a·kin LABS

Is where we build
and test the next generation of AI.

We have developed a new approach called ‘Epigenesis,’ which refers to the scientific concept of how an organism can change and adapt in interaction with its environment.

We have three key research areas for our Core AI:


Emotional Intelligence

A·kin's intelligent assistants combine a deeper level of understanding with reasoning capabilities to support complex tasks, and to help people make more objective, informed and responsible decisions.


Autonomous Reasoning

Harnessing a fusion of modern neurosciences and chaos theory approaches, a·kin's innovative state-based interactive AI transcends the shallow world of chatbots, and enables human-like grounded reasoning, interaction and problem solving.


Habitat as a Complex System

The range of applications for Akin's AI spans the most ambitious tasks involving multi-modal, multi-user interaction and complex system optimisation, from artificial habitats to our own homes.

a·kin SPACE

We deploy and benchmark our AI into the most
difficult environment we can think of: space.

We have been awarded a multi-million dollar multi-year contract, where our AI are being used as ‘crew’ for NASA’s Jet Propulsion Lab, to support the advanced manufacture of spacecraft. We have also won a large grant from the Australian Space Agency, and are using that to train our AI to take on these different roles.


Support complex tasks, autonomous problem solving. Provide both cognitive and physical help. Embodied in an autonomous helper robot.


Understand what is happening in the environment. Look for anomalies and create alerts. AI Analytics. Embodied in a swarm of smaller robots with sensors.


Ambient AI brain, with an overarching view of the whole environment. Understands people, processes, events and the habitat as a whole system. Embodied in a ‘brain’ represented by an abstract avatar.

Core AI / AGI

We place strong focus on unsupervised and semi-supervised learning technologies that will empower the next generation of scalable autonomous AI.

These include goal-oriented reinforcement learning, unsupervised ontology acquisition and advanced dynamic associative memory. We are working towards a fusion of these technologies to enable AI to efficiently and independently handle reasoning, complex problem solving and decision making.

Human-AI relationship

The opaqueness of the human mind poses a great challenge to human-machine interaction.

We are working with a synergy of neuroscience, cognitive theories, behavioural science and multimodal learning to develop AI that understands humans. This spans language, emotion, culture, values and goal alignment in order to achieve deep and trusted relationships between humans and AI.

State optimisation

Our approach is to model AI, humans and their
environment as gravity wells in an event space.

We do this to map resources, events and relationships that AI can use to optimise state space and traverse events more effectively over time. By measuring and optimising according to shared goals, AI will be able to improve its own effectiveness in order to enhance the well-being of humans and manage their environment.

Our latest research

Here's what we've been up to recently.
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