Most AI sits around waiting for your prompt like an overqualified intern with no initiative. But Agentic AI? It makes plans, takes action, and figures things out—on its own. This isn’t just smarter software—it’s a whole new kind of intelligence. Here’s why the future of AI won’t ask for permission.

Based on the article "Agentic AI - When the Machines Start Taking Initiative" by Markus Brinsa.

https://lnkd.in/gqNMYaDZ

Hosted on Acast. See acast.com/privacy for more information.

Everyone wants “ethical AI.” But what about ethical data?

Behind every model is a mountain of training data—often scraped, repurposed, or just plain stolen. In this article, I dig into what “ethically sourced data” actually means (if anything), who defines it, the trade-offs it forces, and whether it’s a genuine commitment—or just PR camouflage.

This episode is based on the article "Between Idealism and Reality - Ethically Sourced Data in AI". 

https://lnkd.in/gBBVJi6b

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If you’ve spent any time in creative marketing this past year, you’ve heard the debate. One side shouts “Midjourney makes the best images!” while the other calmly mutters, “Yeah, but Adobe won’t get us sued.” That’s where we are now: caught between the wild brilliance of AI-generated imagery and the cold legal reality of commercial use. But the real story—the one marketers and creative directors rarely discuss out loud—isn’t just about image quality or licensing. It’s about the invisible, messy underbelly of AI training data.

And trust me, it’s a mess worth talking about.

Based on the article "Adobe Firefly vs Midjourney - The Training Data Showdown and Its Legal Stakes" by Markus Brinsa.

https://www.linkedin.com/pulse/adobe-firefly-vs-midjourney-training-data-showdown-its-brinsa-w5vmc

Hosted on Acast. See acast.com/privacy for more information.

Hosted on Acast. See acast.com/privacy for more information.

Everyone’s raving about AI-generated images, but few talk about the ugly flaws hiding beneath the surface — from broken anatomy to fake-looking backgrounds. 

This episode is based on the following articles by Markus Brinsa.

"The Dirty Secret Behind Text-to-Image AI"

https://www.linkedin.com/pulse/dirty-secret-behind-text-to-image-ai-markus-brinsa-rpgnc

"The Myth of the One-Click AI-generated Masterpiece"

https://www.linkedin.com/pulse/myth-one-click-ai-generated-masterpiece-markus-brinsa-v1pwc

"Why AI Fails with Text Inside Images – And How It Could Change"

https://www.linkedin.com/pulse/why-ai-falls-text-inside-images-how-could-change-markus-brinsa-ov5fc

"What's the time? - Chatbots Behaving Badly"

https://www.linkedin.com/pulse/whats-time-chatbots-behaving-badly-markus-brinsa-s5mec

"Chatbots Behaving Badly - Image Generation"

https://www.linkedin.com/pulse/chatbots-behaving-badley-image-generation-markus-brinsa-ukogc

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OpenAI just rolled back a GPT-4o update that made ChatGPT way too flattering. Here’s why default personality in AI isn’t just tone—it’s trust, truth, and the fine line between helpful and unsettling.

This episode is based on the article The Flattery Bug by Markus Brinsa

https://www.linkedin.com/pulse/flattery-bug-chatgpt-openai-just-rolled-back-gpt-4o-markus-brinsa-takic

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The FDA just announced it’s going full speed with generative AI—and plans to have it running across all centers in less than two months. That might sound like innovation, but in a regulatory agency where a misplaced comma can delay a drug approval, this is less “visionary leap” and more “hold my beer.” Before we celebrate the end of bureaucratic busywork, let’s talk about what happens when the watchdog hands the keys to the algorithm.

Written by Markus Brinsa.

Narrated by Andrew Fauxley.

Hosted on Acast. See acast.com/privacy for more information.