machine learning

Deep learning vs tabular models (Ep. 217)

Deep learning methods are not as effective with tabular data. Here is why, and what to do about it.
 
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References
https://paperswithcode.com/methods/category/deep-tabular-learning 
https://m-clark.github.io/posts/2022-04-01-more-dl-for-tabular/
 

Autonomous cars cannot drive. Here is why. (Ep. 210)

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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Amethix works to create and maximize the impact of the world’s leading corporations and startups, so they can create a better future for everyone they serve. We provide solutions in AI/ML, Fintech, Healthcare/RWE, and Predictive maintenance.

Private machine learning done right (Ep. 207)

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
Mithril Security: https://www.mithrilsecurity.io/ 
BindAI GitHub: https://github.com/mithril-security/blindai 
Use cases for BlindAI:Deploy Transformers models with confidentiality: https://blog.mithrilsecurity.io/transformers-with-confidentiality/
Confidential medical image analysis with COVID-Net and BlindAI: https://blog.mithrilsecurity.io/confidential-covidnet-with-blindai/ 
Build a privacy-by-design voice assistant with BlindAI: https://blog.mithrilsecurity.io/privacy-voice-ai-with-blindai/ 
Confidential Computing Explained: https://blog.mithrilsecurity.io/confidential-computing-explained-part-1-introduction/ 
Confidential Computing Consortium: https://confidentialcomputing.io/ 
Confidential Computing White Papers: https://confidentialcomputing.io/white-papers-reports/ 
List of Intel processors with Intel SGX:https://www.intel.com/content/www/us/en/support/articles/000028173/processors.html 
https://github.com/ayeks/SGX-hardware 
Azure Confidential Computing VMs with SGX:Azure Docs: https://docs.microsoft.com/en-us/azure/confidential-computing/confidential-computing-enclaves 
How to deploy BlindAI on Azure: https://docs.mithrilsecurity.io/getting-started/cloud-deployment/azure-dcsv3 
Confidential Computing 101: https://www.youtube.com/watch?v=77U12Ss38Zc 
Rust: https://www.rust-lang.org/ 
ONNX: https://github.com/onnx/onnx
Tract, a Rust inference engine for ONNX models: https://github.com/sonos/tract
 

Is studying AI in academia a waste of time? (Ep. 202)

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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Explore the Complex World of Regulations. Compliance can be overwhelming. Multiple frameworks. Overlapping requirements. Let Arctic Wolf be your guide.Check it out at https://arcticwolf.com/datascience
 
Amethix works to create and maximize the impact of the world’s leading corporations and startups, so they can create a better future for everyone they serve. We provide solutions in AI/ML, Fintech, Healthcare/RWE, and Predictive maintenance.
 

Online learning is better than batch, right? Wrong! (Ep. 200)

In this episode I speak about online learning systems and why blindly choosing such a paradigm can lead to very unpredictable and expensive outcomes.Also in this episode, I have to deal with an intruder :)
 
 
Links
Birman, K.; Joseph, T. (1987). "Exploiting virtual synchrony in distributed systems". Proceedings of the Eleventh ACM Symposium on Operating Systems Principles - SOSP '87. pp. 123–138. doi:10.1145/41457.37515. ISBN 089791242X. S2CID 7739589.
 

Batteries and AI in Automotive (Ep. 193)

In this episode my friend and I speak about AI, batteries and automotive.Dennis Berner, founder of Digitlabs has been operating in the field of automotive and batteries for a long time. His point of views are absolutely a must to listen to. Below a list of the links he mentioned in the show.
https://amethix.com
https://digitlabs.com
https://www.moia.io
https://www.elli.eco
https://www.uber.com
https://www.didiglobal.com/
https://waymo.com/
https://group.mercedes-benz.com/
https://www.fakultaet73.de
https://www.bmw.de
https://www.volkswagen.de
https://cariad.technology/
 

What is spatial data science? With Matt Forest from Carto (Ep. 190)

In this episode I am with Matt Forrest, VP of Solutions Engineering at Carto. We speak about machine learning applied to spatial data, spatial SQL and GIS (Geographic Information System).Enjoy the show!
 
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and by Amethix Technologies
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
Carto https://carto.com
Spatial Feature Engineering: https://geographicdata.science/book/intro.html
CARTO Blog: https://carto.com/blog/
Spatial SQL Resources: https://forrest.nyc/learn-spatial-sql/
Spatial Data Science: https://forrest.nyc/geospatial-python
 

History of data science [RB] (Ep. 188)

How did we get here? Who invented the methods data scientists use every day?
We answer such questions and much more in this wonderful episode with Triveni Gandhi, Senior Data Scientist and Shaun McGirr, AI Evangelist at Dataiku. We cover topics about the history of data science, ethical AI and...
 
This episode is brought to you by Dataiku
With Dataiku, you have everything you need to build and deploy AI projects in one place, including easy-to-use data preparation and pipelines, AutoML, and advanced automation.
 
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and by Amethix Technologies
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
www.historyofdatascience.com
 

Artificial Intelligence and Cloud Automation with Leon Kuperman from Cast.ai (Ep. 187)

In this episode I speak about AI and cloud automation with Leon Kuperman, co-founder and CTO at CAST AI. Formerly Vice President of Security Products OCI at Oracle, Leon’s professional experience spans across tech companies such as IBM, Truition, and HostedPCI.
Enjoy the episode!
 
Chat with me
Join us on Discord community chat to discuss the show, suggest new episodes and chat with other listeners!
 
Sponsored by Amethix Technologies
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.
 
Sponsored by NordVPN
NordVPN protects your privacy while you are online. Get secure and private access to the internet by surfing nordvpn.com/DATASCIENCE or use coupon code DATASCIENCE and get a massive discount.
 
References
https://cast.ai/
Cloud automation https://cast.ai/blog/cloud-automation-in-2021-the-new-normal-in-the-tech-industry/
Cloud cost management https://cast.ai/blog/cloud-cost-management-alone-wont-fix-your-cloud-spend-problem/
Case study on how gross margin could be increased by cloud automation https://cast.ai/blog/the-hidden-shortcut-to-increasing-fintech-gross-margins-cloud-automation/
 
 

Embedded Machine Learning: Part 4 - Machine Learning Compilers (Ep. 185)

In this episode I speak about machine learning compilers, the most important tools to bridge the gap between high level frontends, ML backends and hardware target architectures.
There are several compilers one can choose. Before that, let's get familiar with what a compiler is supposed to do.
Enjoy the episode!
 
Chat with me
Join us on Discord community chat to discuss the show, suggest new episodes and chat with other listeners!
 
Sponsored by Amethix Technologies
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.
 
Links
Amethix Embedded Machine Learning
https://tvm.apache.org/
https://github.com/pytorch/glow
https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html