On-package memory is one of the factors that made Apple's M-series processors fast, efficient, and compact. With its Core Ultra 200V (Lunar Lake) processors, Intel...
Robots are moving goods in warehouses, packaging foods and helping assemble vehicles — bringing enhanced automation to use cases across industries.
There are...
Bluesky’s evolution from a low-profile initiative within Twitter to a platform with over 18 million users, at the time of writing, highlights the rapidly...
HP OmniBook Ultra 14
MSRP $1,680.00
“The HP OmniBook Ultra 14 is fast and efficient, but a couple of shortcomings hold it back.”
Pros
Excellent build quality
Strong productivity performance
Good...
Up rather early to check out and post some of the best of the best Black Friday Deals at Amazon. Be lucky you don’t live where I live as the great white North got dumped on last night with one of the the heaviest snowfalls ever and it hasn’t stopped, so for me, a quick post here and then out to start cleaning the driveway which will take hours! Just a quick look before the posts though!!!! Ok so… Black Friday Deals at Amazon and we are loving the WD_Black SN850x Gen 4 2TB SSD for a $55 drop to an amazing low of $123.99… for 2 TB. Fully backwards compatible, this baby...
Today, Polars released a new GPU engine powered by RAPIDS cuDF that accelerates Polars workflows up to 13x on NVIDIA GPUs, allowing data scientists to process hundreds of millions of rows of data in seconds on a single machine.
https://www.youtube.com/watch?v=AoKeit2Fbmw
Growing data challenges
Traditional data processing libraries like pandas are single-threaded and become impractical to use beyond a few million rows of data. Distributed data processing systems can handle billions of rows but add complexity and overhead for processing small-to-medium size datasets.
There has been a gap in tools that process data efficiently for tens of millions up to a few hundred million rows of data. Such workloads are common for model development, demand forecasting, and logistics in industries...