Deep Learning

Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)

In this episode of Data Science at Home, we explore the fascinating world of neuromorphic computing — a brain-inspired approach to computation that could reshape the future of AI and robotics. The episode breaks down how neuromorphic systems differ from conventional AI architectures like transformers and LLMs, diving into spiking neural networks (SNNs), their benefits in energy efficiency and real-time processing, and their limitations in training and scalability. Real-world applications are highlighted, including low-power drones, hearing aids, and event-based cameras. Francesco closes with a vision of hybrid systems where neuromorphic chips and LLMs coexist, blending biological inspiration with modern AI.
📚 References
SpikingJelly: https://github.com/fangwei123456/spikingjelly
Norse: https://github.com/norse/norse
IBM TrueNorth: https://research.ibm.com/blog/brain-inspired-chip
Intel Loihi 2: https://www.intel.com/content/www/us/en/research/neuromorphic-computing.html
SpiNNaker: https://apt.cs.manchester.ac.uk/projects/SpiNNaker/
BioRobotics Institute: https://www.santannapisa.it/en/institute/biorobotics
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DSH/Warcoded Kill Chains and Algorithmic Warfare – Autonomy in Targeting and Engagement (Ep. 282)

In this gripping follow-up, we dive into how AI is transforming kinetic operations—from identifying a threat to executing a strike.
🔍 Highlights from this episode:
How AI compresses the OODA loop (Observe, Orient, Decide, Act)
The spectrum of autonomy: human-on-the-loop vs. human-out-of-the-loop
Real-world systems like loitering munitions (Switchblade, Harpy) and Selective Ground Response AI (SGR-AI)
The ethical and legal dimensions of delegating lethal decisions to machines
 
As the lines blur between algorithm and operator, we explore who—or what—is pulling the trigger.
 
 
Sponsors
Warcoded is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don’t just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at amethix.com
 
Warcoded is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai
 
 
#Warcoded #DataScienceAtHome #AI #AutonomousWeapons #MilTech #DefenseTech #KillChain #OODAloop #LAWs #EdgeAI #Podcast

DSH/Warcoded: Eyes and Ears of the Machine – AI Reconnaissance and Surveillance (Ep. 281)

Welcome to DSH/Warcoded
We explore how AI is transforming ISR (Intelligence, Surveillance, Reconnaissance)—from satellite imagery to drone feeds. In this episode:
🔍 Computer vision for target ID📡 Predictive surveillance & pattern-of-life modeling🧠 LLMs for SIGINT & OSINT intelligence briefings🌍 Real-world examples: Ukraine, Gaza & more
Listen now and see how machines are learning to see, predict, and inform at the edge of modern conflict.
 
 
Sponsors
Warcoded is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don’t just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at amethix.com
 
Warcoded is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai
 
#AI #defensetech #ISR #LLM #Warcoded #DataScienceAtHome #OSINT #SIGINT #dronewarfare

Humans vs. Bots: Are You Talking to a Machine Right Now? (Ep. 273)

In this episode of Data Science at Home, host Francesco Gadaleta dives deep into the evolving world of AI-generated content detection with experts Souradip Chakraborty, Ph.D. grad student at the University of Maryland, and Amrit Singh Bedi, CS faculty at the University of Central Florida. 
Together, they explore the growing importance of distinguishing human-written from AI-generated text, discussing real-world examples from social media to news. How reliable are current detection tools like DetectGPT? What are the ethical and technical challenges ahead as AI continues to advance? And is the balance between innovation and regulation tipping in the right direction? 
 
Tune in for insights on the future of AI text detection and the broader implications for media, academia, and policy.
 
Chapters 
 
00:00 - Intro 
00:23 - Guests: Souradip Chakraborty and Amrit Singh Bedi 
01:25 - Distinguish Text Generation By AI 
04:33 - Research on Safety and Alignment of Generative Model 
06:01 - Tools to Detect Generated AI Text  
11:28 - Water Marking
18:27 - Challenges in Detecting Large Documents Generated by AI 
23:34 - Number of Tokens 
26:22 - Adversarial Attack
29:01 - True Positive and False Positive of Detectors 
31:01 - Limit of Technologies 
41:01 - Future of AI Detection Techniques 
46:04 - Closing Thought
 
Subscribe to our new YouTube channel https://www.youtube.com/@DataScienceatHome
 

AI Says It Can Compress Better Than FLAC?! Hold My Entropy 🍿 (Ep. 268)

Can AI really out-compress PNG and FLAC? 🤔 Or is it just another overhyped tech myth? In this episode of Data Science at Home, Frag dives deep into the wild claims that Large Language Models (LLMs) like Chinchilla 70B are beating traditional lossless compression algorithms. 🧠💥
But before you toss out your FLAC collection, let's break down Shannon's Source Coding Theorem and why entropy sets the ultimate limit on lossless compression.
We explore: ⚙️ How LLMs leverage probabilistic patterns for compression 📉 Why compression efficiency doesn’t equal general intelligence 🚀 The practical (and ridiculous) challenges of using AI for compression 💡 Can AI actually BREAK Shannon’s limit—or is it just an illusion?
If you love AI, algorithms, or just enjoy some good old myth-busting, this one’s for you. Don't forget to hit subscribe for more no-nonsense takes on AI, and join the conversation on Discord!
Let’s decode the truth together. Join the discussion on the new Discord channel of the podcast https://discord.gg/4UNKGf3
 
