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 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
Bridging the gap between data science and data engineering: metrics (Ep. 95)
A big welcome to Pryml: faster machine learning applications to production (Ep. 94)
It's cold outside. Let's speak about AI winter (Ep. 93)
The dark side of AI: bias in the machine (Ep. 92)
The dark side of AI: metadata and the death of privacy (Ep. 91)
The dark side of AI: recommend and manipulate (Ep. 90)
The dark side of AI: social media and the optimization of addiction (Ep. 89)
More powerful deep learning with transformers (Ep. 84) (Rebroadcast)
How to improve the stability of training a GAN (Ep. 88)
What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)
Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)
[RB] How to generate very large images with GANs (Ep. 85)
More powerful deep learning with transformers (Ep. 84)
[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)
What is wrong with reinforcement learning? (Ep. 82)
Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history (Ep. 81)
Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)
[RB] How to scale AI in your organisation (Ep. 79)
Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 78)
Training neural networks faster without GPU [RB] (Ep. 77)
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