Marktechpost

JULY 18, 2023

GitHub Copilot GitHub Copilot is an AI-powered code completion tool that analyzes contextual code and delivers real-time feedback and recommendations by suggesting relevant code snippets. Tabnine Tabnine is an AI-based code completion tool that offers an alternative to GitHub Copilot.

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Flipboard

JUNE 13, 2023

Diamond Bishop , CEO and co-founder at Augmend , a Seattle collaboration software startup Diamond Bishop, CEO of Augmend. Augmend Photo) “AI is making it so small startups like ours can accelerate all aspects of the software development lifecycle. It’s helpful with generating much of the boilerplate for unit tests.

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AWS Machine Learning Blog

JUNE 7, 2023

To do so, we use the auto update dataset capability in Canvas and retrain our existing ML model with the latest version of training dataset. Set up auto update on the existing training dataset and upload new data to the Amazon S3 location backing this dataset. Upon completion, it should create a new dataset version.

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AWS Machine Learning Blog

JULY 1, 2024

Create a knowledge base To create a new knowledge base in Amazon Bedrock, complete the following steps. For Data source name , Amazon Bedrock prepopulates the auto-generated data source name; however, you can change it to your requirements. You should see a Successfully built message when the build is complete. Choose Next.

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AWS Machine Learning Blog

AUGUST 22, 2024

The following figure shows the Discovery Navigator generative AI auto-summary pipeline. As Verisk continues to explore the vast potential of generative AI, the Discovery Navigator auto-summary feature serves as a testament to the company’s dedication to responsible and ethical AI adoption.

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AWS Machine Learning Blog

JULY 25, 2024

This solution is applicable if you’re using managed nodes or self-managed node groups (which use Amazon EC2 Auto Scaling groups ) on Amazon EKS. First, it will mark the affected instance in the relevant Auto Scaling group as unhealthy, which will invoke the Auto Scaling group to stop the instance and launch a replacement.

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TheSequence

AUGUST 10, 2023

These AI-powered generative tools have empowered software developers, enabling them to create and maintain code with remarkable ease and significantly enhance their productivity. For example, T5-based models trained with a span denoising objective are ill-suited for auto-regressive generation tasks like code completion.

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AWS Machine Learning Blog

APRIL 19, 2024

Create a solution To set up automatic training, complete the following steps: On the Amazon Personalize console, create a new solution. To set up auto sync, complete the following steps: On the Amazon Personalize console, create a new campaign. Pranesh Anubhav is a Senior Software Engineer for Amazon Personalize.

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AWS Machine Learning Blog

APRIL 25, 2024

The added benefit of asynchronous inference is the cost savings by auto scaling the instance count to zero when there are no requests to process. Prerequisites Complete the following prerequisites: Create a SageMaker domain. He has also developed the advanced analytics platform as a part of the digital transformation journey.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

The integration of these multimodal capabilities has unlocked new possibilities for businesses and individuals, revolutionizing fields such as content creation, visual analytics, and software development. In the metadata.jsonl file, each example is a dictionary that contains three keys named file_name , prompt , and completion.

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AWS Machine Learning Blog

MAY 9, 2023

In addition, you can now use Application Auto Scaling with provisioned concurrency to address inference traffic dynamically based on target metrics or a schedule. In this post, we discuss what provisioned concurrency and Application Auto Scaling are, how to use them, and some best practices and guidance for your inference workloads.

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AWS Machine Learning Blog

OCTOBER 11, 2023

The decode phase includes the following: Completion – After the prefill phase, you have a partially generated text that may be incomplete or cut off at some point. The decode phase is responsible for completing the text to make it coherent and grammatically correct. The default is 32.

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AWS Machine Learning Blog

APRIL 8, 2024

This version offers support for new models (including Mixture of Experts), performance and usability improvements across inference backends, as well as new generation details for increased control and prediction explainability (such as reason for generation completion and token level log probabilities).

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AWS Machine Learning Blog

NOVEMBER 8, 2023

Amazon CodeWhisperer is a generative AI coding companion that speeds up software development by making suggestions based on the existing code and natural language comments, reducing the overall development effort and freeing up time for brainstorming, solving complex problems, and authoring differentiated code.

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AWS Machine Learning Blog

OCTOBER 19, 2023

Solution overview Training a custom moderation adapter involves five steps that you can complete using the AWS Management Console or the API interface: Create a project Upload the training data Assign ground truth labels to images Train the adapter Use the adapter Let’s walk through these steps in more detail using the console.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Auto-resume and healing capabilities One of the new features with SageMaker HyperPod is the ability to have auto-resume on your jobs. Set up your training cluster To create your SageMaker HyperPod cluster, complete the following steps: On the SageMaker console, choose Cluster management under HyperPod Clusters in the navigation pane.

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Unite.AI

SEPTEMBER 13, 2024

Whether you’re an AI engineer, software developer, or researcher, this guide will give you the knowledge to leverage TensorRT-LLM for optimizing LLM inference on NVIDIA GPUs. Kernel Auto-tuning : TensorRT automatically selects the best kernel for each operation, optimizing inference for a given GPU. build/tensorrt_llm*.whl

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AWS Machine Learning Blog

DECEMBER 13, 2023

We use the AWS Neuron software development kit (SDK) to access the AWS Inferentia2 device and benefit from its high performance. The complete code samples with instructions can be found in this GitHub repository. Engine to use: MXNet, PyTorch, TensorFlow, ONNX, PaddlePaddle, DeepSpeed, etc.

