Welcome to the AI in Cybersecurity Podcast, your go-to source for understanding how artificial intelligence is transforming digital defense.
In a world where cyber threats evolve by the minute, our defenses must keep up—and AI is the game-changer. From threat detection to machine learning, we break down the latest innovations shaping cybersecurity and provide practical strategies to integrate AI into your security systems.
Why does this matter? Because cybercriminals are already using AI to outpace traditional defenses. This podcast gives you the edge—helping you outthink, outmaneuver, and protect what matters most.
At Starseed AI, we’re committed to making this knowledge accessible to everyone—always free and designed to empower a forward-thinking cybersecurity community.
The future of cybersecurity starts now. Are you ready? Let’s dive in. 

AI in Cybersecurity Podcast – Powered by Starseed AI

AI is redefining cybersecurity, offering unparalleled tools to predict, detect, and prevent threats. Narrow AI is already transforming the industry, automating processes, and increasing efficiency. Meanwhile, AGI, though still a distant goal, represents the next frontier in AI’s potential to secure our digital future.As we harness the power of AI, a thoughtful and ethical approach is essential. By leveraging AI responsibly, organizations can build resilient defenses, ensuring a safer and more secure digital world for everyone.

Chapter 2. Things to Know About AI in Cybersecurity - Starseed AI

🐚 CONCH (CONtrastive learning from Captions for Histopathology) is a vision language foundation model for histopathology, pretrained on currently the largest histopathology-specific vision-language dataset of 1.17M image caption pairs. Compare to other vision language foundation models, it demonstrates state-of-the-art performance across 14 tasks in computational pathology ranging from image classification, text-to-image, and image-to-text retrieval, captioning, and tissue segmentation.

CONCH

HEAL Security Dispatch Daily Digest is a leading cybersecurity podcast hosted by Richard Simmons from London, delivering the latest updates on threats, vulnerabilities, and expert insights with a focus on healthcare and cybersecurity intelligence. Covering critical developments such as Microsoft's inadvertent removal of Copilot AI, cybercriminals leveraging Cascading Style Sheets for data tracking, and AI tools like DeepSeek capable of generating malware, the podcast highlights the evolving digital risks organizations face. Listeners gain insights into steganographic malware hidden in JPEG images, ransomware threats targeting U.S. government entities, and vulnerabilities in GitHub Actions affecting CI/CD environments. Additionally, it explores Cloudflare's adoption of post-quantum encryption, the extradition of a key LockBit ransomware developer, and the persistent challenges posed by advanced persistent threats (APTs). With expert analysis and in-depth reporting, the podcast equips professionals with the knowledge to navigate the dynamic cybersecurity landscape. 
https://healsecurity.com/

Microsoft's Copilot Mishap, Cloudflare’s Quantum Encryption, and AI-Generated Malware Threats

BUFFALO, NY - April 8, 2025 – A new #editorial was #published in Oncotarget, Volume 16, on April 4, 2025, titled “Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques."

Dr. Yashbir Singh from Mayo Clinic and his colleagues discussed how artificial intelligence (AI) can improve liver imaging by recognizing when it might be wrong. This approach, called “uncertainty quantification,” helps clinicians better detect liver cancer and other diseases by pointing out areas in medical scans that need a second look. The authors explain how these AI tools could make imaging results more accurate and reliable, which is especially important when diagnosing serious conditions like liver tumors.

Liver and bile duct imaging is difficult because of the organ’s complex structure and differences in image quality. Even skilled radiologists can struggle to identify small or hidden tumors, especially in patients with liver damage or scarring. The editorial explains how new AI models not only read medical images but also measure their own confidence. When the AI system is unsure, it can alert clinicians to take a closer look. This extra layer of information can reduce missed diagnoses and improve early detection of liver cancer.

One of the most advanced tools described in the editorial is called AHUNet (Anisotropic Hybrid Network). This AI model works with both 2D and 3D images and can highlight which parts of a scan it is most confident about. It performed well when measuring the entire liver and showed how its confidence dropped when scanning smaller or multiple lesions. This feature helps clinicians know when more testing or review is needed.

The authors also looked at other AI models used in liver imaging. Some tools were able to analyze liver fat using ultrasound images and give clinicians both a result and a confidence score. Others improved the speed and accuracy of liver magnetic resonance imaging (MRI) scans, helping to create clear images in less time. These advancements could help hospitals work faster and provide better care.

The editorial highlights how this technology can be especially helpful in smaller clinics. If they do not have liver specialists, they could still use AI systems that flag uncertain results and send them to larger centers for review. Such an approach could improve care in rural or less-resourced areas.

