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Mariana Krym, COO and Co-founder of Vyvo Smart Chain, has a unique vision for the future of artificial intelligence (AI). Instead of simple task execution, she envisions AI as an “emotional mirror” helping users navigate their emotions and self-awareness.
In a recent discussion with Bitcoin.com News, Krym shared her thoughts on shaping AI companions that can foster self-awareness, aid in emotional processing, and create space for honest introspection.
Having previously worked at tech giants like Twitter, Snapchat, and Waze, Krym emphasized the need to build trust into the very fabric of such emotionally attuned AI.
“We’re not just building tools—we’re shaping companions that can reflect us back to ourselves,” Krym said.
Her vision is for AI to recognize subtle patterns in a user’s tone and behavioral shifts, thereby helping individuals surface insights they might not be consciously aware of.
“AI has the potential to act as a gentle emotional mirror: recognizing patterns in tone, noticing our behavioral shifts, and helping us surface insights we might not articulate alone,” Krym explained.
She further noted that user ownership and privacy are the core tenets of her philosophy.
“For that to happen, trust must be designed into the architecture. The AI must belong to the user,” Krym asserted.
This principle, central to Vyvo’s approach, actively combines real-time biometric signals with decentralized memory (data) to create this “emotional mirror.”
Krym’s perspective diverges from the traditional focus of many AI solutions, which primarily emphasize cognitive intelligence and task completion. Unlike cognitive reasoning, emotions are deeply subjective and context-dependent.
While AI can simulate emotional responses, true emotional intelligence requires lived experience, empathy, and personal context, which AI lacks. However, there are ongoing attempts to incorporate emotion-based interactions, particularly in areas like customer service and social robotics.
Web3 Holds ‘Powerful Answers’ for AI Ethics
The goal isn't to simulate feelings. It’s to support the human experience with awareness and context,” Krym clarified, highlighting that the aim is not to create artificial emotions but rather to enhance human emotional intelligence through AI-driven insights.
As the AI era unfolds, the question of how artificial intelligence will interact with and learn from users is paramount. Krym argues that memory-based AI, capable of growing with its user and building trust through continuity, is not just a desirable feature but a necessity for meaningful human-machine relationships. Still, she firmly believes this must be built upon a foundation of robust user control, privacy, and explicit consent.
Drawing a stark contrast with the often privacy-infringing tracking methods prevalent in Web2, Krym envisions a future where AI agents learn and remember user interactions ethically and securely.
“Absolutely—and we believe they must be. Memory-based AI isn't just a feature; it's essential for building meaningful, personalized relationships between humans and machines,” Krym stated.
To achieve this vision, Vyvo Smart Chain has architected its system around Data NFTs, an approach which according to Krym, places the user firmly in control of their own data.
“That's why we built our system around Data NFTs on Vyvo Smart Chain. Each user holds their own encrypted memory container. The AI can access it only with explicit, revocable consent. No scraping. No backdoors. No centralized logging.”
On what AI will look like in five years, Krym predicts it moving from reactive tools to “collaborative presences.” Still, she sees the ethical use or lack thereof as a challenge that will grow with the increased use of AI.
“But the biggest challenge isn't technical—it's ethical. Regulators will need to confront questions around data sovereignty, memory, and consent. Who owns the training data? What rights does a user have over the memory of an AI they’ve shaped?,” Krym states.
However, she asserts that while these questions demand new frameworks, Web3, and not traditional regulators, offers “powerful answers.”
“Decentralized consent layers, user-owned memory, and transparent data flows can serve as regulatory guardrails by design, not just policy. The challenge is real. But so is the opportunity,” Krym explains.
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