terms in Google's search database.

In this sense, the Web Squared era is an era of augmented reality, arriving (like the sensor revolution) stealthily, in more pedestrian clothes than we expected.

Neural Networks

Neural networks are best at identifying patterns or trends in data, and they are best well suited for prediction or forecasting needs including:

Sales forecasting

Industrial process control

Customer research

Data validation

Risk management

Target marketing

In the business field with several general areas of accounting and financial analysis, and any neural network application would fit into one business area or financial analysis; resource allocation and scheduling; database mining, searching for patterns implicit within explicitly stored information in databases.

There is a marketing application, which has been integrated with a neural network system. The Airline Marketing Tactician (AMT) is a computer system made of various intelligent technologies including expert systems. Neural networks have a huge potential we will only get the best of when they are integrated with computing, AI, fuzzy logic, and related subjects.

Recent studies reported neural network business application studies utilize multilayered feedforwarded neural networks (MFNNs) with the back-propagation learning rule. This is popular because of its broad applicability to many problem domains of relevance to business: principally prediction, classification, and modeling.

Artificial Intelligence

Artificial Intelligence (AI) is applied to product demand, employee turnover, cash flow, distribution requirements, manpower forecasting, and inventory aspects of business operations.

What is AI? It is a computer-based analytical process that exhibits behavior and actions that are considered “intelligent” by human observers. It attempts to mimic the human thought process including reasoning and optimization.

Forecasting generally uses three common types of AI:

Neural Nets emulate elements of the human cognitive process, the ability to recognize patterns.

Expert Systems summarize the totality of available knowledge and rules.

Belief Networks describe the database structure using a tree format.

Banks use AI systems to organize operations, invest in stocks, and manage properties; hospitals can organize bed schedules, make a staff rotation, and provide medical information; and heavy industry plants use it to complete jobs that may be too dangerous for humans.

Artificial Intelligence is developed and used in many ways to assist businesses in their day-to-day operations. Everyday and new develop is being made to make productivity faster and less time consuming. It is also used in security, which makes it harder for certain security measures very hard to penetrate.