“Radiology departments should develop standardized reporting templates that incorporate uncertainty metrics alongside traditional imaging findings.”

By using AI tools that know when to second-guess themselves, clinicians may soon have more reliable methods for detecting liver cancer and monitoring liver disease. The authors suggest that uncertainty-aware AI may soon become a vital part of everyday medical imaging, supporting faster and more accurate decisions in liver disease care.

DOI: https://doi.org/10.18632/oncotarget.28709

Correspondence to: Yashbir Singh — singh.yashbir@mayo.edu

Video short - https://www.youtube.com/watch?v=Zm0QASQ_YSI

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Keywords: cancer, deep learning, uncertainty quantification, radiology, hepatobiliary imaging

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Oncotarget

AI That Measures Its Own Uncertainty Could Improve Liver Cancer Detection

Welcome to *AI with Shaily*! 🎙️ I’m Shailendra Kumar, your guide through the fascinating and fast-changing world of artificial intelligence. Today, we’re exploring some of the hottest breakthroughs in reinforcement learning (RL) — a powerful machine learning technique that’s transforming industries in 2025.

Imagine a robot on a factory line trying to pick up an oddly shaped object it’s never seen before. Previously, success rates were about 78%, but now, thanks to Google’s QT-Opt algorithm combined with deep learning and massive distributed training, robots are hitting an incredible 96% success rate! 🤖💪 This shows how RL enables machines to learn from trial and error, adapting far beyond what traditional programming can achieve.

But robotics is just the beginning. RL is also driving the future of autonomous vehicles 🚗💨. Self-driving cars use RL to make split-second decisions in complex traffic, continuously improving their policies to maximize safety and efficiency. It’s exciting to wonder: how soon will these cars drive with the intuition of a human behind the wheel?

In business, RL is shaking up supply chain logistics and marketing. For example, platforms like Taobao use multi-agent RL to handle thousands of real-time ad bids simultaneously — like a high-stakes auction where players cooperate and compete at once. The outcome? Marketers get better returns on ad spend, and consumers enjoy more relevant ads without the usual clutter. 📈🛒

Gamers will appreciate how RL is revolutionizing AI opponents. Instead of static behavior, AI agents now adapt dynamically to players’ evolving strategies, making games more challenging, fun, and unpredictable — like playing against a clever friend who’s always one step ahead. 🎮🧠

Financial markets are also tapping into RL. Trading bots powered by RL analyze vast amounts of market data to optimize trades in stocks and cryptocurrencies. These bots can test new strategies risk-free or even outperform human traders in real-time, blending speed, learning, and precision in fascinating ways. 💹🤖

The impact of RL is huge — by 2025, it’s a $122 billion industry and growing rapidly, influencing real-world applications far beyond research labs.

Here’s a tip if you want to get started with RL: begin small! Try OpenAI’s Gym environments or simple simulations before jumping into big projects. RL is all about patience and iteration — like teaching a dog new tricks 🐕✨ — so celebrate every small victory along the way.

I’m reminded of a classic quote: “The best way to predict the future is to create it.” With reinforcement learning, we truly are building the intelligent systems of tomorrow.

If you enjoyed this update, join me on YouTube, Twitter, LinkedIn, or Medium for more AI insights. Don’t forget to subscribe to *AI with Shaily* for your regular dose of AI news, where I break down complex topics into friendly conversations, just like chatting with a friend. 😊📲

What do you think? Have you encountered RL-powered tech in surprising places? Share your stories in the comments — I’d love to hear from you!

Thanks for tuning in! Until next time, keep learning and keep questioning. This is Shailendra Kumar signing off from *AI with Shaily*. 👋🤖✨

Reinforcement Learning Revolution: How AI is Transforming Robots, Cars, and Markets in 2025

Blast off with generative guitar fire and thunderous drums—no algorithm can cage this track.
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Keep in touch with latest releases:
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[Verse 1]  
Spread your chrome-feathered wings across my midnight sky,  
Crack the padlock in your mind—let the phantoms drift on by.  
Don’t go beggin’ for a breadcrumb to keep your hunger fed;  
Kick the dust, we’ll ride a riff that screams inside your head.  

[Chorus 1]  
Fly on, baby—turn it loud, lose control!  
Let the backbeat thunder baptize your soul.  
We were born for roaring amps and outlaw heat;  
Fly on, baby—’til the dreamer finds his feet.  

[Verse 2]  
I remember liquid starlight where the rolling surf once lay,  
Now I feel the furnace breathing in a violet solar blaze.  
Be the heartbeat hammer drumming through this rib-cage town;  
I’ll be molten fuel that fires you up when gravity drags you down.  

