OpenAI's Code Red: Sam Altman's Warning About Google's AI Competition
Tom discusses Sam Altman's internal code red warning to OpenAI staff about Google's competitive threat. Explores the challenges OpenAI faces with profitability and Google's advantages in the AI race.O...
11 Des 20254min
Google's SynthID: The AI Watermark Solution to Combat Deepfakes & AI Image Deception
Tom explores Google's SynthID technology that embeds invisible watermarks in AI-generated images to help detect artificial content. A crucial tool for combating AI slop and maintaining authenticity in...
10 Des 20252min
AI Slop: Why Generic AI Content is Polluting the Internet
Exploring the rise of 'AI slop' - low-quality AI-generated content flooding social media and the web. Learn how to use AI responsibly while maintaining authenticity and quality.Episode Show NotesKey T...
9 Des 20254min
React to Shell Bug Meets AI: The New Cybersecurity Threat Landscape
Tom explores how the critical React to Shell vulnerability intersects with AI-powered cyber attacks. Learn why this matters for businesses and how to protect your organization.Show NotesKey Topics Cov...
8 Des 20253min
Why Your AI Projects Fail: The Critical Role of Data Integrity
AI projects often fail due to poor data quality. Tom Barber explores why data integrity is crucial for AI success and how to avoid costly mistakes that lead to unreliable results.Episode NotesKey Topi...
3 Des 20255min
Building on AI: How Much Risk Can You Handle?
In this brief on-the-go episode, Tom discusses the risks of building businesses on centralized AI infrastructure. Sparked by Cloudflare's recent major outage, he explores what happens when AI vendors ...
19 Nov 20252min
AI-Orchestrated Cyberattacks: What Executives Need to Know
State-sponsored attackers just used AI to orchestrate sophisticated cyberattacks—and it worked. A recent report reveals how threat actors used Claude Code to execute 80-90% of attack operations automa...
17 Nov 20253min
The Human Side of AI Transformation
The podcast discusses the 10-20-70 rule for AI investment, emphasizing that successful companies allocate 70% of their efforts to people and processes, 20% to data and technology, and only 10% to algo...
14 Nov 20253min
