AWS Machine Learning Blog

NOVEMBER 22, 2023

For decades, Amazon has pioneered and innovated machine learning (ML), bringing delightful experiences to its customers. From the earliest days, Amazon has used ML for various use cases such as book recommendations, search, and fraud detection. In order to achieve this, the M5 team regularly evaluates new techniques to reduce cost.

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NVIDIA

APRIL 3, 2024

The transcription then goes into an LLM — such as Google’s Gemma, Meta’s Llama 2 or Mistral — and taps Riva’s neural machine translation to generate a natural language text response. Inworld technology also provided the NEO NPCs with intrinsic knowledge of their surroundings, as well as interactive responses powered by Inworld’s LLM.

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ODSC - Open Data Science

OCTOBER 11, 2023

In this post, I’ll give a high-level overview of how AI/ML can be used to automatically detect various issues common in real-world datasets. using any machine learning model you’ve already trained (sklearn, huggingface, pytorch, LLMs, …). Steps to practice data-centric AI Train the initial ML model on the original dataset.

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IBM Journey to AI blog

JULY 17, 2023

Generative AI auto-summarization creates summaries that employees can easily refer to and use in their conversations to provide product, service or recommendations (and it can also categorize and track trends). is a studio to train, validate, tune and deploy machine learning (ML) and foundation models for Generative AI. Watsonx.ai

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Mlearning.ai

AUGUST 19, 2023

Introduction Fine tune LLama2 model in Azure ML Using Azure ML Using NVdia A100 GPU SKU NCADSA100v4 I had to request quota increase using Azure ML to achieve this experiment using open source data set Following this experiment from here Code First install necesary packages !pip pip install -U pip !pip

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Mlearning.ai

JULY 9, 2023

One of the biggest challenges of using LLMs is the cost of accessing them. Many LLMs, such as OpenAI’s GPT-3, are only available through paid APIs. Learn how to deploy any open-source LLM as a free API endpoint using HuggingFace and Gradio. Many LLMs, such as OpenAI’s GPT-3, are only available through paid APIs.

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AWS Machine Learning Blog

AUGUST 14, 2023

An application using the RAG approach retrieves information most relevant to the user’s request from the enterprise knowledge base or content, bundles it as context along with the user’s request as a prompt, and then sends it to the LLM to get a response. In recent years, ML techniques have become increasingly popular to enhance search.

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Unite.AI

NOVEMBER 2, 2023

Prior to your current role you lead development of Banjos AI/ML products, what were these products and what were some of your key takeaways from this experience? Using AI-powered insights, businesses arm themselves with a complete picture of the lead journey, from initial contact to final outcomes, across both digital and offline channels.

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Snorkel AI

JUNE 7, 2023

Foundation models, Alex said, yield results that are “nothing short of breathtaking,” but they’re not a complete answer for enterprises who aim to solve challenges using machine learning. “We s Daniel Wu , and Snorkel AI’s Aarti Bagul explored the ethical challenges of leveraging generative AI in the midst of an ML arms race.

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Snorkel AI

JUNE 7, 2023

Foundation models, Alex said, yield results that are “nothing short of breathtaking,” but they’re not a complete answer for enterprises who aim to solve challenges using machine learning. “We s Daniel Wu , and Snorkel AI’s Aarti Bagul explored the ethical challenges of leveraging generative AI in the midst of an ML arms race.

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Mlearning.ai

DECEMBER 22, 2023

Write a response that appropriately completes the request.nn" question = sample["prompt"].replace("nn### strip() answer = sample["completion"].replace("n### Write a response that appropriately completes the request.nn" question = sample["prompt"].replace("nn### 1 on the Billboard 200??

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The MLOps Blog

JANUARY 19, 2024

Imagine you’re facing the following challenge: you want to develop a Large Language Model (LLM) that can proficiently respond to inquiries in Portuguese. We will fine-tune different foundation LLM models on a dataset, evaluate them, and select the best model. You have a valuable dataset and can choose from various base models.

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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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Marktechpost

OCTOBER 18, 2023

Large language models (LLMs) such as ChatGPT and Llama have garnered substantial attention due to their exceptional natural language processing capabilities, enabling various applications ranging from text generation to code completion. Check out the Reference Page and Project Page. We are also on WhatsApp.

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Mlearning.ai

OCTOBER 2, 2023

Learn how to use them to avoid the biggest scare in ML: overfitting and underfitting. It completely depends on your data and the goal of the project itself. If there are too many missing pieces, then it might be hard to complete the puzzle and understand the whole picture. We’ll answer exactly that question in this article.

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Marktechpost

NOVEMBER 7, 2023

It will be necessary to expand the capabilities of current code completion tools—which are presently utilized by millions of programmers—to address the issue of library learning to solve this multi-objective optimization. Figure 1: The LILO learning loop overview. (Al)

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AWS Machine Learning Blog

MAY 2, 2024

This post showcases a reward modeling technique to efficiently customize LLMs for an organization by programmatically defining rewards functions that capture preferences for model behavior. We demonstrate an approach to deliver LLM results tailored to an organization without intensive, continual human judgement.

