Agents of Complexity in AI Powered Neuro - Data Driven Decisions

Abstract Purpose: Purpose of this paper is to reject traditional assumptions and evaluate cognitive factors that have stimulus on actor’s decision. The question being proposed is; Can cognitive processes be inferred from neuro-imaging data? Methodology: Methodology includes an eye tracking experiment conducted on Eye Movements with single - subject towards obtaining deductions in deep uncertainty-based entrepreneurial complex decisions based on identifying fixations & saccades and eye movement (Geometry of Stimulus). Analysis: One significant area where AI is making an impact is in the analysis of eye imaging data. Neuroimaging techniques produce vast amounts of data that can be challenging to interpret. AI algorithms, particularly those based on machine learning, can analyze these complex datasets more efficiently than traditional methods. Moreover, AI also aids in the modelling of neural networks. In neuroscience, the human eyes intricate network of neurons can be likened to artificial neural networks used in machine learning. By studying how biological neural networks operate, AI researchers can improve the design and effectiveness of artificial networks. Furthermore, AI is being used to simulate eye functions, providing insights into how we think, learn, and decide. Notwithstanding considerable developments, enquiry of how we make AI Powered neuro driven - datadecisions stays to posture significant trials for methodical explorations. How does an Entrepreneur choose via AI Powered Neuro Driven - Data? What part do eyes sprays perform in AI Powered neuro driven - data decision making? Scope examines challenges where range, dimensions and predictability of AI Powered neuro-driven – data biological substrates underlying cognition processes cannot be reasonably expected. Results: This paper attempts to deliberate conclusions in the direction of understanding neuro - design and proposition to riposte topics in entrepreneurial preference undercurrents via. AI powered neuro driven – data biological substrates. Research efforts conclude with characteristic schemes and presents directions for future research. Research attempts would assist reconsidering practicalities of entrepreneurial preference dynamic forces by providing alternate arrangement for rational preference complications. This research opens new panoramas for future replicative scholarships. Originality/Value: The paper attempts to experimentally decipher the Agents of Complexities in combinatorial AI powered neuro based data driven decisions. Type of Paper: Experimental based analytical paper Keywords: Artificial Intelligence, Deep Uncertainty, Neuro Driven – Data, Neuro-Feedback and Eye Movements