Totango

AUGUST 23, 2022

Touchpoints may involve any medium you use to interact with customers, including: Search engine marketing. This may occur through encountering your brand or product through a search engine result, a search engine ad, a social media post, a video, a review on a technology website, word-of-mouth or other means. Blog content.

B2B 118

B2B Journey mapping SaaS Upselling 118

AWS Machine Learning

AUGUST 3, 2022

In this post, we walk you through the benchmarking process and the results we obtained while working on subsampled datasets. Sampling configuration and benchmarking process. This was done by using a custom script designed to create subsampled datasets in which each entity type appears at least k times, within a minimum of n documents.

Benchmark 79

Benchmark APIs Metrics Scripts 79

AWS Machine Learning

SEPTEMBER 22, 2023

Gone are the days when you need unnatural prompt engineering to get base models, such as GPT-3, to solve your tasks. The script initiates the SFT model using its current weights and then optimizes them under the guidance of a reward model, so that the resulting RLHF trained model aligns with human preference. yaml ppo_hh.py

Engineering 116

Engineering Feedback industry standards Benchmark 116

AWS Machine Learning

AUGUST 16, 2023

Prepare the BigEarthNet-S2 dataset BigEarthNet-S2 is a benchmark archive that contains 590,325 multispectral images collected by the Sentinel-2 satellite. To train the classifier, we create a SageMaker PyTorch Estimator that runs the training script, eval_linear.py. file: init_distributed_mode function in the util.py

Scripts 84

Scripts Analytics Technology Benchmark 84

Comm100

JANUARY 21, 2020

Online customers in the pre-purchase stage typically find companies in one of two ways: on social media or through a search engine. Recommended for you: 8 Proactive Chat Best Practices with Ready-to-Use Scripts. Comm100’s 2020 Live Chat Benchmark Report found that 74.5 Ask us about our free shipping codes!”).

B2C 84

B2C B2B Benchmark Best practices 84

AWS Machine Learning

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

Engineering 121

Engineering Accountability Construction APIs 121

Callminer

AUGUST 1, 2017

Bill Dettering is the CEO and Founder of Zingtree , a SaaS solution for building interactive decision trees and agent scripts for contact centers (and many other industries). Interactive agent scripts from Zingtree solve this problem. Agents can also send feedback directly to script authors to further improve processes.

Contact Center 334

Contact Center Call Center Average Handle Time Real estate 334

SharpenCX

AUGUST 26, 2020

The Agile Manifesto , which is usually your engineering team’s go-to guide for management, can help leaders in every department. Set benchmarks and measure your team on how they perform against them. Reward and recognize those who achieve or surpass your benchmarks and coach up those who don’t. Be a Good Performance Assessor.

Call Center 67

Call Center Abandon rate Management Benchmark 67

AWS Machine Learning

JUNE 17, 2024

PrestoDB is an open source SQL query engine that is designed for fast analytic queries against data of any size from multiple sources. For more information on the TPC-H data, its database entities, relationships, and characteristics, refer to TPC Benchmark H. Twilio needed to implement an MLOps pipeline that queried data from PrestoDB.

Scripts 115

Scripts Engineering Metrics Big data 115

AWS Machine Learning

DECEMBER 6, 2022

In real-world toxicity detection applications, toxicity filtering is mostly used in security-relevant industries like gaming platforms, where models are constantly being challenged by social engineering and adversarial attacks. Social engineers can use this type of characteristic of NLP models to bypass toxicity filtering systems.

Engineering 86

Engineering APIs Construction Metrics 86

Comm100

DECEMBER 7, 2021

This will put you on the right path to manage your expectations, set targets, and benchmark your progress along the way. Keyword chatbots use a simple keyword engine to understand what the visitor is asking and respond with the most appropriate answer. Keyword chatbots.

Chatbots 52

Chatbots Wait times Education Benchmark 52

Comm100

JANUARY 21, 2020

Online customers in the pre-purchase stage typically find companies in one of two ways: on social media or through a search engine. Recommended for you: 8 Proactive Chat Best Practices with Ready-to-Use Scripts. Comm100’s 2020 Live Chat Benchmark Report found that 74.5 Social media vs. SEO reach. Remember: Think proactively.

B2C 40

B2C B2B Benchmark Best practices 40

AWS Machine Learning

JULY 15, 2024

Welocalize benchmarks the performance of using LLMs and machine translations and recommends using LLMs as a post-editing tool. We use the custom terminology dictionary to compile frequently used terms within video transcription scripts. in Mechanical Engineering from the University of Notre Dame. Here’s an example.

