Data Science at Home

Latest Episodes:

Chatting with ChatGPT: Pros and Cons of Advanced Language AI (Ep. 215) Jan 26, 2023

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In this episode, I'll be discussing the capabilities and limitations of ChatGPT, an advanced language AI model. I'll go over its power to understand and respond to natural language, and its applications in tasks such as language translation and text summarization.
However, I'll also touch on the challenges that still need to be overcome such as bias and data privacy concerns.
Tune in for a comprehensive look at the current state of advanced language AI.

References

https://datascienceathome.com/have-you-met-shannon-conversation-with-jimmy-soni-and-rob-goodman-about-one-of-the-greatest-minds-in-history/

Accelerating Perception Development with Synthetic Data (Ep. 214) Jan 14, 2023

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In this episode I am with Kevin McNamara, founder and CEO of Parallel Domain. We speak about a very effective method to generate synthetic data that is currently in production at Parallel Domain. Enjoy the show! References Parallel Domain Synthetic Data Improves Cyclist Detection (blog post): https://paralleldomain.com/parallel-domain-synthetic-data-improves-cyclist-detection/ Beating the State of the Art in Object Tracking with Synthetic Data: https://paralleldomain.com/beating-the-state-of-the-art-in-object-tracking-with-synthetic-data/ Parallel Domain Open Synthetic Dataset: https://paralleldomain.com/open-datasets/bicycle-detection How Toyota Research Institute Trains Better Computer Vision Models with PD Synthetic Data (interview): https://www.youtube.com/watch?v=QIYttoVxf2w Career Opportunities: https://paralleldomain.com/careers

Edge AI applications for military and space [RB] (Ep. 213) Dec 13, 2022

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From image to 3D model (Ep. 212) Dec 08, 2022

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Is it possible to reconstruct a 3D model from a simple image?

Under certain constraints, it is!
In this episode I tell you how.

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References

https://github.com/isl-org/Open3D

https://huggingface.co/docs/transformers/model_doc/glpn

https://arxiv.org/abs/2201.07436

Machine learning is physics (Ep. 211) Dec 02, 2022

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What if we borrowed from physics some theories that would interpret deep learning and machine learning in general?
Here is a list of plausible ways to interpret our beloved ML models and understand why they works, or they don't.
Enjoy the show!

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Autonomous cars cannot drive. Here is why. (Ep. 210) Nov 21, 2022

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If you think that the problem of self-driving cars has been solved, think twice.
As a matter of fact, the problem of self-driving cars cannot be solved with the technical solutions that companies are currently considering.
Don't get fooled by marketing and PR on social media. Whoever is telling you they solved the problem of driving a vehicle fully autonomously, they are lying.
Here is why.

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Evolution of data platforms (Ep. 209) Nov 08, 2022

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Let's look at the history of data platforms. How did they evolve? Why?
Shall I switch to the latest architecture?
Enjoy the show!

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[RB] Is studying AI in academia a waste of time? (Ep. 208) Nov 02, 2022

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Companies and other business entities are actively involved in defining data products and applied research every year. Academia has always played a role in creating new methods and solutions/algorithms in the fields of machine learning and artificial intelligence.
However, there is doubt about how powerful and effective such research efforts are.
Is studying AI in academia a waste of time?

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Private machine learning done right (Ep. 207) Oct 25, 2022

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There are many solutions to private machine learning. I am pretty confident when I say that the one we are speaking in this episode is probably one of the most feasible and reliable.
I am with Daniel Huynh, CEO of Mithril Security, a graduate from Ecole Polytechnique with a specialisation in AI and data science. He worked at Microsoft on Privacy Enhancing Technologies under the office of the CTO of Microsoft France. He has written articles on Homomorphic Encryptions with the CKKS explained series (https://blog.openmined.org/ckks-explained-part-1-simple-encoding-and-decoding/). He is now focusing on Confidential Computing at Mithril Security and has written extensive articles on the topic: https://blog.mithrilsecurity.io/.

In this show we speak about confidential computing, SGX and private machine learning

References