Howard Holton, the Chief Technology Officer of GigaOm, explores some of the most pressing topics in technology today. With over two decades of experience spanning roles as CTO, CISO, CIO, and consultant, Howard brings a wealth of knowledge to the conversation. His background includes leadership positions at Rheem Manufacturing, Hitachi Vantara, and Precision Discovery, where he honed his expertise in digital transformation, data science, and operational strategy. At GigaOm, Howard combines his technical acumen with a passion for helping organizations navigate the complexities of modern technology landscapes.

The conversation delves into the rapid rise of generative AI (GenAI) and the realities beyond the hype. Howard explains how businesses are grappling with this transformative technology, which, while promising, is rife with complexities. Many organizations rushed into adopting AI without fully understanding its implications, leading to inefficiencies and unexpected risks. He points out that generative AI is a powerful tool but cautions against treating it as a catch-all solution. The conversation highlights how improper use can lead to issues like misinformation, inaccurate outputs, and even legal challenges, underscoring the need for deliberate strategy in deploying AI tools.

Howard also provides an unvarnished look at AI governance and its associated risks. With generative AI being a relatively young technology, governance frameworks are still in their infancy. Organizations often lack cohesive tools to manage the risks associated with AI deployments. This leads to challenges in ensuring compliance with data privacy regulations and safeguarding sensitive information.

Shadow AI emerged as another critical topic in the discussion. Howard describes Shadow AI as the unauthorized use of AI tools by employees, often without the knowledge or approval of management. While employees leverage these tools to improve productivity or efficiency, this practice introduces significant risks to data security and compliance. Sensitive company data may unknowingly be exposed to public large language models (LLMs), creating vulnerabilities and potential regulatory breaches.

Advice for the Tech Community
Closing the episode, Howard offers invaluable advice for professionals navigating the ever-changing tech landscape. He underscores the importance of mentorship, curiosity, and collaboration in driving innovation. “It’s our job to help people,” he says, emphasizing the need for tech leaders to share their knowledge and foster growth within their communities. Howard also encourages organizations to adopt a mindset of continuous learning, particularly as emerging technologies like AI continue to evolve.

For those looking to engage with Howard directly, he is active on LinkedIn and passionate about providing guidance to individuals and businesses alike. He emphasizes that everyone should have access to knowledge and tools that help them succeed. 

LinkedIn: https://www.linkedin.com/in/howardholton/ 

GigaOm: https://gigaom.com/ 



Howard Holton: Weighing ﻿﻿AI Cyber Hype and Risks

HEAL Security Dispatch Daily Digest is your essential cybersecurity podcast, hosted by Richard Simmons from London. Stay updated on the latest threats, trends, and innovations at the intersection of healthcare and cybersecurity.

In today’s episode:

X (formerly Twitter) blocks Signal’s contact links, raising concerns among privacy advocates.
Microsoft reminds admins to prepare for the deprecation of Windows Server Update Services (WSUS) driver syncing.
A new variant of the macOS XCSSET malware evades privacy protections to capture sensitive data.
Pangea introduces AI Guard and Prompt Guard, strengthening security for generative AI technologies.
Chinese hackers exploit Microsoft’s APP-V tool to bypass antivirus defenses undetected.
CISA issues advisories on industrial control system vulnerabilities.
OpenSSH security flaws put servers at risk of MiTM and DoS attacks.
As cyber threats evolve, HEAL Security Dispatch Daily Digest equips you with the insights needed to stay ahead.
🎧 Tune in now: healsecurity.com

HEAL Security Dispatch: Signal Blocked, New macOS Malware, and AI Security Innovations

HEAL Security Dispatch Daily Digest is a cybersecurity-focused podcast presented by HEAL Security, bringing expert insights and the latest developments in the ever-evolving digital security landscape. Hosted by Richard Simmons from London, this podcast explores the critical nexus between healthcare and cybersecurity, covering topics such as quantum-safe encryption, national security decisions impacting cybersecurity, evolving cyber threats, and regulatory actions. Recent discussions include Google's quantum-resistant digital signatures, Australia’s ban on Kaspersky software, a major North Korean cryptocurrency heist, and emerging malware threats. With a strong emphasis on healthcare cybersecurity and broader industry trends, the show provides essential updates to help professionals stay ahead of cyber risks and advancements in security technology. 
https://healsecurity.com/

Google Cloud's Quantum-Safe Security, Australia Bans Kaspersky, and North Korea's $1.5B Crypto Heist

🤖 AI tools like ChatGPT & Copilot boost productivity—but if misused, they can leak sensitive data 😬. From accidental pastes to hacker-driven prompt injections, small businesses are vulnerable. Create a clear AI policy, train your team, use secure platforms & monitor usage. Don’t ban AI—manage it smartly before one click causes chaos. 🔐

Is Your Business Training AI How To Hack You_

Welcome to AI with Shaily! 🎙️ I’m Shailendra Kumar, your host, diving deep into one of the most pressing questions in the world of artificial intelligence: How can we truly trust and ensure the safety of Super AI? 🤖✨ As AI grows smarter every day, it’s not just about what it can do, but *how* it does it—and whether it behaves responsibly in the real world.

