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
How to generate very large images with GANs (Ep. 76)
[RB] Complex video analysis made easy with Videoflow (Ep. 75)
[RB] Validate neural networks without data with Dr. Charles Martin (Ep. 74)
How to cluster tabular data with Markov Clustering (Ep. 73)
Waterfall or Agile? The best methodology for AI and machine learning (Ep. 72)
Training neural networks faster without GPU (Ep. 71)
Validate neural networks without data with Dr. Charles Martin (Ep. 70)
Complex video analysis made easy with Videoflow (Ep. 69)
Episode 68: AI and the future of banking with Chris Skinner [RB]
Episode 67: Classic Computer Science Problems in Python
Episode 66: More intelligent machines with self-supervised learning
Episode 65: AI knows biology. Or does it?
Episode 64: Get the best shot at NLP sentiment analysis
Episode 63: Financial time series and machine learning
Episode 62: AI and the future of banking with Chris Skinner
Episode 61: The 4 best use cases of entropy in machine learning
Episode 60: Predicting your mouse click (and a crash course in deeplearning)
Episode 59: How to fool a smart camera with deep learning
Episode 58: There is physics in deep learning!
Episode 57: Neural networks with infinite layers
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