​ High deployment costs are a growing worry as huge foundation models (e.g., GPT-3.5/GPT-4) (OpenAI, 2023) are deployed in many practical contexts. Although quantization, pruning, compression, and distillation are useful general methods for lowering LLMs’ serving costs, the inference efficiency bottleneck of transformer-based generative models… Read More »Microsoft Research Propose LLMA: An LLM Accelerator To Losslessly Speed Up Large Language Model (LLM) Inference With References Tanushree Shenwai Artificial Intelligence Category – MarkTechPost

​ High deployment costs are a growing worry as huge foundation models (e.g., GPT-3.5/GPT-4) (OpenAI, 2023) are deployed in many practical contexts. Although quantization, pruning, compression, and distillation are useful general methods for lowering LLMs’ serving costs, the inference efficiency bottleneck of transformer-based generative models… Read More »Microsoft Research Propose LLMA: An LLM Accelerator To Losslessly Speed Up Large Language Model (LLM) Inference With References Tanushree Shenwai Artificial Intelligence Category – MarkTechPost

​ MongoDB has released a new shell called mongosh, which is designed to provide an enhanced user experience for working with MongoDB databases. The new shell is intended to replace the existing mongo shell and provides several new features, including better syntax highlighting, improved error… Read More »Working with MongoDB Shell AQSA Spark By {Examples}

​ Both Cassandra and MongoDB are NoSQL databases, and they have numerous similarities as well as differences. MongoDB is frequently used for web and mobile apps that need short development cycles and flexible data models. Cassandra employs applications with a lot of users and high write-throughput.… Read More »Cassandra Vs MongoDB Differences AQSA Spark By {Examples}

​ The sparklyr filter() function is a powerful tool for filtering data rows from DataFrame based on a given condition or SQL expression. Sparklyr package allows you to use Spark capabilities in R programming, it provides an interface between R and Apache Spark. In this sparklyr… Read More »Filter in sparklyr | R Interface to Spark kathiriya1111 Spark By {Examples}

​ The sparklyr filter() function is a powerful tool for filtering data rows from DataFrame based on a given condition or SQL expression. Sparklyr package allows you to use Spark capabilities in R programming, it provides an interface between R and Apache Spark. In this sparklyr… Read More »Filter in sparklyr | R Interface to Spark kathiriya1111 Spark By {Examples}

​ The sparklyr filter() function is a powerful tool for filtering data rows from DataFrame based on a given condition or SQL expression. Sparklyr package allows you to use Spark capabilities in R programming, it provides an interface between R and Apache Spark. In this sparklyr… Read More »Filter in sparklyr | R Interface to Spark kathiriya1111 Spark By {Examples}

​ The sparklyr filter() function is a powerful tool for filtering data rows from DataFrame based on a given condition or SQL expression. Sparklyr package allows you to use Spark capabilities in R programming, it provides an interface between R and Apache Spark. In this sparklyr… Read More »Filter in sparklyr | R Interface to Spark kathiriya1111 Spark By {Examples}

​ The sparklyr filter() function is a powerful tool for filtering data rows from DataFrame based on a given condition or SQL expression. Sparklyr package allows you to use Spark capabilities in R programming, it provides an interface between R and Apache Spark. In this sparklyr… Read More »Filter in sparklyr | R Interface to Spark kathiriya1111 Spark By {Examples}

​ The sparklyr filter() function is a powerful tool for filtering data rows from DataFrame based on a given condition or SQL expression. Sparklyr package allows you to use Spark capabilities in R programming, it provides an interface between R and Apache Spark. In this sparklyr… Read More »Filter in sparklyr | R Interface to Spark kathiriya1111 Spark By {Examples}