Let me share a personal story: A few years back, I worked with an enterprise implementing AI decision tools. Initially, everything seemed perfect, but soon customers noticed some strange recommendations from the system. That’s when I realized intelligence alone isn’t enough; we need transparency and explainability to understand *how* AI arrives at its conclusions. 🔍🧠

To confidently trust Super AI, it must answer some tough questions:

First, can it clearly explain its decision-making process? We need to trace outputs back to specific input data to detect errors or hidden biases. Without this, AI becomes a “black box,” which nobody wants—imagine trusting a doctor who won’t explain their diagnosis! 🏥❓

Next, continuous safeguards are crucial. AI models can “drift” over time, so constant monitoring is essential to catch bias or unintended harm early. Compliance with privacy laws like GDPR and HIPAA isn’t optional—it’s mandatory as regulations tighten worldwide. 🔐📜

Security is another key pillar. Super AI must defend against sneaky attacks like prompt injections or data leaks, using enterprise-grade protections to keep sensitive information safe. After all, if your AI gets hacked, what good is its intelligence? 🛡️⚠️

Failure mode analysis acts like a behind-the-scenes superhero, enabling AI to spot its own errors, explain them, and recover gracefully—think of it as the AI’s self-check to avoid catastrophic mistakes. 🦸‍♂️🔄

Moreover, as AI handles multi-turn conversations and integrates APIs and external tools, maintaining consistent and coherent responses becomes a complex challenge that must be flawlessly managed. 💬🔗

Legal and regulatory compliance is front and center now. New AI-specific laws coming by 2025—especially around automated decision-making and employment—require documented proof of bias testing and prevention. This isn’t just best practice; it’s the law. ⚖️📅

Finally, concrete metrics like Stanford’s CRFM Transparency Index help quantify how explainable and trustworthy a model really is, providing ongoing benchmarks for improvement. 📊✅

Here’s a bonus tip for all curious minds: When evaluating any AI system, ask for its transparency score or similar metrics. If it can’t provide one, treat it like a mystery novel missing its crucial chapters! 📚❌

Why does all this matter? Because AI is increasingly making critical decisions in healthcare, finance, and beyond. We owe it to ourselves and society to demand clarity, security, and fairness. It’s not just about smarter AI; it’s about *responsible* AI. 🌍🤝

Before we wrap up, remember this: “Trust is built not from what you say, but from what you show.” In AI, transparency is that proof. 👁️‍🗨️🔑

Thanks for tuning in to AI with Shaily! Don’t forget to connect with me on YouTube, Twitter, LinkedIn, and Medium for more insights. If you love deep dives like this, subscribe and share your thoughts—I’m eager to hear your take on the trust challenge facing Super AI! 🚀💬

Until next time, keep questioning, keep learning, and stay curious! 🌟🤓

Building Trust in Super AI: The Transparency and Safety Challenge

This episode covers the latest in cybersecurity, from the CORNFLAKE.V3 backdoor and QR code phishing scams to hackers abusing the Internet Archive and cheap VPS services. We also look at Apple’s seventh zero-day patch of the year, new DripDropper malware tactics, and how AI crawler traffic is overwhelming websites.

Cyber Threats on the Rise: New Malware, Phishing Tactics, and AI Traffic Overload

Welcome back to *AI with Shaily*! 🎙️ I’m Shailendra Kumar, your host and AI enthusiast, here to bring you the freshest updates and insights from the world of artificial intelligence. Today’s episode dives into a groundbreaking discovery that’s sending ripples through the AI and cybersecurity communities — a hardware vulnerability named **GPUHammer** 🛠️💥.

This isn’t just another software bug or neural network tweak. Researchers at the University of Toronto have revealed that GPUs, especially powerful models like Nvidia’s RTX A6000 🎮⚡, are susceptible to a sneaky attack inspired by the classic Rowhammer technique. Traditionally, Rowhammer targeted CPU memory by rapidly flipping bits in adjacent rows of DRAM, causing data corruption. But GPUHammer takes this concept further by showing that GPU memory (GDDR) isn’t immune either. This is huge because GPUs are the engines driving AI workloads across industries — from medical imaging 🏥🧠 to fraud detection 💳🔍.

