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 100

APIs Benchmark Best practices Engineering 100

AWS Machine Learning

JUNE 21, 2024

The application’s frontend is accessible through Amazon API Gateway , using both edge and private gateways. When a SageMaker endpoint is constructed, an S3 URI to the bucket containing the model artifact and Docker image is shared using Amazon ECR. The following diagram visualizes the architecture diagram and workflow.

Engineering 125

Engineering Construction Benchmark Advertising 125

AWS Machine Learning

JUNE 6, 2024

Jina Embeddings v2 is the preferred choice for experienced ML scientists for the following reasons: State-of-the-art performance – We have shown on various text embedding benchmarks that Jina Embeddings v2 models excel on tasks such as classification, reranking, summarization, and retrieval.

Benchmark 118

Benchmark Enterprise Construction APIs 118

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 103

Enterprise Construction Engineering Metrics 103

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 133

APIs Benchmark Enterprise Construction 133

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

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 98

Scripts APIs Benchmark Engineering 98

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 112

Construction Metrics industry standards Benchmark 112

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 90

APIs Engineering Construction Benchmark 90

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

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 126

Engineering Accountability Construction APIs 126

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 128

Metrics Scripts Benchmark Enterprise 128

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 87

APIs Engineering Telecommunications Construction 87

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 93

Scripts Benchmark Metrics Transportation 93

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 96

Engineering APIs Construction Benchmark 96

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.

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Calibration Engineering Automotive Analytics 104

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 122

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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, 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 113

Benchmark Metrics Engineering APIs 113

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 132

Benchmark Engineering Construction APIs 132

AWS Machine Learning

APRIL 28, 2025

However, as industries require more adaptive, decision-making AI, integrating tools and external APIs has become essential. Expanding LLM capabilities with tool use LLMs excel at natural language tasks but become significantly more powerful with tool integration, such as APIs and computational frameworks.

APIs 100

APIs Benchmark Scripts Metrics 100

AWS Machine Learning

APRIL 22, 2025

Expanded API schema support with three flexible options to allow seamless integration with applications built on popular API patterns: Message format compatible with the OpenAI Chat Completions API. Chat Completions Message format is compatible with OpenAI Chat Completions API. For more information, see the vLLM Blog.

APIs 75

APIs Engineering Benchmark Telecommunications 75

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 113

Customer Support APIs Engineering Feedback 113

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 113

Finance Benchmark Construction Enterprise 113