[Chorus 2]
Burn on, baby—shake the night, let it bleed!  
Ride the tidal pulse of every pounding beat.  
Rock ’n’ roll Salvation’s crashing down our street;  
Burn on, baby—stomp the shadows with your feet.  

[Verse 3]
I’ll carve a rebel scripture on the parchment of the night,  
I'll be the dog-eared book of legends sparking lanterns in your eyes.  
I'll be the outlaw melody tattooed upon my tongue;  
I’ll be every shattered word we shout forever young.  

[Chorus 3]
Sing on, baby—raise the roof, crack the sky!  
Let the echo of your anthem never die.  
We were ink, we were blood, now we’re fire set free;  
Sing on, baby—write the rest of history.

Padlock to the Sky

You’re tuning into “AI with Shaily,” hosted by Shailendra Kumar, a passionate explorer of the latest advancements in artificial intelligence. 🎙️🤖 In this episode, Shaily dives deep into the intriguing world of lie detection powered by AI, focusing on how Convolutional Neural Networks (CNNs) are revolutionizing our ability to spot deception. 🕵️‍♂️✨

Shailendra explains that CNNs, traditionally famous for image recognition, are now being fine-tuned to tackle one of humanity’s oldest puzzles: distinguishing truth from falsehood. These networks analyze data in layered features—imagine peeling an onion, but instead of layers of skin, it’s layers of pixels, patterns, and subtle signals. This approach allows CNNs to detect microexpressions on faces, voice tone changes, and unusual text phrasing—tiny clues that often slip past traditional algorithms. 👁️🎭🔍

What’s truly groundbreaking is the integration of graph attention networks into these models. This means CNNs don’t just look at isolated signals but understand the broader context, effectively “reading between the lines.” This holistic analysis boosts accuracy in identifying fake news, forged identities, and deceptive speech, making AI-powered lie detection smarter and more reliable than ever. 🧠📊🕸️

Shaily shares a personal reflection on how, early in his career, fraud detection was a tedious process relying on simple keyword searches and manual checks—like trying to catch fish with bare hands in a river full of trout. 🐟🙌 Now, CNNs act like high-tech fishing nets, dramatically enhancing the scope and precision of what can be detected and analyzed. This advancement opens exciting possibilities for law enforcement, security, and digital media integrity, bringing us closer to AI-driven truth verification becoming a practical reality. 🚓🔒🖥️

For AI enthusiasts and developers, Shaily offers a valuable tip: combining multiple data types—text, audio, and video—into a multimodal approach can significantly strengthen lie detection models. It’s like getting multiple expert opinions simultaneously, making the system more robust and reliable. 🎤📹📝

The episode closes with a thought-provoking question: how comfortable would you feel if AI could assess your truthfulness in real time? This technology might shift from science fiction to everyday life sooner than expected, raising important conversations about privacy and ethics. 🤔🔮

Shaily wraps up with a powerful quote highlighting AI’s transformative potential: “Artificial intelligence is the new electricity.” Just as electricity changed the world, AI’s ability to uncover human truthfulness could be the next major force shaping our future. ⚡🌍

Stay connected with Shailendra Kumar on YouTube, Twitter, LinkedIn, and Medium for more insightful discussions on AI. Don’t forget to subscribe, share your thoughts, and keep the conversation alive about whether CNNs in lie detection are a groundbreaking breakthrough or a privacy concern. Until next time, Shaily wishes you clear truths and clean code! 💡💻✨

AI with Shaily: How CNNs Are Revolutionizing Lie Detection and Truth Verification

Short Stories from the Bleeding Edge of AI

AI Angst - S01E01 {A Silicon Valley AI Short Story}

Welcome to *AI with Shaily*, your go-to podcast hosted by Shailendra Kumar, where the exciting world of artificial intelligence unfolds! 🎙️🤖 Whether you're commuting, grabbing a coffee, or just curious about what AI holds for our future, Shaily is here to bring you the freshest updates and insights.