Why should you care? Imagine your AI model’s accuracy plummeting from a solid 80% to a catastrophic 0.1% due to subtle memory bit flips. That’s like asking a doctor with perfect credentials to diagnose you while blindfolded — a scary thought! 😱 GPUHammer works by electrically “hammering” adjacent memory rows to induce bit flips without altering the data or code directly, making the attack stealthy and hard to detect. The University of Toronto team demonstrated this attack live on an Nvidia RTX A6000, proving it’s not just theoretical but a real-world threat. Nvidia is aware and actively working on protective measures 🛡️.

As someone deeply involved in AI development, this revelation hits home. It’s a stark reminder that vulnerabilities don’t just hide in algorithms or datasets — the very hardware we trust to run AI can betray us. This calls for a holistic approach to AI security, one that includes hardware-level safeguards and rigorous fault injection testing 🔍🛠️. For AI practitioners, integrating hardware fault testing into your validation pipeline is a must to catch these subtle glitches before they wreak havoc.

Before we close, here’s a question to mull over: if AI outputs can be silently corrupted at the hardware level, how do we maintain trust and ensure reliability in critical applications like healthcare or finance? 🤔

I’ll leave you with a timeless quote from Alan Turing: “Machines take me by surprise with great frequency.” Today, the surprise lies not just in AI’s capabilities but in the fragility of its foundations.

Don’t forget to follow me, Shailendra Kumar, on YouTube, Twitter, LinkedIn, and Medium for more AI news and engaging discussions. Subscribe to *AI with Shaily* for your weekly AI fix, and share your thoughts in the comments — I’m eager to hear your perspective! Until next time, keep your AI models sharp and your hardware secure. Stay curious, stay safe! 🔐🤖✨

GPUHammer Exposed: The Hidden GPU Vulnerability Threatening AI Accuracy

This episode covers the latest in cybersecurity, from hackers using AI-powered phishing schemes to a new Phoenix Rowhammer attack targeting DDR5 memory. We dive into insider and financial data breaches, Microsoft’s Windows 10 end-of-support warning, and a surge of malicious WhiteCobra extensions in developer tools. Plus, we look at how AI is reshaping clinical trial site selection with major implications for data security.

AI Scams, Insider Threats, and New Cyber Attacks: This Week in Cybersecurity

In this episode, Edd Hall discusses the latest wave of global cyber threats — from Chinese espionage operations using NET-STAR malware to critical vulnerabilities in Palo Alto’s GlobalProtect, Google Gemini AI, and Linux sudo. He also covers CISA’s funding shift for MS-ISAC, the major cyberattack on Asahi Group, hijackings of Microsoft SQL Servers with XiebroC2, and the Harrods data breach impacting hundreds of thousands of customers.

From Chinese Espionage to Corporate Breaches

In this episode, Edd Hall discusses the latest developments in cybersecurity, covering a wide range of critical threats and trends. He explores global cybercrime operations like the UAT-8099 SEO fraud campaign, major breaches affecting platforms such as Discord, and emerging malware like the new Android RAT. Edd also highlights the growth of the healthcare cybersecurity market, the challenges posed by quantum computing, rising payment fraud, AI security considerations, and critical browser vulnerabilities like Chrome’s RCE flaw. Tune in to stay informed and learn how to better protect your data and digital infrastructure.

Healthcare & Cybersecurity Alerts – Quantum Threats, Fraud & Data Breaches

Kitecast features interviews with security, IT, compliance, and risk management leaders and influencers, highlighting best practices, trends, and strategic analysis and insights. Kitecast is cohosted by Tim Freestone and Patrick Spencer who have more than four decades of combined experience in technology and cybersecurity senior leadership roles.

The Daily HEAL Security Dispatch Podcast is a leading source for up-to-the-minute news and deep insights in the realm of healthcare cybersecurity and threat intelligence. 

At the heart of HEAL Security's vision is the commitment to equipping organizations and individuals with rapid, contextually rich cybersecurity updates, establishing itself as a pivotal force in unifying practice and data against the ingenious tactics of criminal and malicious entities. HEAL Security is fervently devoted to constructing a robust resource and community that champions the defense of the healthcare sector against the growing cyber threats from organized crime groups and antagonistic nation-states. Our core focus encompasses the protection of vital IT infrastructures, the security of sensitive patient and clinical information, the safeguarding of critical healthcare systems, and the assurance of continuous, undisturbed patient care services.

Unlock the secrets of data mastery with Shailendra, a 27-year veteran in AI, ML, and Data Science, driving AU$ 6 Billion in transformative value. As the author of 'Making Money out of Data,' their strategies redefine digital success. With expertise honed at IBM and Accenture, they drive innovation and data monetization. Explore how loyalty programs like Flybuys and Everyday Rewards revolutionize business—connect with Shaily today.

New tracks tagged #AIsecurity