Data Science at Home – Détails, épisodes et analyse

The hype around Generative AI is real, but is the bubble about to burst? Join me as we dissect the recent downturn in AI investments and what it means for the tech giants like OpenAI and Nvidia. Could this be the end of the AI gold rush, or just a bump in the road?

 

References

• http://garymarcus.com/index.html
• https://garymarcus.substack.com/p/why-the-collapse-of-the-generative?r=8tdk6&utm_source=substack&utm_medium=email
• https://www.theinformation.com/articles/openai-makes-a-60-million-hardware-startup-bet?utm_source=substack&utm_medium=email

 

 

In this insightful episode, we dive deep into the pressing issue of data privacy, where 86% of U.S. consumers express growing concerns and 40% don't trust companies to handle their data ethically. Join us as we chat with the Vice President of Engineering at MetaRouter, a cutting-edge platform enabling enterprises to regain control over their customer data. We explore how MetaRouter empowers businesses to manage data in a 1st-party context, ensuring ethical, compliant handling while navigating the complexities of privacy regulations.

 

Sponsors

• Intrepid AI (https://intrepid.ai) is an AI assisted all-in-one platform for robotics teams. Build robotics applications in minutes, not months

 

References

• https://www.metarouter.io/post/mastering-data-governance-why-governance-at-the-point-of-collection-is-a-must-have 
• https://hubs.ly/Q02HwJly0 
• https://www.metarouter.io/post/why-privacy-sandbox-is-a-good-paradigm-shift-for-consumers 

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

• Intrepid AI is an AI assisted all-in-one platform for robotics teams. Build robotics applications in minutes, not months.
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🔗 Links Mentioned in the Episode:

1. Generative AI for time series: TimeGPT Documentation
2. Lag-llama: GitHub (Note: The benchmark results on this one are pretty horrible)
3. Open source LLM: Olmo Blog Post
4. 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! 😄)

Remember the Netflix challenge?

It was a ton of money for the one who would have cracked the problem of recommending the best possible movie.

Was it a fair challenge? Did it work? Let me tell you what happened...

 

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In this episode Fetch AI CTO Jonathan Ward speaks about decentralization, AI, blockchain for smart cities and the enterprise. Below some great links about collective learning, smart contracts in Rust and the Fetch AI ecosystem.

• Decentralised collective learning: https://github.com/fetchai/colearn
• Smart contracting platform written in Rust https://docs.cosmwasm.com/docs/0.14/
• Fetch.ai cosmwasm contracts for collective learning: https://github.com/fetchai/contract-learn
• How the Colearn system works: https://vimeo.com/440365943

Do you want to know the latest in big data analytics frameworks? Have you ever heard of Apache Arrow? Rust? Ballista? In this episode I speak with Andy Grove one of the main authors of Apache Arrow and Ballista compute engine. Andy explains some challenges while he was designing the Arrow and Ballista memory models and he describes some amazing solutions.

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Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

 

References

 

https://arrow.apache.org/

 

https://ballistacompute.org/

 

https://github.com/ballista-compute/ballista

 

 

 

 

It made already quite some noise in the news, GitHub copilot promises to be your pair programmer for life. In this episode I explain how and what GitHub copilot does. Should developers be happy, scared or just keep coding the traditional way?

 

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Sponsors

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Data from the real world are never perfectly balanced. In this episode I explain a simple yet effective trick to train models with very unbalanced data. Enjoy the show!

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References

• Leo Breiman, Random Forests, 2001
• C. Chen, A. Liaw, L. Breiman, Using Random Forest to Learn Imbalanced Data (2004)

 

In this episode I am with Gilbert Hill, head of strategy at https://tapmydata.com/ We speak about personal data, blockchain and the ability to control it and monetize with another simple yet effective app in the ecosystem.     References

• https://tapmydata.com/
• https://medium.com/@tholder/we-dont-want-your-data-pushing-boundaries-in-data-collection-and-end-to-end-encryption-for-apps-ebd1d5f79df5