In 'Hyperion', Dan Simmons crafts a complex and engaging narrative that follows seven pilgrims as they travel to the enigmatic planet Hyperion. Each pilgrim has a unique story to tell, which they share during their journey, revealing their connections to Hyperion and the Shrike, a metallic creature with the power to grant wishes. The novel is structured similarly to 'The Canterbury Tales' by Geoffrey Chaucer, with a framing narrative that presents the tales of the pilgrims. The story explores themes of religion, war, love, and the human condition, set against a backdrop of interstellar politics and technological advancements. The novel is praised for its detailed world-building, character development, and literary references[1][2][5].
Blood Meridian is a historical novel that depicts the brutal reality of the American West in the mid-19th century. The story follows a 14-year-old runaway from Tennessee, known as 'the kid', who joins the Glanton gang, a historical group of scalp hunters. The gang, led by John Joel Glanton and the enigmatic Judge Holden, is contracted to kill and scalp Native Americans but soon devolves into indiscriminate violence against various groups. The novel explores themes of brutality, the loss of innocence, and the harsh realities of human nature, with Judge Holden serving as a central figure embodying philosophical and sadistic elements. The book is known for its unflinching portrayal of violence and its allegorical exploration of human existence[2][3][5].
What happens when the need for rapid AI innovation runs up against the growing pressure for trust, accountability, and compliance? In this episode of Tech Talks Daily, I sit down with Mrinal Manohar, CEO of Prove AI, to explore how risk management can accelerate rather than hinder AI deployment.
Mrinal shares how Prove AI is helping organizations build trust into their AI systems from the start. At a time when businesses are moving AI models into production, yet often lack visibility or safeguards, Prove AI offers a solution grounded in transparency and automation. Their approach uses distributed ledger technology to create tamper-proof audit trails for AI models. This allows teams to focus on innovation while having the infrastructure in place to meet evolving standards and regulatory demands.
We discuss why traditional monitoring techniques fall short in an AI context, especially as models become more complex and decisions happen in real time. Prove AI’s infrastructure is designed to support continuous risk mitigation. By recording every event and decision with cryptographic certainty, they make it possible to prove safety, compliance, and responsible use without relying on labor-intensive manual audits.
Mrinal also explains how Prove AI’s upcoming GRC product aligns with ISO 42001 and helps companies stay ahead of regulatory expectations. Whether you're deploying AI in customer service, manufacturing, or high-risk environments, the platform ensures clear oversight without disrupting speed or agility.
This conversation covers practical examples of AI risk in action, from automated railway inspections to drive-through ordering systems. We also explore how distributed ledger technology is helping redefine AI governance, offering companies a way to move fast with confidence.
If you're scaling AI and wrestling with risk, compliance, or trust, this episode will give you a fresh perspective on how to build guardrails that support growth—not slow it down.
Tech Talks Daily 
