Traditionally, the unstructured environment of our human world has been very hard for computers to understand — it lacks repetition, order and automation. This presents a problem for our everyday devices, which we expect to operate effectively in our highly complex, nuanced environment: each machine would require a huge amount of on-board processing power necessary to compute the different variables within every situation it encounters. Compounding this problem, any knowledge that has been accumulated by each device is not easy to exchange with other devices, so any learnt knowledge is siloed and not useful for other users and devices. To solve this problem, Neurence was founded by a group of world-class mathematicians and software engineers in Cambridge, England. Representing one of Europe's premier technical groups, the team at Neurence has built a highly intelligent, cloud-based central repository of information: Neurence acts like a "brain", with an ability to actually see, hear and understand the world around it. By using new mathematical and computational algorithms which power our cloud architecture, devices can be connected into and powered by Neurence, 'outsourcing' the processing of information from on-board the device into Neurence's intelligent cloud. By communicating all sensory data to Neurence, devices can access Neurence's knowledge to react to situations in the most effective and efficient way yet. This cloud-based machine learning means that each device does not need on-board processing power, allowing devices to be lighter, faster and less expensive to manufacture. Most importantly, each device can learn from the experience of others — enabling computers to move away from a rules-based, pre-programmed approach, evolving to understand the complexities of humans and their environments, and react accordingly. Features include: a) Neurence is hosted in a shared cloud storage architecture, meaning devices and applications can consult the brain when they come across a new situation; b) As Neurence learns from the experience of all connected devices, Neurence will automatically instruct the device on what to do based on the optimal outcome of other devices' history; c) These learnt repositories of information can be updated and refined in light of new information received by each device and application, sending this optimized information back to all devices; d) Neurence self-learns, therefore the more devices that are connected to the cloud, the more intelligent Neurence becomes; and e) The Neurence platform can be used to power any number of devices, such as phones, smart glasses and home appliances. Connected devices will instantly be able to access an almost infinite library of information, stored in our cloud. This will be added to Artificial Intelligence Resources Subject Tracer™. This will be added to the tools section of Research Resources Subject Tracer™. This will be added to Knowledge Discovery Resources Subject Tracer™. This will be added to Entrepreneurial Resources Subject Tracer™. This will be added to Bot Research Subject Tracer™.
posted by Marcus Zillman |