Engineering 114

Engineering Entertainment Big data APIs 114

AWS Machine Learning

JULY 26, 2023

We’ll cover fine-tuning your foundation models, evaluating recent techniques, and understanding how to run these with your scripts and models. As an added bonus, we’ll walk you through a Stable Diffusion deep dive, prompt engineering best practices, standing up LangChain, and more. More of a reader than a video consumer?

Scripts 93

Scripts Engineering Benchmark Best practices 93

AWS Machine Learning

APRIL 26, 2024

Code generation DBRX models demonstrate benchmarked strengths for coding tasks. user Write a Python script to read a CSV file containing stock prices and plot the closing prices over time using Matplotlib. The file should have columns named 'Date' and 'Close' for this script to work correctly.

Transportation 119

Transportation Scripts Accountability Benchmark 119

AWS Machine Learning

OCTOBER 31, 2022

Data scientists and machine learning engineers are constantly looking for the best way to optimize their training compute, yet are struggling with the communication overhead that can increase along with the overall cluster size. To get started, follow Modify a PyTorch Training Script to adapt SMPs’ APIs in your training script.

Scripts 75

Scripts Benchmark APIs Engineering 75

AWS Machine Learning

MAY 22, 2024

Customers can more easily locate products that have correct descriptions, because it allows the search engine to identify products that match not just the general category but also the specific attributes mentioned in the product description. The script also merges the LoRA weights into the model weights after training.

Scripts 128

Scripts Engineering Accountability APIs 128

AWS Machine Learning

DECEMBER 16, 2022

Finally, we’ll benchmark performance of 13B, 50B, and 100B parameter auto-regressive models and wrap up with future work. A ready-to-use training script for GPT-2 model can be found at train_gpt_simple.py. You can find an example in the same training script train_gpt_simple.py. Benchmarking performance. 24xlarge nodes.

Benchmark 81

Benchmark Engineering APIs Scripts 81

AWS Machine Learning

NOVEMBER 27, 2023

In this post, we dive deep into the new features with the latest release of LMI DLCs, discuss performance benchmarks, and outline the steps required to deploy LLMs with LMI DLCs to maximize performance and reduce costs. To use SmoothQuant, set option.quantize=smoothquan t with engine = DeepSpeed in serving.properties.

Engineering 109

Engineering Benchmark Scripts Advertising 109

AWS Machine Learning

MARCH 13, 2024

. * The `if __name__ == "__main__"` block checks if the script is being run directly or imported. To run the script, you can use the following command: ``` python hello.py ``` * The output will be printed in the console: ``` Hello, world! Evaluate model on test set, compare to benchmarks, analyze errors and biases.

Benchmark 126

Benchmark Scripts APIs Feedback 126

AWS Machine Learning

NOVEMBER 30, 2023

Note that your model artifacts also include an inference script for preprocessing and postprocessing. If you don’t provide an inference script, the default inference handlers for the container you have chosen will be implemented. Gaurav Bhanderi is a Front End engineer with AI platforms team in SageMaker.

Benchmark 121

Benchmark APIs Scripts Engineering 121

AWS Machine Learning

APRIL 17, 2023

Prompt engineering Prompt engineering refers to efforts to extract accurate, consistent, and fair outputs from large models, such text-to-image synthesizers or large language models. For more information, refer to EMNLP: Prompt engineering is the new feature engineering.

Engineering 93

Engineering Benchmark Scripts industry standards 93

AWS Machine Learning

AUGUST 18, 2022

Machine learning (ML) experts, data scientists, engineers and enthusiasts have encountered this problem the world over. The team’s early benchmarking results show 7.3 The baseline model used in these benchmarking is a multi-layer perceptron neural network with seven dense fully connected layers and over 200 parameters.

Scripts 91

Scripts APIs Benchmark Engineering 91

AWS Machine Learning

APRIL 27, 2023

Trainium support for custom operators Trainium (and AWS Inferentia2) supports CustomOps in software through the Neuron SDK and accelerates them in hardware using the GPSIMD engine (General Purpose Single Instruction Multiple Data engine). The scalar and vector engines are highly parallelized and optimized for floating-point operations.

APIs 85

APIs Engineering Scripts Benchmark 85

AWS Machine Learning

MARCH 14, 2024

We provide an overview of key generative AI approaches, including prompt engineering, Retrieval Augmented Generation (RAG), and model customization. Building large language models (LLMs) from scratch or customizing pre-trained models requires substantial compute resources, expert data scientists, and months of engineering work.

