Orson Amiri

  In this dynamic episode of Discover Dialogues , Vikramsinh Ghatge—Senior Marketing Director and Editor-in-Chief—sits down with Adam Gale, Field CTO for AI and Cybersecurity at NetApp, for an in-depth discussion on the escalating challenges of data protection in the AI era. With more than 20 years of experience across the finance, public sector, and enterprise technology landscapes, Adam offers a unique blend of technical depth, strategic perspective, and storytelling finesse. The conversation kicks off by retracing Adam’s unexpected entry into tech—starting with a childhood mishap involving a floppy disk and evolving into a career that spans support roles, presales, and strategic leadership. His adaptability and curiosity have helped him thrive across industries, and he shares pivotal moments that shaped his professional path. As the dialogue unfolds, Adam unpacks the mounting cybersecurity risks linked to AI workloads, particularly around AI training datasets. He sheds light on ...

  Detective Del Spooner had a personal stake in solving the mysterious death of Dr. Alfred Lanning, a genius who co-founded U.S. Robotics (USR) and developed Spooner’s advanced robotic arm after a life-changing accident. When Lanning died under strange circumstances, a pre-recorded hologram specifically summoned Spooner to investigate—but only if he asked the right questions. If not, the hologram coldly responded, “You must ask the right questions.” While this scene from the 2004 sci-fi thriller I, Robot is fictional, the message rings true even outside the world of robotics: asking the right questions is often the key to uncovering meaningful answers. Except—when it comes to AI chatbots, that logic takes on a new twist. With modern AI tools, you can ask anything and receive answers instantly. But when the query is complex, how you ask becomes just as important as what you ask. This is the foundation of prompt engineering , a skill many businesses still overlook. Fortunately, Tech...

  In today’s world of “real-time everything”—calls, code, content, and creation—your tech should boost your momentum, not break it. Those freezes? They're not just annoying; they can be critical, especially for professionals and creators. That’s why Intel’s latest move isn’t just about another processor—it's a whole new era. Picture this: Marvel’s cosmic enforcer Nova isn’t fighting aliens this time. He’s battling a more sinister enemy—a network of rogue AI-native machines powered by next-gen chipsets. They're smarter, faster, and more adaptable. His legendary armor? Lagging. His commands? Sluggish. He needs more than brute strength now. He needs edge computing, lightning-fast bandwidth, and intelligent acceleration. And just when it all seems lost, he crashes into an alien world, discovering a mysterious, humming chip beneath a glowing lake. It fuses with his suit—and suddenly, everything changes. Speed returns. The AI begins to cooperate. He’s not fighting the system; he’...

  The screens are still glowing. Caffeine-fueled minds type away as the final hours of a global AI hackathon tick down. Students from around the world are racing against the clock, pushing their ideas — and the machines helping them — to the edge. In one corner, a team stares anxiously at the screen. GPT-4o is writing code, but the output lacks the finesse they need. It’s powerful, yes — but bloated, pricey, and not quite hitting the mark. One developer mutters, “We need something better.” Then, across the room, a solo coder works quietly. No paywalls. No API quotas. Just a clean UI and swift execution. He’s breezing through web research, code generation, and report writing — and he's not even sweating. A judge notices. “What model are you using?” they ask. “Zhipu’s AutoGLM,” he replies coolly. Suddenly, the room buzzes. People start pulling up benchmarks. MMLU. GSM8K. LiveCodeBench. And to everyone’s surprise, Zhipu’s free, open-source agent is not just keeping up — it’s outperfor...

  Imagine AI-powered coding platforms competing in The Great British Bake Off . Only instead of cakes, they're building web apps — and the pressure to impress is just as real. Bolt.New would be the contestant who finishes first: quick, confident, and turning in a polished product before anyone else has even rolled out their dough. It’s built for speed, delivering a clean, functional app in minutes. Lovable.Dev , by contrast, is the methodical perfectionist. It doesn’t rush. Instead, it focuses on structure, layering features with care, and ensuring the final product is not just functional but scalable and beautifully designed. While plenty of AI tools exist, Bolt.New and Lovable.Dev stand out for how uniquely they help developers build smarter. They may differ in approach, but the end goal is the same: to help you — the real judge — create something great with AI. At TechDogs , we believe that comparing these tools head-to-head provides real insights — not just hype. Let’s take ...

  In this compelling episode of Discover Dialogues , Vikramsinh Ghatge, Sr. Marketing Director and Editor-in-Chief at TechDogs, sits down with Neeraj Manik, Vice President & Senior Partner – Intelligent Business Operations at IBM Consulting. With a rich career spanning over 25 years and leadership roles at GE, Genpact, and IBM, Neeraj offers a unique perspective at the intersection of transformation, innovation, and empathy. From his early days in hospitality during the 1990s to now overseeing a billion-dollar AI-first business unit at IBM, Neeraj’s journey illustrates how deep operational insight and people-centric thinking can reshape global enterprises. Episode Highlights: Adoption Over Perfection Neeraj makes a strong case that AI projects don’t fail due to weak tech—but rather because users aren’t engaged. To drive usage, his team intentionally removes fallback options such as human email support, making the AI system the only viable path forward. The Right Metrics to Mea...

  Remember those toy bows and arrows from childhood? Some arrows stuck to the target—others didn’t. The ones that stuck had more power. That’s exactly how AI changes the game in cybersecurity: it turns ordinary cyber-attacks into powerful, persistent threats. In this analogy: Cyber-attacks = Arrows AI = Bow Organizations = Target On their own, cyber-attacks can be harmful. But with AI behind them, they become smarter, faster, and harder to detect. These AI-driven attacks adapt in real time, craft convincing content, and exploit even the most secure systems. What Are AI-Powered Attacks? AI-powered attacks leverage technologies like machine learning (ML) and natural language processing (NLP) to breach systems. They generate realistic phishing emails, deepfakes, and malware that mimic human behavior—making traditional security measures less effective. These attacks learn and evolve—just like AI models themselves. Types of AI-Driven Threats Here are key types of AI-powered...