AWS Machine Learning

NOVEMBER 15, 2023

Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention.

Engineering 98

Engineering APIs Automotive Entertainment 98

AWS Machine Learning

MAY 9, 2024

Verisk has embraced this technology and has developed their own Instant Insight Engine, or AI companion, that provides an enhanced self-service capability to their FAST platform. Coming from a software development and sales engineering background, the possibilities that the cloud can bring to the world excite him.

Engineering 124

Engineering Customer Support APIs Government 124

AWS Machine Learning

NOVEMBER 13, 2024

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. Solution overview The solution outlines how to build a reverse image search engine to retrieve similar images based on input image queries. Engine : Select nmslib. Distance metric : Select Euclidean.

Engineering 99

Engineering Management APIs Healthcare 99

AWS Machine Learning

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

Metrics 76

Metrics APIs Engineering Accountability 76

AWS Machine Learning

MAY 5, 2023

To address the problems associated with complex searches, this post describes in detail how you can achieve a search engine that is capable of searching for complex images by integrating Amazon Kendra and Amazon Rekognition. Users may have to manually filter out unsuitable image results when dealing with complex searches.

Engineering 104

Engineering APIs Scripts Enterprise 104

Beyond Philosophy

MAY 23, 2020

Sutherland says that when you worry about the same things as the competition and run the same metrics for success, you are essentially becoming the same business. Sutherland describes it as a financial engineering, Newtonian-reductionist mindset. Let’s take a closer look at the few we asked him about and what he had to say.

Advertising 258

Advertising Engineering Consulting Consulting 258

Callminer

FEBRUARY 4, 2021

Now more than ever, organizations need to actively manage the Average-Speed-of-Answer (ASA) metric. Older citizens, the unhealthy, and those in low-income areas have always been targets for social engineering. Despite the pandemic, customers have retained the expectation that if they call you, you’ll be there for them.

Call Center 345

Call Center Contact Center Finance Consulting 345

CX Global Media

OCTOBER 15, 2018

More specifically, they must re-engineer not as a set of training events that are delivered at a certain time and in certain places, but instead incorporate learning and development directly and continuously into the daily activities of work. Know Your Metrics. Use a Digital Mindset.

Contact Center 269

Contact Center Morale Call Center Metrics 269

Helpware

JUNE 4, 2024

Measuring and tracking development efficiency has been an ongoing topic of debate and one of the most difficult parts of any engineering manager’s job. As much as at its core programming revolves around 1's and 0's, quantifying the performance of development teams is a far more complicated story than one number can tell.

Metrics 79

Metrics Engineering 79

CCNG

JUNE 14, 2023

Here are some key metrics and approaches to consider: Key Metrics to Assess Customer Engagement and Loyalty In Jeanne Bliss’s book, Chief Customer Officer 2.0: How to Build Your Customer-Driven Growth Engine , "Competency #1 is to Honor and Manage Customers as Assets".

Customer Experience 195

Customer Experience Airlines CCNG Chief Customer Officer 195

Beyond Philosophy

JANUARY 12, 2023

They see that living by numbers and metrics will not provide the big-picture vision that CEOs need. However, the toxins will return if the engine isn’t working well. You have to fix the problem with the experience engine. Carbone believes there will be a rise in distinctive qualitative research and design.

Engineering 195

Engineering Quality management CRM Customer Experience 195

AWS Machine Learning

SEPTEMBER 6, 2024

This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application. FMEval is a comprehensive evaluation suite from Amazon SageMaker Clarify , providing standardized implementations of metrics to assess quality and responsibility. Question Answer Fact Who is Andrew R.

Best practices 82

Best practices Metrics Sales Benchmark 82

AWS Machine Learning

FEBRUARY 26, 2024

In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda. Overview of solution The first thing to consider is that different metrics require different computation considerations. The function invokes the modules.

Metrics 118

Metrics Big data Analytics Engineering 118

Beyond Philosophy

OCTOBER 27, 2022

With the Evaluability Heuristic, we view a complex decision and make it simpler by using a metric that is easy to evaluate. But, like most people, I am not an expert in electrical engineering, so it isn’t very meaningful to me. Providing those things will show in any metric you measure, from NPS to revenue to customer emotions.

Customer centricity 39

Customer centricity Metrics Customer emotions Consulting 39

CCNG

MARCH 30, 2022

Because the culture hasn’t been re-engineered for the remote environment, the agent doesn’t feel emotionally engaged and is lonely. Because there hasn’t been any real coaching or training from the supervisor, the performance metric doesn’t move in a positive direction. What could be wrong?”

Coaching 195

Coaching CCNG Average Handle Time Contact Center 195

AWS Machine Learning

MARCH 27, 2024

In software engineering, there is a direct correlation between team performance and building robust, stable applications. The data community aims to adopt the rigorous engineering principles commonly used in software development into their own practices, which includes systematic approaches to design, development, testing, and maintenance.

Enterprise 97

Enterprise APIs Metrics Engineering 97

AWS Machine Learning

JUNE 20, 2024

Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. This makes it difficult to apply standard evaluation metrics like BERTScore ( Zhang et al.

Metrics 117

Metrics Engineering Accountability Benchmark 117

AWS Machine Learning

JANUARY 4, 2024

Specifically, we discuss the following: Why do we need Text2SQL Key components for Text to SQL Prompt engineering considerations for natural language or Text to SQL Optimizations and best practices Architecture patterns Why do we need Text2SQL? Effective prompt engineering is key to developing natural language to SQL systems.

Best practices 126

Best practices Enterprise Engineering APIs 126

Beyond Philosophy

AUGUST 26, 2021

When we worked with the water utility years ago, we learned that an expensive part of their costs was the field engineer labor. However, we discovered that by investing in the call center, changing the experience a little, and the metrics they were measured by, the employees there could ascertain whether a customer needed a field engineer.