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AWS Machine Learning Blog

MAY 7, 2024

The Hugging Face containers host a large language model (LLM) from the Hugging Face Hub. Hugging Face is an open-source machine learning (ML) platform that provides tools and resources for the development of AI projects. You can use other languages such as Spanish, French, or Portuguese, but the quality of the completions may degrade.

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AWS Machine Learning Blog

MARCH 28, 2024

It provides a collection of pre-trained models that you can deploy quickly and with ease, accelerating the development and deployment of machine learning (ML) applications. This technique provides targeted yet broad-ranging search capabilities, furnishing the LLM with a wider perspective. Create a question embedding.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at scale. For more information, refer to Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements.

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Flipboard

NOVEMBER 20, 2023

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. There are two models in this implementation: the embeddings model and the LLM that generates the final response.

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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. In this post, we explore best practices for prompting the Llama 2 Chat LLM. The complete example is shown in the accompanying notebook.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

What is SageMaker JumpStart Our model comes from SageMaker JumpStart, a feature of SageMaker that accelerates the machine learning (ML) journey by offering pre-trained models, solution templates, and example notebooks. SageMaker Python SDK After deployment is complete, it will return an AsyncPredictor object.

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AWS Machine Learning Blog

DECEMBER 13, 2023

Deploy a fine-tuned Model on Inf2 using Amazon SageMaker AWS Inferentia2 is purpose-built machine learning (ML) accelerator designed for inference workloads and delivers high-performance at up to 40% lower cost for generative AI and LLM workloads over other inference optimized instances on AWS.

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AWS Machine Learning Blog

OCTOBER 11, 2023

The LMI container has a powerful serving stack called DJL serving that is agnostic to the underlying LLM. It provides system-level configuration parameters that can be tuned for extracting the best performance of the hosting infrastructure for a given LLM. These cached key and value tensors are often referred to as the KV cache.

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AWS Machine Learning Blog

MAY 1, 2024

Llama2 by Meta is an example of an LLM offered by AWS. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture and is intended for commercial and research use in English. This results in faster restarts and workload completion.

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AWS Machine Learning Blog

SEPTEMBER 11, 2023

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. It’s an auto-regressive language model that uses an optimized transformer architecture. It was trained on 3.5

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AWS Machine Learning Blog

DECEMBER 5, 2023

The insurance provider receives payout claims from the beneficiary’s attorney for different insurance types, such as home, auto, and life insurance. When this is complete, the document can be routed to the appropriate department or downstream process. The following diagram outlines the proposed solution architecture. append(e["Text"].upper())

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AWS Machine Learning Blog

MAY 31, 2023

Running machine learning (ML) workloads with containers is becoming a common practice. What you get is an ML development environment that is consistent and portable. In this post, we show you how to run your ML training jobs in a container using Amazon ECS to deploy, manage, and scale your ML workload.

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AWS Machine Learning Blog

JUNE 13, 2023

Last week, Technology Innovation Institute (TII) launched TII Falcon LLM , an open-source foundational large language model (LLM). The result of this effort is TII Falcon LLM. SageMaker large model inference DLCs simplify LLM hosting Hosting LLMs such as Falcon-40B and Falcon-7B can be challenging.

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AWS Machine Learning Blog

APRIL 16, 2024

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them.

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Marktechpost

JULY 17, 2023

To that end, they introduce Auto-GPT (An Autonomous GPT-4 Experiment), a free program demonstrating how LLMs like GPT-4 may be used to develop and handle various activities independently, like writing code or developing business ideas. Very resource intensive. ” Check out the Github.

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AWS Machine Learning Blog

SEPTEMBER 25, 2023

We’re at an exciting inflection point in the widespread adoption of machine learning (ML), and we believe most customer experiences and applications will be reinvented with generative AI. Batching refers to the process of sending multiple input sequences together to a LLM and thereby optimizing the performance of the LLM inference.

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AWS Machine Learning Blog

DECEMBER 14, 2023

Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code Open Source), and RStudio. It’s attached to a ML compute instance whenever a Space is run. Choose Create JupyterLab space.

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The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

In addition to QLoRA, bitsanbytes is used to convert to 4-bit precision to quantize frozen LLM to 4-bit and attach LoRA adapters on it. Cleaning up Complete the following steps to clean up your resources: Shut down the Amazon SageMaker Studio instances to avoid incurring additional costs. Wait for tuning job to finish.

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AWS Machine Learning Blog

MAY 12, 2023

Amazon SageMaker comes with two options to spin up fully managed notebooks for exploring data and building machine learning (ML) models. In addition to creating notebooks, you can perform all the ML development steps to build, train, debug, track, deploy, and monitor your models in a single pane of glass in Studio.

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