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AWS Machine Learning Blog

AUGUST 5, 2024

Next, we perform auto-regressive token generation where the output tokens are generated sequentially. This means we will be repeating this process more times to complete the response, resulting in slower overall processing. You can also use NeuronAutoModelForCausalLM which will attempt to auto-detect which decoder to use.

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AWS Machine Learning Blog

JUNE 23, 2023

Another option is to download complete data for your ML model training use cases using SageMaker Data Wrangler processing jobs. After you check out the data type matching applied by SageMaker Data Wrangler, complete the following steps: Choose the plus sign next to Data types and choose Add analysis. This is a one-time setup.

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AWS Machine Learning Blog

JULY 9, 2024

When the job is complete, you can deploy to an endpoint and test the model predictions. After the optimization job is complete, you can deploy the model or run further evaluation jobs on the optimized model. If config name is lmi-optimized , that means the configuration is pre-optimized by SageMaker.

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AWS Machine Learning Blog

JUNE 13, 2023

LMI DLCs are a complete end-to-end solution for hosting LLMs like Falcon-40B. You can monitor the status of the endpoint by calling DescribeEndpoint , which will tell you when everything is complete. He has more than 15 years working with technology, from software development, infrastructure, serverless, to machine learning.

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NVIDIA

JUNE 7, 2024

In early trials, cuOpt delivered routing solutions in 10 seconds , achieving a 90% reduction in cloud costs and enabling technicians to complete more service calls daily. The company found that data scientists were having to remove features from algorithms just so they would run to completion.

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AWS Machine Learning Blog

DECEMBER 4, 2023

The project was completed in a month and deployed to production after a week of testing. She has 12 years of software development and architecture experience. We used GPU jobs that help us run jobs that use an instance’s GPUs. The following diagram shows the solution’s architecture.

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NVIDIA

AUGUST 8, 2023

The suite of GPU-accelerated software development kits and cloud-native microservices lets users deploy AI features that enhance audio, video and augmented-reality effects for real-time communications services and platforms.

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AWS Machine Learning Blog

MAY 31, 2023

Complete the following steps: Launch the provided CloudFormation template. When the stack is complete, you can move to the next step. Complete the following steps: On the Amazon ECR console, create a new repository. To do a complete cleanup, delete the CloudFormation stack to remove all resources created by this template.

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AWS Machine Learning Blog

OCTOBER 8, 2024

In this blog post, we explore a comprehensive approach to time series forecasting using the Amazon SageMaker AutoMLV2 Software Development Kit (SDK). In the training phase, CSV data is uploaded to Amazon S3, followed by the creation of an AutoML job, model creation, and checking for job completion.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. Following are the steps completed by using APIs to create and share a model package group across accounts. It can take up to 20 minutes for the setup to complete. sagemaker_client = boto3.client("sagemaker")

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AWS Machine Learning Blog

NOVEMBER 30, 2023

You can also edit the auto scaling policy on the Auto-scaling tab on this page. Deploy a SageMaker JumpStart LLM To deploy a SageMaker JumpStart LLM, complete the following steps: Navigate to the JumpStart page in SageMaker Studio. More details on adding, removing, and testing models are covered in the following sections.

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AWS Machine Learning Blog

AUGUST 4, 2023

With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface. Make sure to disable sampling when importing the data.

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AWS Machine Learning Blog

JUNE 11, 2024

Launch the instance using Neuron DLAMI Complete the following steps: On the Amazon EC2 console, choose your desired AWS Region and choose Launch Instance. You can update your Auto Scaling groups to use new AMI IDs without needing to create new launch templates or new versions of launch templates each time an AMI ID changes.

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AWS Machine Learning Blog

MAY 4, 2023

For ultra-large models that don’t fit into a single accelerator, data flows directly between accelerators with NeuronLink, bypassing the CPU completely. These endpoints are fully managed and support auto scaling. xlarge" ) Refer to Developer Flows for more details on typical development flows of Inf2 on SageMaker with sample scripts.

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Unite.AI

AUGUST 1, 2023

GPT-4: Prompt Engineering ChatGPT has transformed the chatbot landscape, offering human-like responses to user inputs and expanding its applications across domains – from software development and testing to business communication, and even the creation of poetry.

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AWS Machine Learning Blog

JULY 31, 2023

A perfect F1 score of 1 indicates that the model has achieved both perfect precision and perfect recall, and a score of 0 indicates that the model’s predictions are completely wrong. Finally, when it’s complete, the pane will show a list of columns with its impact on the model. Indrajit is an AWS Enterprise Sr. Solutions Architect.

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The MLOps Blog

FEBRUARY 27, 2023

You would address it in a completely different way, depending on what’s the problem. 2 The more interesting ones are the ones that don’t have the data science teams, or sometimes they don’t even have software developers in the way that they are companies that live in the 21st century. Sabine: Oh yes.

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AWS Machine Learning Blog

APRIL 17, 2023

SageMaker LMI containers includes model download optimization by using the s5cmd library to speed up the model download time and container startup times, and eventually speed up auto scaling on SageMaker. A complete example that illustrates the no-code option can be found in the following notebook.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Llama 2 stands at the forefront of AI innovation, embodying an advanced auto-regressive language model developed on a sophisticated transformer foundation. The complete example is shown in the accompanying notebook. Its model parameters scale from an impressive 7 billion to a remarkable 70 billion.

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