Join us in a dynamic conversation with Yori Lavi, Field CTO at SQream, as we unravel the data analytics landscape. From debunking the data lakehouse hype to SQream's GPU-based magic, discover how extreme data challenges are met with agility.
Yori shares success stories, insights into SQream's petabyte-scale capabilities, and a roadmap to breaking down organizational bottlenecks in data science.
Dive into the future of data analytics with SQream's commitment to innovation, leaving legacy formats behind and leading the charge in large-scale, cost-effective data projects.
Tune in for a dose of GPU-powered revolution!
References
Test-First machine learning (Ep. 115)
GPT-3 cannot code (and never will) (Ep. 114)
Make Stochastic Gradient Descent Fast Again (Ep. 113)
What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)
[RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)
Rust and machine learning #4: practical tools (Ep. 110)
Rust and machine learning #3 with Alec Mocatta (Ep. 109)
Rust and machine learning #2 with Luca Palmieri (Ep. 108)
Rust and machine learning #1 (Ep. 107)
Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)(Ep. 106)
Compressing deep learning models: rewinding (Ep.105)
Compressing deep learning models: distillation (Ep.104)
Pandemics and the risks of collecting data (Ep. 103)
Why average can get your predictions very wrong (ep. 102)
Activate deep learning neurons faster with Dynamic RELU (ep. 101)
WARNING!! Neural networks can memorize secrets (ep. 100)
Attacks to machine learning model: inferring ownership of training data (Ep. 99)
Don't be naive with data anonymization (Ep. 98)
Why sharing real data is dangerous (Ep. 97)
Building reproducible machine learning in production (Ep. 96)
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