Chara AI Reviews:researches and builds explainable and modular artificial intelligence systems
About Chara AI
Chara AI uses machine learning techniques to answer a difficult question, “how do we evaluate a creative work without bias?”. Through the Resident Entrepreneur programme, the Chara Screen Score project attempts to answer this, focussed on the sector’s specific needs of video platforms and the thousands of writers that supply stories for film and TV production. Their approach is to combine human expertise with an Artificial Intelligence system with the aim of bringing diverse new talent to the screen.
Artificial Intelligence alignment
What is Chara AI?
Chara AI researches and builds explainable and modular artificial intelligence systems. Their goal is to provide audience-informed informatics solutions to diversify creative markets and economies.
Chara AI researches and builds explainable and modular artificial intelligence systems. Their goal is to provide audience-informed informatics solutions to diversify creative markets and economies. Chara AI is a Scotland based Artificial Intelligence company founded in 2020. They focus on interpreting stories and ideas when in development, to help creative businesses meet the demands of video streaming platforms.
Creative Informatics will be delivered by the University of Edinburgh in partnership with Edinburgh Napier University, Codebase and Creative Edinburgh. The programme is funded by the AHRC Creative Economy Programme with support from SFC.
Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2023.
What if we could discover thousands of new stories by solving one problem?
Founded in 2019, Chara AI is a publicly and commercially funded R&D company supported by The Bayes Centre, The University of Edinburgh, Innovate UK – Creative Catalyst and Scottish Enterprise. We offer cutting-edge Artificial Intelligence Solutions for Creative Markets, Audience-Informed Informatics Solutions and AI for Diversifying Creative Economies,
Our goal is to provide audience-informed informatics solutions to diversify creative markets and economies. Leveraging machine learning and deep analysis of heuristics, we discover and connect dynamic online mezzo communities. Our focus is on cultivating spaces where interactions are fostered around shared interests or experiences.
Narrative + Novelty = Evolution
In investigating the dynamics of storytelling novelty, we plunge into the social networks’ labyrinth, charting narrative flux and tracking sentiment alterations algorithmically. Using a ‘reverse order’ algorithm, we decode sentiment shift patterns from latest sharer to origin node. Novelty spikes, linked to trending themes or diverse narratives, subtly add to a calculable virality score. The omnipresent ‘narrative equilibrium’, prevalent in social network competition, emerges as a factor, revealing its widespread effect on narrative creation and concerning propensity to standardize bias and manipulation in digital storytelling.
At Chara AI, we delve into the core of novelty and its role in shaping evolutionary processes across technological, biological, and social systems. We differentiate between invention, the creation of something new, and innovation, a successful and transformative invention. Both are crucial for evolutionary processes. Our research explores themes like the origins of life, social and cultural change, technological advancements, knowledge systems transformation, complex societies development, and the formation of ecological and social networks. We aim to understand the origins of novelty and the factors that lead to innovation. Our goal is to develop a predictive, quantitative theory of novelty.
The Generative Algorithm, our cutting-edge evolutionary system, curates personalized visual narratives based on participant input. It engages participants with an AI-posed seed question, prompting interactions within our bespoke NLP sandbox. Here, participants carve unique narratives as the algorithm draws from diverse data to refine its generated imagery. This user-guided storytelling process acknowledges user-approved scenarios and discards “extinct” ones, fostering co-creation. The algorithm navigates through layers such as ‘APPEARANCE’, tuning its outputs as per user responses. With GAN capabilities and AI API, it crafts individual image scenarios displayed on the NLP sandbox, marking its evolutionary stride.