Jack Poller

2 weeks ago | techstrong.ai | Jack Poller

Jack Poller is the founder and principal analyst for Paradigm Technica, an independent research, analyst, and and content creation company. Jack uses his more than 30 years of industry experience across a broad range of security, systems, storage, networking, and cloud-based solutions to help marketing and management leaders develop winning strategies in highly competitive markets.

Feb 27, 2025 | linkedin.com | Jack Poller

The Identity Crisis Identity has emerged as the single greatest cybersecurity threat facing organizations today. The statistics are alarming: According to the 2024 Verizon Data Breach Investigations Report (DBIR): Stolen credentials, phishing, and vulnerability exploitation remain the top three attack vectors. Security incidents and confirmed breaches have doubled since last year.

Feb 26, 2025 | linkedin.com | Jack Poller

The AI landscape has evolved into a two-tiered ecosystem: a select few tech giants handle the resource-intensive task of training massive AI models, while thousands of organizations focus on deploying these models through inferencing—applying pre-trained intelligence to solve real-world problems. This division of labor has democratized access to AI capabilities, allowing companies to harness sophisticated AI without investing billions in training infrastructure.

Feb 25, 2025 | linkedin.com | Jack Poller

Beneath AI’s promise of enhanced productivity and competitive advantage lies a formidable challenge: building and managing the infrastructure to support AI. Organizations deploying open-source AI models face a maze of resource management complexities, data privacy concerns, and the sobering reality of underutilized, expensive hardware. These obstacles aren't just technical footnotes—they're significant barriers preventing businesses from fully capitalizing on AI's potential.

Feb 18, 2025 | linkedin.com | Jack Poller

Artificial intelligence isn't just changing the world—it's redefining what's possible. As organizations rush to harness AI's transformative power, they discover that building effective, efficient, and performant AI systems is far more complex than simply deploying more computing power. It's a multifaceted challenge that demands new ways of thinking about performance, efficiency, and success.