Best practices 124

Best practices Engineering Chatbots Enterprise 124

AWS Machine Learning

JANUARY 19, 2024

The concepts illustrated in this post can be applied to applications that use PLM features, such as recommendation systems, sentiment analysis, and search engines. We use the Recognizing Textual Entailment dataset from the GLUE benchmarking suite. He specializes in Generative AI and Machine Learning Data Engineering.

Metrics 116

Metrics Scripts Benchmark Enterprise 116

Vistio

APRIL 2, 2022

And we also do a couple benchmarking surveys a year for member companies and also have an online forum, some private meeting groups for members to be able to exchange digitally in that environment. And then re-engineer training so that it is multimedia.

Contact Center 52

Contact Center Real estate Customer Service Self service 52

AWS Machine Learning

MAY 31, 2023

In 2018, BERT-large made its debut with its 340 million parameters and innovative transformer architecture, setting the benchmark for performance on NLP tasks. Q: Can I see the model weights and scripts of proprietary models in preview with Amazon SageMaker JumpStart? Each question should have 4 options.

Scripts 81

Scripts Engineering Accountability APIs 81

AWS Machine Learning

JULY 26, 2023

SageMaker LMI containers provide two ways to deploy the model: A no-code option where we just provide a serving.properties file with the required configurations Bring your own inference script We look at both solutions and go over the configurations and the inference script ( model.py ). The container requires your model.py

Scripts 92

Scripts APIs Benchmark Engineering 92

AWS Machine Learning

MAY 8, 2023

To serve models, Triton supports various backends as engines to support the running and serving of various ML models for inference. With kernel auto-tuning, the engine selects the best algorithm for the target GPU, maximizing hardware utilization. Import the ONNX model into TensorRT and generate the TensorRT engine.

Engineering 96

Engineering APIs Best practices Scripts 96

AWS Machine Learning

NOVEMBER 17, 2022

AlexaTM 20B has shown competitive performance on common natural language processing (NLP) benchmarks and tasks, such as machine translation, data generation and summarization. To use a large language model in SageMaker, you need an inferencing script specific for the model, which includes steps like model loading, parallelization and more.

Scripts 100

Scripts APIs Government Engineering 100

AWS Machine Learning

OCTOBER 24, 2022

DL scripts often require boilerplate code, notably the aforementioned double for loop structure that splits the dataset into minibatches and the training into epochs. At the time of this writing, it supports PyTorch and includes 25 techniques—called methods in the MosaicML world—along with standard models, datasets, and benchmarks.

Scripts 90

Scripts Enterprise APIs Benchmark 90

AWS Machine Learning

DECEMBER 16, 2022

In this post, we outline the key benefits and pain points addressed by SageMaker Training Managed Warm Pools, as well as benchmarks and best practices. Benchmarks. We performed benchmarking tests to measure job startup latency using a 1.34 Overview of SageMaker Training Managed Warm Pools. When should you use warm pools?

Best practices 89

Best practices Management Engineering Benchmark 89

AWS Machine Learning

JUNE 6, 2023

The following figure shows a performance benchmark of fine-tuning a RoBERTa model on Amazon EC2 p4d.24xlarge inference with AWS Graviton processors for details on AWS Graviton-based instance inference performance benchmarks for PyTorch 2.0. Run your DLC container with a model training script to fine-tune the RoBERTa model.

Scripts 82

Scripts APIs Benchmark Management 82

AWS Machine Learning

FEBRUARY 16, 2023

Briefly, this is made possible by an installation script specified by CustomActions in the YAML file used for creating the ParallelCluster (see Create ParallelCluster ). You can invoke neuron-top during the training script run to inspect NeuronCore utilization at each node. Jeffrey Huynh is a Principal Engineer in AWS Annapurna Labs.

Scripts 96

Scripts APIs Benchmark Engineering 96

ProProfs Blog

JANUARY 31, 2020

Responding to customer issues quickly through the pre-populated canned responses or scripts can work perfectly well if all you are talking with are robots facing a similar set of issues. There are constant calls, an urge to meet deadlines and a benchmark. Make them share insights via surveys and polls using good online survey software.

Customer Service 78

Customer Service Customer Support Surveys Feedback 78

AWS Machine Learning

AUGUST 22, 2024

Snowflake Arctic is a family of enterprise-grade large language models (LLMs) built by Snowflake to cater to the needs of enterprise users, exhibiting exceptional capabilities (as shown in the following benchmarks ) in SQL querying, coding, and accurately following instructions.

Enterprise 117

Enterprise APIs Benchmark Scripts 117