is an artificial intelligence company founded with the purpose of augmenting human intelligence with AI by unifying the three essential aspects of human cognition namely: problem solving, learning and memory. AIBrain’s Conversational AI enables humans and toys alike to interact with artificial agents in a natural way through use of natural language. AIBrain’s AICoRE, Memory Graph, and advanced planner technologies make this possible.
Conversational AI is part of our effort to develop a customizable AI brain for all toys where communication can drive higher usage and extend the toy’s lifespan. Cognitive Intelligence is core to achieving this unique goal of enabling seamless conversation between a toy and its user. Aside from improving playability, it can also serve an instrumental role in cultivating a child’s cognitive abilities, including problem solving, speech improvement, cognitive learning and memory enhancement.
The Company initially received recognition at CES 2014-2015 by accepting the innovation award in the “A Better World category” and has since developed an AI robot platform where the conversational AI is applied to toys. Beyond just the pattern matching-based methods most chatbots use, AIBrain’s conversational AI provides an exceptional user interface experience with a natural feel and has been designed to mirror human-like cognitive intelligence.
AIBRAIN TECHNOLOGY COMPONENTS
- AICoRE: AIBrain’s AICoRE (Adaptive Interactive Cognitive Reasoning Engine) fully automates the reasoning process from end-to-end. AICoRE is the most advanced cognitive reasoning engine on the planet, simulating human intelligence across the full spectrum of logical reasoning, as well as in unifying problem solving, learning, and memory. Along with our other major technology component (MG, AICoRE enables any Conversational AI Toy platform to better understand human language and respond in a human-like manner.
- Memory Graph (MG): Different from Knowledge Graph and Social Graph platforms, MG is a dedicated memory structure which empowers toy agents to possess more powerful reasoning capability by leveraging the knowledge gathered over time.
Value propositions to the user range from:
- Personalization: the ability to remember each toy user as a unique individual.
- Natural Conversation: The ability to interact with users in a natural fashion that is well beyond the scope of traditionally-predefined scripted dialogs.
- Learning: the ability to persistently learn a toy user’s personal preferences, nuances, and personality traits (profile) over time based on continual dialog and ongoing interaction, with spontaneous adjustment as needed and as appropriate. In other words, the toy grows/matures with the child and therefore remains relevant.
Aside from the value proposition described above, MG automatically organizes and links new conversations with existing memories, continually correlates them with similar or related memories, and is able to scale to massively large amounts of conversational data.
- Cognitive Multi-Agent Planner (CMAP): A fully autonomous and intelligent agent needs to fulfill the entire cognitive process from beginning to end, including sensing, reasoning, problem discovery, planning, learning, remembering and responding. CMAP is the most advanced multi-agent cognitive planner commercially available and is completely conformant with the PDDL industry standard (Note: PDDL or “Planning Domain Definition Language” is a recent attempt to standardize planning domain and problem description languages.