AWS Machine Learning Blog

NOVEMBER 15, 2023

Prerequisites The following are prerequisites for completing the walkthrough in this post: An AWS account Familiarity with SageMaker concepts, such as an Estimator, training job, and HPO job Familiarity with the Amazon SageMaker Python SDK Python programming knowledge Implement the solution The full code is available in the GitHub repo.

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Robot Writers AI

JUNE 30, 2024

Specifically, the company is looking to integrate Google’s Gemini AI into its services to auto-write ad scripts, automate ad narration and auto-generate product images. Also promised is a new world-building tool that will enable writers to auto-design fictional worlds ranging from dystopian cities to magical realms.

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AWS Machine Learning Blog

JUNE 13, 2023

The integration of large language models helps humanize the interaction with automated agents, creating a more engaging and satisfying support experience. In addition, deployments are now as simple as calling Boto3 SageMaker APIs and attaching the proper auto scaling policies. The following diagram illustrates our legacy architecture.

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AWS Machine Learning Blog

OCTOBER 8, 2024

SageMaker AutoMLV2 is part of the SageMaker Autopilot suite, which automates the end-to-end machine learning workflow from data preparation to model deployment. 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

MAY 16, 2024

Problem definition Traditionally, the recommendation service was mainly provided by identifying the relationship between products and providing products that were highly relevant to the product selected by the customer. When training is complete (through the Lambda step), the deployed model is updated to the SageMaker endpoint.

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Topbots

AUGUST 22, 2023

auto-evaluation) and using human-LLM hybrid approaches. Thus, holistic evaluation of LLM performance typically entails at least 3 different approaches: Quantitative Metrics : When definitive correct answers exist, you can default to traditional ML evaluation methods using quantitative approaches.

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Flipboard

APRIL 11, 2023

Public ledgers may appear to be a technology looking for a solution, but projects like the State of California’s effort to put auto registration on a blockchain are likely to simplify the painful process of dealing with the Department of Motor Vehicles. However, I wouldn’t write off NFTs and blockchains just yet. Well, partly.

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deepsense.ai

OCTOBER 8, 2023

Usually agents will have: Some kind of memory (state) Multiple specialized roles: Planner – to “think” and generate a plan (if steps are not predefined) Executor – to “act” by executing the plan using specific tools Feedback provider – to assess the quality of the execution by means of auto-reflection.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Automated retraining mechanism – The training pipeline built with SageMaker Pipelines is triggered whenever a data drift is detected in the inference pipeline. It also provides select access to related services, such as AWS Application Auto Scaling , Amazon S3, Amazon Elastic Container Registry (Amazon ECR), and Amazon CloudWatch Logs.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Deploy the CloudFormation stack The CloudFormation stack automates the deployment of the OpenSearch Service domain and SageMaker Notebook instance. Complete the following steps to deploy the stack: Sign in to the AWS Management Console with your credentials in the account where you want to deploy the CloudFormation stack.

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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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The MLOps Blog

JULY 18, 2024

Veriff is an identity verification platform that combines AI-powered automation with human feedback, deep insights, and expertise. The SageMaker MMEs provide auto-scaling and reduce operational overhead. This usually only makes sense for companies with a strategic mindset saying ‘We want to be completely independent.

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The MLOps Blog

FEBRUARY 27, 2023

Stephen: Definitely sounds a whole like the typical project management dilemma. You would address it in a completely different way, depending on what’s the problem. Then what is needed in such cases is definitely this awareness that by being open, we may not be able to specify how good something will work in the first place.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

Amazon SageMaker Pipelines allows orchestrating the end-to-end ML lifecycle from data preparation and training to model deployment as automated workflows. You can call get on the object ref to block the execution of the current task until the remote computation is complete and the result is available.

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AWS Machine Learning Blog

SEPTEMBER 11, 2023

It’s an auto-regressive language model that uses an optimized transformer architecture. In SageMaker Studio, you can access SageMaker JumpStart, which contains pre-trained models, notebooks, and prebuilt solutions, under Prebuilt and automated solutions. It was trained on 3.5 Input System: You are a helpful trip planner.