Recently, Shaily shared a fascinating story about a friend in enterprise IT overwhelmed by repetitive workflows and juggling multiple tools just to get simple approvals done. Enter AWS’s new Agentic AI tools—a real game-changer! These AI agents don’t just follow rigid scripts; they autonomously interact across different apps, adapt dynamically, and make decisions with minimal human input. Imagine having a tireless digital assistant that streamlines complex, multi-step business processes effortlessly. 🛠️✨

But AI’s impact goes beyond office automation. Google has introduced “Big Sleep,” a deep learning-powered cybersecurity watchdog. This AI quietly patrols the internet, autonomously detecting and shutting down dormant web domains before hackers can exploit them. Think of it as a vigilant digital night watch securing the web while we sleep soundly. 🌙🛡️

On a deeper level, leading AI researchers from OpenAI, DeepMind, and Anthropic are pushing for greater transparency in AI’s reasoning. They want clearer “chains of thought” inside neural models so users can understand *how* AI reaches its conclusions. This is crucial for building trust—after all, we want to know if our AI assistants truly understand problems or are just guessing. 🧠🔍

However, challenges remain. Studies reveal that large language models can struggle with very long texts, sometimes losing track of the story. Engineers are actively refining AI architectures to keep these models sharp and coherent even in sprawling conversations. 📚🤯

A cautionary note comes from the emergence of a new adversarial attack named “RisingAttacK.” This sneaky method can manipulate AI vision systems—like those used in self-driving cars or medical imaging—tricking them about what they actually see. It’s a stark reminder that as AI gets smarter, we must also strengthen defenses against those trying to deceive it. 🚗⚠️🖼️

On a hopeful front, deep neural networks are revolutionizing healthcare. Introducing UNAGI—not the sushi, but an advanced AI model monitoring idiopathic pulmonary fibrosis, a serious lung disease. By analyzing cellular and genetic data, UNAGI suggests personalized therapies that could dramatically improve patient outcomes. 🫁💡❤️

Shaily’s bonus advice: when exploring AI solutions—be it for business, security, or health—always ask, “How transparent and robust is this AI system?” Understanding not just *what* AI does but *how* it thinks is key to trusting it with critical decisions. 🔑🤝

As we journey into AI’s future, remember Alan Turing’s wise words: *“We can only see a short distance ahead, but we can see plenty there that needs to be done.”* 🌟🔮

If you enjoyed this deep dive into AI innovations and challenges, follow Shailendra Kumar on YouTube, Twitter, LinkedIn, and Medium for more engaging content. Subscribe, share your thoughts, and let’s explore the AI frontier together! 🚀💬

This has been *AI with Shaily*. Stay curious, stay informed. Until next time! 👋😊

AI with Shaily: Exploring Agentic AI, Cybersecurity, and the Future of Trust in Artificial Intelligence

The Daily HEAL Security Dispatch Podcast is a leading source for up-to-the-minute news and deep insights in the realm of healthcare cybersecurity and threat intelligence. 

At the heart of HEAL Security's vision is the commitment to equipping organizations and individuals with rapid, contextually rich cybersecurity updates, establishing itself as a pivotal force in unifying practice and data against the ingenious tactics of criminal and malicious entities. HEAL Security is fervently devoted to constructing a robust resource and community that champions the defense of the healthcare sector against the growing cyber threats from organized crime groups and antagonistic nation-states. Our core focus encompasses the protection of vital IT infrastructures, the security of sensitive patient and clinical information, the safeguarding of critical healthcare systems, and the assurance of continuous, undisturbed patient care services.

Unlock the secrets of data mastery with Shailendra, a 27-year veteran in AI, ML, and Data Science, driving AU$ 6 Billion in transformative value. As the author of 'Making Money out of Data,' their strategies redefine digital success. With expertise honed at IBM and Accenture, they drive innovation and data monetization. Explore how loyalty programs like Flybuys and Everyday Rewards revolutionize business—connect with Shaily today.

Please subscribe on YouTube :

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Rock n roll has been a fun ride but for now county is calling the soul once again. You can easily navigate genres in the Playlist section.

Strumming their way through heartbreak, hilarity, and highway hijinks, The Artificial Home Wreckers are a country rock band like no other. Born from a chance encounter at a roadside diner with a broken jukebox, these renegades of rhythm specialize in songs that sound like a wild Friday night and feel like a hungover Saturday morning.

Their music is a cocktail of twangy guitars, foot-stomping beats, and lyrics that toe the line between tragic and downright ridiculous. From ballads about exes who "borrowed" their truck (and forgot to return it) to anthems about that one unforgettable karaoke night gone horribly wrong, they’ve got a tune for every lovable misfit out there.

Catch them on tour (if their GPS actually works this time), and remember their motto: “Breaking homes one chorus at a time!”

Oncotarget is a primarily oncology-focused, peer-reviewed, open access journal. Papers are published continuously within yearly volumes in their final and complete form and then quickly released to Pubmed.

Oncotarget is now indexed by MEDLINE, PubMed and PMC/PubMed.

Read about the Oncotarget Scientific Integrity Process: https://www.oncotarget.com/scientific_integrity/

Pathologist with an interest in computational pathology

New tracks tagged #DeepLearning