In this episode of the Eye on AI podcast, Tyler Xuan Saltsman, CEO of Edgerunner, joins Craig Smith to explore how AI is reshaping military strategy, logistics, and defense technology—pushing the boundaries of what’s possible in modern warfare.

Tyler shares the vision behind Edgerunner, a company at the cutting edge of generative AI for military applications. From logistics and mission planning to autonomous drones and battlefield intelligence, Edgerunner is building domain-specific AI that enhances decision-making, ensuring national security while keeping humans in control.

We dive into how AI-powered military agents work, including the LoRA (Low-Rank Adaptation) model, which fine-tunes AI to think and act like military specialists—whether in logistics, aircraft maintenance, or real-time combat scenarios. Tyler explains how retrieval-augmented generation (RAG) and small language models allow warfighters to access mission-critical intelligence without relying on the internet, bringing real-time AI support directly to the battlefield.

Tyler also discusses the future of drone warfare—how AI-driven, vision-enabled drones can neutralize threats autonomously, reducing reliance on human pilots while increasing battlefield efficiency. With autonomous swarms, AI-powered kamikaze drones, and real-time situational awareness, the landscape of modern warfare is evolving fast.

Beyond combat, we explore AI’s role in security, including advanced weapons detection systems that can safeguard military bases, schools, and public spaces. Tyler highlights the urgent need for transparency in AI, contrasting Edgerunner’s open and auditable AI models with the black-box approaches of major tech companies.

Discover how AI is transforming military operations, from logistics to combat strategy, and what this means for the future of defense technology.

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

00:00) Introduction – AI for the Warfighter

(01:34) How AI is Transforming Military Logistics(

04:44) Running AI on the Edge – No Internet Required

(06:49) AI-Powered Mission Planning & Risk Mitigation

(14:32) The Future of AI in Drone Warfare

(22:17) AI’s Role in Strategic Defense & Economic Warfare

(26:34) The U.S.-China AI Race – Are We Falling Behind?

(35:17) The Future of AI in Warfare

In this episode of the Eye on AI podcast, Matt Price, CEO of Crescendo, joins Craig Smith to discuss how generative AI is reshaping customer service and blending seamlessly with human expertise to create next-level customer experiences.

Matt shares the story behind Crescendo, a company at the forefront of revolutionizing customer service by integrating advanced AI technology with human-driven solutions. With a focus on outcome-based service delivery and quality assurance, Crescendo is setting a new standard for customer engagement.

We dive into Crescendo’s innovative approach, including its use of large language models (LLMs) combined with proprietary IP to deliver consistent, high-quality support across 56 languages. Matt explains how Crescendo’s AI tools are designed to handle routine tasks while enabling human agents to focus on complex, empathy-driven interactions—resulting in higher job satisfaction and better customer outcomes.

Matt highlights how Crescendo is redefining the BPO industry, combining AI and human capabilities to reduce costs while improving the quality of customer interactions. From enhancing agent retention to enabling scalable, multilingual support, Crescendo’s impact is transformative.

Discover how Matt and his team are designing a future where AI and humans work together to deliver exceptional customer experiences—reimagining what’s possible in the world of customer service.

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Introduction to Matt Price and Crescendo

(01:49) The rise of AI in customer service

(05:34) Using AI and human expertise for better customer experiences

(07:47) How Gen AI reduces costs and improves engagement

(09:37) Challenges in customer service design and innovation

(11:32) Moving from hidden chatbots to front-and-center customer interaction

(14:08) Training human agents to work seamlessly with AI

(17:02) Using AI to analyze and improve service interactions

(19:15) Outcome-based pricing vs traditional headcount models

(21:53) Improving contact center roles with AI integration

(25:08) The importance of curating accurate knowledge bases for AI

(28:05) Crescendo’s acquisition of PartnerHero and its impact

(30:39) Scaling customer service with AI-human collaboration

(32:06) Multilingual support: AI in 56 languages

(33:49) The vast market potential of AI-driven customer service

(36:28) How Crescendo is reshaping customer service with AI innovation

(42:42) Building customer profiles for personalized support

In this special episode of the Eye on AI podcast, Sepp Hochreiter, the inventor of Long Short-Term Memory (LSTM) networks, joins Craig Smith to discuss the profound impact of LSTMs on artificial intelligence, from language models to real-time robotics.

Sepp reflects on the early days of LSTM development, sharing insights into his collaboration with Jürgen Schmidhuber and the challenges they faced in gaining recognition for their groundbreaking work.

He explains how LSTMs became the foundation for technologies used by giants like Amazon, Apple, and Google, and how they paved the way for modern advancements like transformers. Topics include:

- The origin story of LSTMs and their unique architecture.
- Why LSTMs were crucial for sequence data like speech and text.
- The rise of transformers and how they compare to LSTMs.
- Real-time robotics: using LSTMs to build energy-efficient, autonomous systems.

The next big challenges for AI and robotics in the era of generative AI. Sepp also shares his optimistic vision for the future of AI, emphasizing the importance of efficient, scalable models and their potential to revolutionize industries from healthcare to autonomous vehicles.

Don’t miss this deep dive into the history and future of AI, featuring one of its most influential pioneers.

(00:00) Introduction: Meet Sepp Hochreiter
(01:10) The Origins of LSTMs
(02:26) Understanding the Vanishing Gradient Problem
(05:12) Memory Cells and LSTM Architecture
(06:35) Early Applications of LSTMs in Technology
(09:38) How Transformers Differ from LSTMs
(13:38) Exploring XLSTM for Industrial Applications
(15:17) AI for Robotics and Real-Time Systems
(18:55) Expanding LSTM Memory with Hopfield Networks
(21:18) The Road to XLSTM Development
(23:17) Industrial Use Cases of XLSTM
(27:49) AI in Simulation: A New Frontier
(32:26) The Future of LSTMs and Scalability
(35:48) Inference Efficiency and Potential Applications
(39:53) Continuous Learning and Adaptability in AI
(42:59) Training Robots with XLSTM Technology
(44:47) NXAI: Advancing AI in Industry