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The MLOps Blog

JANUARY 23, 2023

Machine Learning Operations (MLOps): Overview, Definition, and Architecture” By Dominik Kreuzberger, Niklas Kühl, Sebastian Hirschl Great stuff. If you haven’t read it yet, definitely do so. We need both automated continuous monitoring AND periodic manual inspection. Either way, we definitely need that person on the team.

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John Snow Labs

JUNE 27, 2023

In this comprehensive overview, we will explore the definition, significance, and real-world applications of these game-changing models. Automation and Scalability: LLMs enable automation of various NLP tasks, eliminating the need for manual intervention. What are Large Language Models (LLMs)?

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AWS Machine Learning Blog

MAY 7, 2024

With a decade of enterprise AI experience, Veritone supports the public sector, working with US federal government agencies, state and local government, law enforcement agencies, and legal organizations to automate and simplify evidence management, redaction, person-of-interest tracking, and eDiscovery.

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The MLOps Blog

JULY 18, 2023

It’s an automated chief of staff that automates conversational tasks. We are aiming to automate that functionality so that every worker in an organization can have access to that help, just like a CEO or someone else in the company would. Jason: Hi Sabine, how’s it going? Jason, you are the co-founder and CTO of Xembly.

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Snorkel AI

MARCH 21, 2023

They were able to do a much more complete and holistic exploration of the solution space. These were higher-quality hits with more information, a more informative definition of the phenotypes. FMs are much more powerful than the traditional approach. Because of this, they can create far more hits and higher-quality hits.

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Dlabs.ai

JUNE 8, 2020

Let’s start with a definition: what is Industry 4.0 ? refers to the rise of automation technology in manufacturing. What is important: moving averages model described above is not a part of the ARIMA model — it is a completely different model. Key Takeaways Predictive maintenance will play a key role in Industry 4.0 Industry 4.0

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Explosion

JANUARY 31, 2021

The quickstart widget auto-generates a starter config for your specific use case and setup You can use the quickstart widget or the init config command to get started. Automated checks and validation. When you load a config, spaCy checks if the settings are complete and if all values have the correct types. adopts pydantic.

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

It also enables operational capabilities including automated testing, conversation analytics, monitoring and observability, and LLM hallucination prevention and detection. “We When the stack is complete, you can review the resources it creates on the Resources tab for the CloudFormation stack. seconds or less.

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Snorkel AI

MARCH 2, 2023

Others, toward language completion and further downstream tasks. There are definitely compelling economic reasons for us to enter into this realm. In terms of technology: generating code snippets, code translation, and automated documentation. Very large core pie, and very efficient in certain sets of things.

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Snorkel AI

MARCH 2, 2023

Others, toward language completion and further downstream tasks. There are definitely compelling economic reasons for us to enter into this realm. In terms of technology: generating code snippets, code translation, and automated documentation. Very large core pie, and very efficient in certain sets of things.

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Dlabs.ai

JANUARY 16, 2023

That’s why the clinic wants to harness the power of deep learning in a bid to help healthcare professionals in an automated way. Pipeline definition Pre-processing pipeline concept Below you can find the definition of our pipeline expressed using Apache Beam. But it’s not easy to spot the tell-tale signs in scans.

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The MLOps Blog

DECEMBER 29, 2022

People will auto-scale up to 10 GPUs to handle the traffic. Kyle, you definitely touched upon this already. Kyle: Yes, I can speak that you definitely can. So, you definitely can. It’s definitely faster with GPU. They’ll come to me and say, “Hey, I need to make inference faster.”

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Snorkel AI

MARCH 16, 2023

Oftentimes that inspection process is pretty costly, so if you can automate that with a machine learning system, you can reduce that cost. We quickly started to find all the difficulties with doing custom work and developed processes for quickly completing these projects. This particular project took about two months to complete.

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Snorkel AI

MARCH 16, 2023

Oftentimes that inspection process is pretty costly, so if you can automate that with a machine learning system, you can reduce that cost. We quickly started to find all the difficulties with doing custom work and developed processes for quickly completing these projects. This particular project took about two months to complete.

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