Why future applications of AI will need higher quality data

Why future applications of AI will need higher quality data

Author: BKBT Productions January 12, 2026 Duration: 35:44
What if the real AI revolution isn't about better models—but about unlocking the data we've been sitting on? Mike McLaughlin [https://www.linkedin.com/in/michael-g-mclaughlin/]—cybersecurity and data privacy attorney, former US Cyber Command—joins us to discuss something most people miss in the AI conversation: we're building the infrastructure for a completely new asset class. The conversation moves past today's headlines and LLM limitations into what becomes possible when we solve the data access problem: Research acceleration at unprecedented scale. Imagine biotech startups accessing decades of pharmaceutical failure data, every null result, every experiment that didn't work. That's years cut from development cycles. That's drugs to market faster. That's lives saved. Universities as innovation accelerators. Right now, research institutions pay to store petabytes of data collecting dust on servers. Mike argues they're sitting on billions in untapped assets to fuel innovation. Beyond synthetic training. The next generation of AI won't be trained on Reddit threads and scraped websites. It'll be trained on high-quality, provenance-verified research data from institutions that have incentive to participate in the ecosystem. Mike's vision isn't just about compliance or risk mitigation. It's about creating the conditions for AI to actually deliver on the promise everyone keeps talking about. The compute exists. The capital exists. The models are improving. What we need now is the mechanism to turn decades of institutional research into fuel for the next wave of moonshot innovation. Mentioned Google licensing deal with Reddit [https://www.reuters.com/technology/reddit-ai-content-licensing-deal-with-google-sources-say-2024-02-22/] Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples [https://arxiv.org/abs/2510.07192] MIT researchers discover new class of antibiotics using machine learning [https://news.mit.edu/2023/using-ai-mit-researchers-identify-antibiotic-candidates-1220] Reducing bacterial infections from hospital catheters using machine learning [https://www.caltech.edu/about/news/aided-by-ai-new-catheter-design-prevents-bacterial-infections]

There’s a lot of noise in the world of technology talk, but Bare Knuckles and Brass Tacks cuts through it with a focus on the people behind the products and the societal currents shaping our digital landscape. Hosts George K and George A steer conversations that are less about specs and hype, and more about real-world consequences. You’ll hear them dig into topics like the messy rollout of new AI tools, the often-invisible backbone of digital infrastructure, and why communities adopt or reject certain technologies. This podcast regularly features guests from various fields who offer unvarnished opinions on what’s genuinely functional and what’s fundamentally flawed in our tech-saturated lives. The discussions move beyond simple commentary to challenge the standard narratives promoted by the tech industry, examining the cultural and social ripples of every new development. It’s a show for anyone who feels that technology coverage often misses the human element-the frustrations, the adaptations, and the ethical dilemmas. Tune in for a grounded, critical, and consistently engaging dialogue that connects the dots between code and culture. This production from BKBT Productions lives up to its name, getting down to the brass tacks of how technology is built and used, with a bare-knuckle honesty that’s increasingly rare.
Author: Language: English Episodes: 100

Bare Knuckles and Brass Tacks
Podcast Episodes
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