The core foundation of our human-centric augmented intelligence models involves investigating the true meaning and the working of human intelligence, not merely developing mathematical models.
It’s not about AI vs humans. It’s humans plus AI. This is Augmented Intelligence.
Simon Jack – Co-founder & Chief Design Officer – Nebuli.
We facilitate real and meaningful collaboration between humans and technology by helping customers uncover new methods that replace conventional “command and response” models with more personalised, interactive, exploratory and versatile user experiences.
Nebuli’s unique approach enables your team to easily apply personalised augmented intelligence frameworks to elevate your own smarter applications within your workflow or expand to wider markets faster and with a much higher level of data security.
No tedious integration work.
No replacement of your apps.
No lengthy staff training.
From our founding team’s experience with AI since the late 1990s, we compared conventional AI systems with the human brain’s short and long-term memory mechanisms.
We identified and developed the key stages needed for Nebuli to generate a human-like Working Memory, which is at the core of our products and services available to all customers.
Search through resources and datasets to gain information and build initial insights – i.e. the amount of potential knowledge acquired.
Establishing awareness and understanding of the facts, data, research information, descriptions, or skills acquired through the exploration and learning processes.
Detecting something new, such as new trends, events, anomalies, actions, or ideas, providing new reasoning to explain the knowledge gathered through such detections and building initial “quick” decisions.
Retention of the new information and knowledge discovery over time for the purpose of influencing future actions and decisions. This forms the building blocks for Working Memory by examining decisions, ideas, thoughts, data, behaviors, feelings and motivations and asking why.
Formation of Working Memory – i.e. detailed evaluation, reasoning, data processing, and deeper analysis – using the stored knowledge for problem solving, decision making and generation of new ideas.
Self-examination of own reliability, ensuring overall consistency – using a set of internal test scores related to the number of random errors recorded within a database to generate better and smarter cognition.
Using applied and/or collaborative improvisation methods to establish true personalization and creativity to accommodate specific needs and interests of oneself, generating new data and ideas for exploration.
Collect and manage your various datasets from different sources through a single channel.
Bring together the traditionally separate services of data security, compression, modelling, segmentation, classification and knowledge discovery into the same channel.
Combine several other layers of your integrated services such as your software, applications, UI/UX and data security protocols within your existing workflow.
and much more…