Questions we get asked.
Short answers about artificial consciousness, AI and what we are building.
What does G = (V,E) mean?
It is the standard mathematical notation for a graph: a set of vertices V connected by edges E. Brains are graphs of neurons and synapses, and we think minds are best understood as graphs whose activity changes over time. Read more about brain graphs.
What does G = (V,E) research?
Artificial consciousness. We look for mathematical properties that distinguish systems that merely process information from systems with the integrated, self-representing organisation associated with conscious brains, and test them in software. See our research.
Can AI be conscious?
Nobody knows yet. There is no scientific consensus that any current AI system is conscious, and no proof that machines cannot be. Researchers assess AI against indicator properties drawn from theories of consciousness. Read our explainer.
Are you building a conscious AI?
Our first goal is scientific: a falsifiable mathematical framework and experiments that test it. A prototype artificial mind comes after that, built on whatever survives testing. We will be explicit about what our results do and do not show.
How would you test whether a machine is conscious?
Not by asking it. We focus on mechanisms. Our first experiment builds two comparable systems, one with a recurrent workspace and persistent self-model, then selectively disables components and measures the change in performance, ΔP = P(intact) − P(disrupted).
What is the hard problem of consciousness?
The question of why physical processes in the brain are accompanied by subjective experience at all. It was framed by David Chalmers in 1995. Read our explainer.
Which theory of consciousness do you follow?
None exclusively. We draw testable mechanisms from several theories, including integrated information, recurrent processing, global workspace and higher-order theories, and let experiments decide which matter. Compare the theories.
What role does mathematics play?
Mathematics forces precision. It turns ideas about the brain into models that make predictions that can fail. We start from computational neuroscience, the mathematics of neurons and networks. Learn the basics.
What is your position on ethics?
Consent comes first for anything built from a person's data or likeness, and if we ever create a being that genuinely experiences, its interests matter. We are honest about what is proven, promising or speculative. Read our values.
Who founded G = (V,E)?
Sai Kiran Reddy Badduri, who leads the lab's research and also works as a data product owner building a company classification data product. Meet the team.
Are you hiring?
Not yet. G = (V,E) is at the research proposal stage. We'll announce roles here when that changes.
Is G = (V,E) open to investment?
Yes. We are open to investors and venture firms who want to take part in this research and development from the beginning. See the investor page.
How can I get in touch?
Email saibadduri1@gequalsve.com. We welcome investors, researchers with feedback on the framework, and curious people.