AWS Machine Learning

JUNE 15, 2023

We demonstrate how to use the AWS Management Console and Amazon Translate public API to deliver automatic machine batch translation, and analyze the translations between two language pairs: English and Chinese, and English and Spanish. In this post, we present a solution that D2L.ai

APIs 88

APIs Benchmark Best practices Engineering 88

AWS Machine Learning

JUNE 9, 2023

The pre-trained GNN embeddings show a 24% improvement on a shopper activity prediction task over a state-of-the-art BERT- based baseline; it also exceeds benchmark performance in other ads applications.” Basically, by using the API of this layer, you can focus on the model development without worrying about how to scale the model training.

Enterprise 99

Enterprise Construction Engineering Metrics 99

AWS Machine Learning

SEPTEMBER 12, 2024

On Hugging Face, the Massive Text Embedding Benchmark (MTEB) is provided as a leaderboard for diverse text embedding tasks. It currently provides 129 benchmarking datasets across 8 different tasks on 113 languages. medium instance to demonstrate deploying the model as an API endpoint using an SDK through SageMaker JumpStart.

APIs 126

APIs Benchmark Enterprise Construction 126

JivoChat

JUNE 20, 2022

You will learn the best practices and coding conventions for writing Java code, and how to program using Java 8 constructs like Lambdas and Streams. Data and time API. Rest API Testing (Automation) from Scratch-Rest Assured Java. Main topics: Rest API basics and terminology. API testing using Postman. Input-output.

APIs 75

APIs Benchmark Best practices Construction 75

Cincom

MARCH 20, 2025

One morning, he received an urgent request from a large construction firm that needed a specialized generator setup for a multi-site project. 4- Improving Deal Closure Rates with Real-Time Insights CPQ provides real-time analytics on customer preferences, pricing trends, and competitor benchmarks.

B2B 40

B2B Sales CRM Finance 40

AWS Machine Learning

JULY 26, 2023

We compile the UNet for one batch (by using input tensors with one batch), then use the torch_neuronx.DataParallel API to load this single batch model onto each core. The directory path for the compiled model is constructed by joining COMPILER_WORKDIR_ROOT with the subdirectory text_encoder : emb = torch.tensor([.])

Scripts 91

Scripts APIs Benchmark Engineering 91

AWS Machine Learning

NOVEMBER 30, 2023

Customers have to leave their development environment to use academic tools and benchmarking sites, which require highly-specialized knowledge. We surveyed existing open-source evaluation frameworks and designed FMEval evaluation API with extensibility in mind.

Construction 105

Construction Metrics industry standards Benchmark 105

AWS Machine Learning

JULY 24, 2023

A recent initiative is to simplify the difficulty of constructing search expressions by autofilling patent search queries using state-of-the-art text generation models. In this section, we show how to build your own container, deploy your own GPT-2 model, and test with the SageMaker endpoint API. model_fp16.onnx gpt2 and predictor.py

APIs 76

APIs Engineering Construction Benchmark 76

AWS Machine Learning

SEPTEMBER 1, 2023

In this scenario, the generative AI application, designed by the consumer, must interact with the fine-tuner backend via APIs to deliver this functionality to the end-users. If an organization has no AI/ML experts in their team, then an API service might be better suited for them. 15K available FM reference Step 1.

Engineering 122

Engineering Accountability Construction APIs 122

AWS Machine Learning

JANUARY 19, 2024

We use the Recognizing Textual Entailment dataset from the GLUE benchmarking suite. Phrase 2: A bearded man pulls a rope We load the textual recognizing entailment dataset from the GLUE benchmarking suite via the dataset library from Hugging Face within our training script (./training.py training.py ).

Metrics 116

Metrics Scripts Benchmark Enterprise 116

AWS Machine Learning

JANUARY 20, 2023

After cycles of research and initial benchmarking efforts, CCC determined SageMaker was a perfect fit to meet a majority of their production requirements, especially the guaranteed uptime SageMaker provides for most of its inference components. Step-by-step solution Step 1 A client makes a request to the AWS API Gateway endpoint.

