Data Science at Home

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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References
https://twitter.com/filippie509
http://blog.piekniewski.info/ (On limits of deep learning and where to go next with AI.)
 
 

Destroy your toaster before it kills you. Drama at OpenAI and other stories (Ep. 244)

Brace yourselves, dear friends! In this episode, we delve into the earth-shattering revelation that OpenAI might have stumbled upon AGI (lol) and we're all just seconds away from being replaced by highly sophisticated toasters (lol lol). Spoiler alert: OpenAI's CEO is just playing 7D chess with the entire human race. So, sit back, relax, and enjoy this totally not ominous exploration into the 'totally not happening' future of 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

Rolling the Dice: Engineering in an Uncertain World (Ep. 242)

Hey there, engineering enthusiasts! Ever wondered how engineers deal with the wild, unpredictable twists and turns in their projects? In this episode, we're spilling the beans on uncertainty and why it's the secret sauce in every engineering recipe, not just the fancy stuff like deep learning and neural networks!
Join us for a ride through the world of uncertainty quantification. Tune in and let's demystify the unpredictable together! 🎲🔧🚀
 
References
https://www.osti.gov/servlets/purl/1428000
https://arc.aiaa.org/doi/pdf/10.2514/6.2010-124
https://arxiv.org/pdf/2001.10411
 
 

How Language Models Are the Ultimate Database(Ep. 241)

In this episode, dive deep into the world of Language Models as we decode their intricate structure, revealing how these powerful algorithms exploit concepts from the past.
But... what if LLMs were just a database?
 
References
https://fchollet.substack.com/p/how-i-think-about-llm-prompt-engineering
 

Elon is right this time: Rust is the language of AI (Ep. 240)

In this episode, I delve into Elon Musk's foresight on the future of AI as he champions Rust programming language. Here is why Rust stands at the forefront of AI technology and the potential it holds.
References
https://github.com/WasmEdge/mediapipe-rs
https://blog.stackademic.com/why-did-elon-musk-say-that-rust-is-the-language-of-agi-eb36303ce341
 

Attacking LLMs for fun and profit (Ep. 239)

As a continuation of Episode 238, I explain some effective and fun attacks to conduct against LLMs. Such attacks are even more effective on models served locally, that are hardly controlled by human feedback.
Have great fun and learn them responsibly.
 
References
https://www.jailbreakchat.com/
https://www.reddit.com/r/ChatGPT/comments/10tevu1/new_jailbreak_proudly_unveiling_the_tried_and/
https://arxiv.org/abs/2305.13860
 

Unlocking Language Models: The Power of Prompt Engineering (Ep. 238)

Join me on an enlightening journey through the world of prompt engineering. Explore the multifaceted skills and strategies involved in harnessing the potential of large language models for various applications. From enhancing safety measures to augmenting models with domain knowledge, learn how prompt engineering is shaping the future of AI.
 
References
https://arxiv.org/pdf/2109.01652.pdf
https://arxiv.org/abs/2201.11903
https://arxiv.org/abs/2302.00923
https://www.mihaileric.com/posts/a-complete-introduction-to-prompt-engineering
https://www.axios.com/2023/02/22/chatgpt-prompt-engineers-ai-job

Erosion of Software Architecture Quality in the Age of AI Code Generation (Ep. 237)

In this era of AI-powered code generation, software architects are facing a concerning decline in the quality of their creations. The once meticulously crafted software architectures are now being compromised. Should LLMs be responsible?
 
References
Program Design in the UNIX Environmenthttps://harmful.cat-v.org/cat-v/unix_prog_design.pdf

The new dimension of AI: Vector Databases (Ep. 236)

Let's delve into the emerging trend in database design – or is it really a new trend? The realm of vector databases and their revolutionary influence on AI and ML is making headlines. Come along as we investigate how these groundbreaking databases are revolutionizing the landscape of data storage, retrieval, and processing, ultimately unlocking the complete potential of artificial intelligence and machine learning. But are they genuinely as innovative as they seem?
 
References
https://partee.io/2022/08/11/vector-embeddings/
https://blog.det.life/why-you-shouldnt-invest-in-vector-databases-c0cd3f59d23c
https://medium.com/@ryanntk/choosing-the-right-embedding-model-a-guide-for-llm-applications-7a60180d28e3