Don't forget to subscribe to our new YouTube channel 
https://www.youtube.com/@DataScienceatHome
 
 
References
Have you met Shannon? https://datascienceathome.com/have-you-met-shannon-conversation-with-jimmy-soni-and-rob-goodman-about-one-of-the-greatest-minds-in-history/
 
 

What Big Tech Isn’t Telling You About AI (Ep. 267)

Are AI giants really building trustworthy systems? A groundbreaking transparency report by Stanford, MIT, and Princeton says no. In this episode, we expose the shocking lack of transparency in AI development and how it impacts bias, safety, and trust in the technology. We’ll break down Gary Marcus’s demands for more openness and what consumers should know about the AI products shaping their lives.
 
Check our new YouTube channel https://www.youtube.com/@DataScienceatHome and Subscribe! 
 
Cool links
https://mitpress.mit.edu/9780262551069/taming-silicon-valley/
http://garymarcus.com/index.html

Kaggle Kommando’s Data Disco: Laughing our Way Through AI Trends (Ep. 265) [RB]

In this episode, join me and the Kaggle Grand Master, Konrad Banachewicz, for a hilarious journey into the zany world of data science trends. From algorithm acrobatics to AI, creativity, Hollywood movies, and music, we just can't get enough. It's the typical episode with a dose of nerdy comedy you didn't know you needed. Buckle up, it's a data disco, and we're breaking down the binary!
 
Sponsors
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🔗 Links Mentioned in the Episode:
Generative AI for time series: TimeGPT Documentation
Lag-llama: GitHub (Note: The benchmark results on this one are pretty horrible)
Open source LLM: Olmo Blog Post
Quantization for LLM: Hugging Face Guide
And finally, don't miss Konrad's Substack for more nerdy goodness! (If you're there already, be there again! 😄)

Careers, Skills, and the Evolution of AI (Ep. 248)

!!WARNING!!
Due to some technical issues the volume is not always constant during the show. I sincerely apologise for any inconvenienceFrancesco
 
 
In this episode, I speak with Richie Cotton, Data Evangelist at DataCamp, as he delves into the dynamic intersection of AI and education. Richie, a seasoned expert in data science and the host of the podcast, brings together a wealth of knowledge and experience to explore the evolving landscape of AI careers, the skills essential for generative AI technologies, and the symbiosis of domain expertise and technical skills in the industry.
 
References
Become a generative AI developer in this FREE code-along series. Learn to build a chatbot using the OpenAI API, the Pinecone API, and LangChain, and learn to build NLP and image applications with Hugging Face. https://www.datacamp.com/ai-code-alongs
Learn to use ChatGPT and the OpenAI API in the OpenAI Fundamentals skill track. https://www.datacamp.com/tracks/openai-fundamentals
Get started with deep learning using PyTorch in the Introduction to Deep Learning with PyTorch course. https://www.datacamp.com/courses/introduction-to-deep-learning-with-pytorch
 
 

Debunking AGI Hype and Embracing Reality [RB] (Ep. 245)

In this thought-provoking episode, we sit down with the renowned AI expert, Filip Piekniewski, Phd, who fearlessly challenges the prevailing narratives surrounding artificial general intelligence (AGI) and the singularity. With a no-nonsense approach and a deep understanding of the field, Filip dismantles the hype and exposes some of the misconceptions about AI, LLMs and AGI. Join us as we delve into the real-world implications of AI, separating fact from fiction, and gaining a firm grasp on the tangible possibilities of AI advancement. If you're seeking a refreshingly pragmatic perspective on the future of AI, this episode is an absolute must-listen.
 
Filip Piekniewski Bio
Filip Piekniewski is a distinguished computer vision researcher and engineer, specializing in visual object tracking and perception. He approaches machine learning with a pragmatic mindset, recognizing its current limitations. Filip earned his Ph.D. from Warsaw University, where he explored neuroscience and later joined Brain Corporation in San Diego. His extensive study of neuroscience inspired him to develop innovative, bio-inspired machine learning architectures. Filip's unique blend of scientific curiosity and software engineering expertise allows him to quickly prototype and implement new ideas. He is known for his realistic perspective on AI, debunking AGI hype and focusing on tangible advancements.
 
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Amethix works to create and maximize the impact of the world’s leading corporations and startups, so they can create a better future for everyone they serve. We provide solutions in AI/ML, Fintech, Defense, Robotics and Predictive maintenance.
 
References
https://twitter.com/filippie509
http://blog.piekniewski.info/ (On limits of deep learning and where to go next with AI.)
 
 

The AI Chip Chat 🤖💻 (Ep. 243)

Dive into the cool world of AI chips with us! 🚀 We're breaking down how these special computer chips for AI have evolved and what makes them different. Think of them like the superheroes of the tech world!
Don't miss out! 🎙️🔍 #AIChips #TechTalk #SimpleScience