APIs 74

APIs Engineering Telecommunications Construction 74

AWS Machine Learning

OCTOBER 27, 2022

Our benchmarks show up to 46% price performance benefit after enabling heterogeneous clusters in a CPU-bound TensorFlow computer vision model training. Performance benchmark results. For more information, refer to Using the SageMaker Python SDK and Using the Low-Level SageMaker APIs. Heterogeneous clusters at Mobileye.

Scripts 80

Scripts Benchmark Metrics Transportation 80

AWS Machine Learning

OCTOBER 5, 2022

We also share the key technical challenges that were solved during construction of the Face-off Probability model. To make an informed decision, we performed a series of benchmarks to verify SageMaker latency and scalability, and validated that average latency was less than 100 milliseconds under the load, which was within our expectations.

Calibration 102

Calibration Engineering Automotive Analytics 102

AWS Machine Learning

DECEMBER 6, 2022

The Trainer class provides an API for feature-complete training in PyTorch. To answer this question, we select an attack recipe from the TextAttack library and use it to construct perturbed adversarial examples to fool our target toxicity filtering model. outputs = 1 * (pred.predictions >= 0.5) Model performance evaluation.

Engineering 85

Engineering APIs Construction Benchmark 85

AWS Machine Learning

MAY 7, 2024

To deploy a model from SageMaker JumpStart, you can use either APIs, as demonstrated in this post, or use the SageMaker Studio UI. The following section details the benchmark’s performance overall, and against each intent. In this example, we use Llama-2-70b-chat, but you might use a different model depending on your use case.

Engineering 115

Engineering Chatbots Technical Support Best practices 115

AWS Machine Learning

SEPTEMBER 28, 2023

In this post, we describe the enhancements to the forecasting capabilities of SageMaker Canvas and guide you on using its user interface (UI) and AutoML APIs for time-series forecasting. While the SageMaker Canvas UI offers a code-free visual interface, the APIs empower developers to interact with these features programmatically.

APIs 111

APIs Construction Finance Enterprise 111

AWS Machine Learning

NOVEMBER 29, 2023

Each trained model needs to be benchmarked against many tasks not only to assess its performances but also to compare it with other existing models, to identify areas that needs improvements and finally, to keep track of advancements in the field. These benchmarks have leaderboards that can be used to compare and contrast evaluated models.

Benchmark 101

Benchmark Metrics Engineering APIs 101

AWS Machine Learning

AUGUST 2, 2024

We partnered with Keepler , a cloud-centered data services consulting company specialized in the design, construction, deployment, and operation of advanced public cloud analytics custom-made solutions for large organizations, in the creation of the first generative AI solution for one of our corporate teams.

APIs 111

APIs Analytics Chatbots Engineering 111

AWS Machine Learning

NOVEMBER 9, 2022

Your application simply needs to include an API call with the target model to this endpoint to achieve low-latency, high-throughput inference. To deploy, use the endpoint_from_production_variant construct to create the endpoint. Deploying an MVE is also very straightforward. This implies each variant receives 50% of the total traffic.

Best practices 52

Best practices Construction Metrics Enterprise 52

AWS Machine Learning

NOVEMBER 29, 2024

With this capability, you can now optimize your prompts for several use cases with a single API call or a click of a button on the Amazon Bedrock console. In this post, we discuss how you can get started with this new feature using an example use case in addition to discussing some performance benchmarks.

Benchmark 123

Benchmark Engineering Construction APIs 123

AWS Machine Learning

FEBRUARY 20, 2025

Solution overview The following diagram showcases a high-level architectural data flow that highlights various AWS services used in constructing the solution. The Amazon Bedrock unified API and robust infrastructure provided the ideal platform to develop, test, and deploy LLM solutions at scale.

Customer Support 104

Customer Support APIs Engineering Feedback 104

AWS Machine Learning

JANUARY 14, 2025

For example, in a network of agents working on software development, a coordinator agent can manage overall planning, a programming agent can generate correct code and test cases, and a code review agent can provide constructive feedback on the generated code. We refer to this approach as assertion-based benchmarking.

Finance 101

Finance Benchmark Construction Enterprise 101