The nature of business tools are changing, and it’s all thanks to neural network technology.
AI neural networks are designed after the human brain, and the use of this technology is continually growing. For businesses to appropriately power up their services and their tools, it is important to have access to this neural network technology. Although it might sound like science fiction, the idea of an artificial neural network can instantly improve almost any type of business system and help to automate processes within a business.
Some of the tools that businesses are using are available for free such as the Google cloud speech to text. This is a tool that will allow almost any developer to convert audio to text by using their network models through the application programming interface. The tool can recognize a staggering 120 languages and can be used for transcribing call-center audio over time.
Microsoft also has its own deep learning neural networks to assist with classifying malware and recognizing threats. Testing for a variety of electronics manufacturing solutions and for protecting businesses of the future, this could be a fantastic way to validate threats and prevent them in the future.
IBM also has their neural network within the Watson project. Watson can work at using deep learning architectures for recognizing audio data, text and even images. Watson can do a wide range of tasks such as capturing text from images, sorting and translating audio and even data entry tasks.
When we start to see how some of these key business processes could lend himself in the software-oriented positions within the business world, it’s easy to start understanding the way that future businesses could be powered using neural network technology.
A small subset of neural network technology is ANN’s or artificial neural networks. These are tools that specialize in the process of learning and problem solving as well as recognizing sound and language. These networks are formed using artificial neurons in the same way our brain is formed for function. Within the process of deep learning techniques, there can be multiple layers of learning and a series of information highways for transmitting data to business systems for quick results. When handling extremely complex tasks, this is one of the best tools for business systems moving forward.
Some other types of neural networks can include:
Convolutional neural networks: These are designed expressly for image inputs and for classifying visual imagery.
Recurrent Neural networks: these networks are designed with loops to ensure that it can store an ongoing memory and learn from these memories. This is perfect for understanding vocabulary and recognizing speech.
Long short Term memory: This is another RNN that can keep in mind long-term discrepancies and solve for even more complex problems.
Reinforcement Learning out rhythms: This is an algorithm that is put in place for a specific goal. It’s particularly important for examining the outcome of software performing under set conditions. These types of AI are the perfect learners for video games and other tasks.
Gated recurrent units: These are a mechanism that Gates RNN’s ensuring that they can be trained to record and retain information but that they can also filter out irrelevant information for their function.
Challenges persist for many businesses in choosing the right artificial neural networks as well as investing in this technology. Creating this technology for yourself does require extremely high computational costs and months or even years of development before a working AI can function. What many companies are choosing to do instead is utilizing proven systems from the likes of tech giants and developers and then customizing them and their functions for the needs of their business.
Artificial neural networks will continue to shape the future of the business world.