Finance 195

Finance Engineering Best practices Call Center 195

AWS Machine Learning

FEBRUARY 12, 2024

For hyperparameter tuning, a hyperparameter optimization (HPO) job can be initiated, selecting the best model based on the objective metric. This decision is based on a condition metric defined in the configuration file. Training occurs in a distributed manner using Horovod, and the resulting model artifact is stored in Amazon S3.

Engineering 119

Engineering Wait times Metrics Accountability 119

AWS Machine Learning

JANUARY 12, 2023

This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. The overriding goal for The Very Group’s engineering team was to prevent any PII data from reaching documents within Elasticsearch. Overview of solution. Some decisions had to be made to enable the solution.

Engineering 116

Engineering APIs Accountability Metrics 116

AWS Machine Learning

NOVEMBER 15, 2024

Model monitoring of key NLP metrics was incorporated and controls were implemented to prevent unsafe, unethical, or off-topic responses. As an early adopter of Amazon Q Business, engineers from Principal worked directly with the Amazon Q Business team to validate updates and new features.

Chatbots 113

Chatbots Engineering Enterprise Feedback 113

AWS Machine Learning

FEBRUARY 29, 2024

This enables data scientists to quickly build and iterate on ML models, and empowers ML engineers to run through continuous integration and continuous delivery (CI/CD) ML pipelines faster, decreasing time to production for models. Solution overview The proposed framework code starts by reading the configuration files. The model_unit.py

Scripts 101

Scripts Engineering Metrics Best practices 101

AWS Machine Learning

OCTOBER 23, 2023

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. The system is developed by a team of dedicated applied machine learning (ML) scientists, ML engineers, and subject matter experts in collaboration between AWS and Talent.com.

Engineering 98

Engineering Metrics Scripts Construction 98

ShepHyken

AUGUST 22, 2022

My Comment: Here’s an article from the hospitality industry, written by someone on the hotel’s engineering and facility management side. Dan Gingiss, the “Experience Maker,” shares his wisdom on why customers cancel, the right metrics to use, how to handle customers who cancel, and more.

Customer Service 38

Customer Service Airlines B2C B2B 38

AWS Machine Learning

APRIL 24, 2024

Conversational artificial intelligence (AI) assistants are engineered to provide precise, real-time responses through intelligent routing of queries to the most suitable AI functions. Additionally, you can access device historical data or device metrics. The tasks are then run through a series of API calls.

APIs 116

APIs Engineering Metrics Management 116

AWS Machine Learning

OCTOBER 2, 2024

This is often referred to as platform engineering and can be neatly summarized by the mantra “You (the developer) build and test, and we (the platform engineering team) do all the rest!” Amazon Bedrock is compatible with robust observability features to monitor and manage ML models and applications.

Government 105

Government APIs Enterprise Best practices 105

AWS Machine Learning

MAY 13, 2024

In this part of the blog series, we review techniques of prompt engineering and Retrieval Augmented Generation (RAG) that can be employed to accomplish the task of clinical report summarization by using Amazon Bedrock. Prompt engineering helps to effectively design and improve prompts to get better results on different tasks with LLMs.

Healthcare 114

Healthcare Engineering APIs Benchmark 114

Customer Service Life

NOVEMBER 10, 2022

With a bit of digging, we discover a larger bug or problem that may need to be addressed by engineering. Before reporting to engineering we get a sense of how many customers are impacted by the issue. But time metrics are easy targets for managers because they can be tied to reduced costs with relative ease.

Contact Center 132

Contact Center Engineering Average Handle Time Analytics 132

AWS Machine Learning

DECEMBER 19, 2023

Many businesses already have data scientists and ML engineers who can build state-of-the-art models, but taking models to production and maintaining the models at scale remains a challenge. Just like DevOps combines development and operations for software engineering, MLOps combines ML engineering and IT operations.

Analytics 113

Analytics Engineering Government Best practices 113

AWS Machine Learning

APRIL 1, 2024

However, training or fine-tuning these large models for a custom use case requires a large amount of data and compute power, which adds to the overall engineering complexity of the ML stack. Grafana dashboard Now that you understand how your system works on the pod and node level, it’s also important to look at metrics at the cluster level.

Scripts 113

Scripts Engineering Metrics Management 113

Cisco - Contact Center

MARCH 16, 2023

This article is authored by Matt Schmitz, Technical Solutions Specialist, Cisco’s Global Virtual Engineering (GVE) DevNet team. Visit the GVE DevNet GitHub page Where are my Metrics? Networks … Read more on Cisco Blogs

Engineering 89

Engineering Metrics 89

AWS Machine Learning

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The post-inference notification Lambda function collects batch inference metrics and sends an email to the approver to promote the model to the next environment. This post is co-written with Jayadeep Pabbisetty, Sr.

APIs 108

APIs Construction Engineering Analytics 108

AWS Machine Learning

DECEMBER 4, 2024

Available in SageMaker AI and SageMaker Unified Studio (preview) Data scientists and ML engineers can access these applications from Amazon SageMaker AI (formerly known as Amazon SageMaker) and from SageMaker Unified Studio. Comet has been trusted by enterprise customers and academic teams since 2017. To learn more, visit Comet.

Engineering 127

Engineering Enterprise SaaS Management 127

AWS Machine Learning

OCTOBER 28, 2024

Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames. A preprocessor script is a capability of SageMaker Model Monitor to preprocess SageMaker endpoint data capture before creating metrics for model quality.

Scripts 89

Scripts Metrics Engineering Analytics 89