97% false positives. Millions of alerts daily. Security tools that can't keep up. The threat landscape has outpaced traditional security operations—and Agentic AI is the answer.

In this episode, hosts Mac Goswami and Sam Dey sit down with Ramya Ganesh, Top 50 Women Cybersecurity Leads in the US and AI leader at Cisco, to break down how autonomous AI agents are transforming cybersecurity from detection to response.

Key Insights:

Multi-Agent Systems Beat Single Models — Like a hospital with specialists, multiple focused agents outperform one generalist AI. Modular, scalable, explainable, resilient.

The Future SOC — Not humans vs. AI, but humans supervising teams of AI agents handling continuous telemetry while analysts focus on strategic decisions.

Agentic AI vs. AI-Assisted Tools — Speed, autonomy, and cross-system correlation distinguish today's agentic platforms from yesterday's alert dashboards.

POC to Production — Most AI initiatives fail because they start with technology, not business problems. Success requires measurable metrics and governance discipline before deployment.

For Women in Tech — Stay curious, experiment, share what you build publicly. Imposter syndrome is real but community and visibility accelerate growth.

Ramya's takeaway: "The companies seeing the greatest AI success aren't those with the most advanced models—they're the ones with the strongest discipline around AI adoption."

Connect with Ramya: https://www.linkedin.com/in/ramya-ganesh-082bb231/

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#AgenticAI #Cybersecurity #WomenInTech #SOC #AsembleAI

What does it take to call out billion-dollar healthcare AI companies when the system is rigged against whistleblowers?

In this episode of Inside Assemble AI, hosts Sam Day and Mac welcome Sergei Polevikov, PhD-trained data scientist, AI entrepreneur, author of the widely-read Substack newsletter AI Health Uncut, and co-host of Digital Health Inside Out. Sergei has spent years investigating irregularities in healthcare AI, from inflated product claims and misleading adoption reports to the structural VC incentives that allow fraud to fester.

This is one of our most candid conversations yet — covering the 10 patterns that predict healthcare AI failure, why the real AI adoption rate in healthcare is nowhere near what industry reports claim, and why human-in-the-loop remains an essential safeguard regardless of how capable foundation models become.

TOPICS COVERED:

→ How Sergei went from healthcare AI founder (WellAI / Chart2Chart) to fraud investigator — and why transparency, not scandal, drives his mission.

→ His 10 healthcare tech failure patterns, including: the Chinese wall between management and teams, investors-as-customers conflicts of interest, smoke-and-mirrors technology, champagne-and-cocaine financial mismanagement, toxic code of silence, founder extortion, and celebrity protection schemes.

→ Why surveys from firms like Menlo Ventures and McKinsey dramatically overstate AI adoption — and what US Census Bureau data covering 30,000+ smaller healthcare organisations actually shows.

→ The structural reason why incumbents like Epic, Optum, and Cigna are disincentivised to build genuinely innovative AI products — and why startups like Abridge are winning despite the odds.

→ What's genuinely working in healthcare AI right now: AI scribes (done well), drug discovery, genomics, and protein structure modelling.

→ His advice for founders entering the healthcare or pharma space: protect your mission when VC money arrives, read every clause in your operating agreement, and choose partners who care about patients — not just their LPs.

RESOURCES & LINKS:

2. Advancing AI in Healthcare: A Comprehensive Review of Best Practices: https://www.sciencedirect.com/science/article/abs/pii/S0009898123003212

3. "Digital Health Inside Out" podcast: https://www.youtube.com/@DigitalHealthInsideOut

CONNECT WITH ASSEMBLE AI:

Subscribe on Apple Podcasts, Spotify, iHeartRadio, and Amazon Music. Follow our YouTube channel and Substack newsletter for more deep dives into AI's real impact across industries. Have a topic you'd like us to explore? Reach out — we welcome new voices and fresh perspectives.

Keywords: healthcare AI, AI fraud, digital health, VC pump and dump, Babylon Health, Olive AI, Theranos patterns, AI scribes, Epic health, healthcare startup, AI adoption, human in the loop, AI compliance, healthcare innovation

68.5 billion euros in EPL betting annually. 1.4 million data points per match. Soccer sits at the absolute center of the AI revolution, and it's transforming the world's most popular sport from officiating to tactical analysis.

In Episode 2 of our "AI in Sports Analytics" series, hosts Sam Dave and Mac Goswami explore how AI fundamentally changed soccer from 2020-2025.

Semi-Automated Offside Detection (EPL 2024-25): Calibrated cameras + AI algorithms measure player positions with centimeter-level precision. Pioneered at 2022 Qatar World Cup, now standard across elite leagues. Processes data faster than humans, eliminating decades of controversial calls.

Player Tracking: Optical systems track each player 25x/second, detecting invisible tactical patterns. Game-changer: Standard TV footage now generates tracking data previously requiring expensive dedicated cameras. Smaller-budget teams access insights once reserved for Barcelona, Manchester City, Bayern Munich.

Match Prediction: 69-78% accuracy with ensemble models. Challenge: Soccer is harder to predict than basketball/baseball due to lower scoring and higher randomness. One lucky deflection can decide a match despite dominating possession.

Tactical Analysis (March 2025 study): Real-time computer vision tracks all players, ball, formations simultaneously. Coaches see which tactical adjustments opponents made in the 67th minute three weeks ago and how they affected passing networks.

Large Events Model (2024): Deep learning framework simulates games from any state. Test tactical approaches against AI-simulated opponents before stepping onto the pitch.

Economic Impact: Sports analytics market: $1.03B (2024) → $2.61B (2030). AI-powered betting analytics provide sophisticated predictions.

AI reveals tactical sophistication fans never saw. That perfect through ball required reading three defenders' positioning, understanding striker's running profile, executing with millimeter precision. AI helps us see genius, not replace it.

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Next: Baseball AI revolution

#SoccerAnalytics #AIFootball #EPL #SportsAnalytics #AsembleAI