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. The same approach can be used with different models and vector databases.

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AWS Machine Learning Blog

JULY 1, 2024

It features natural language understanding capabilities to recognize more accurate identification of user intent and fulfills the user intent faster. Amazon Bedrock simplifies the process of developing and scaling generative AI applications powered by large language models (LLMs) and other foundation models (FMs).

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AWS Machine Learning Blog

SEPTEMBER 25, 2023

Transformers are slow and memory-hungry on generating long text sequences due to the sheer size of the models. Large language models (LLMs) used to generate text sequences need immense amounts of computing power and have difficulty accessing the available high bandwidth memory (HBM) and compute capacity.

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Google Research AI blog

MARCH 10, 2023

Today we introduce PaLM-E , a new generalist robotics model that overcomes these issues by transferring knowledge from varied visual and language domains to a robotics system. We began with PaLM , a powerful large language model, and “embodied” it (the “ E ” in PaLM-E), by complementing it with sensor data from the robotic agent.

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AWS Machine Learning Blog

OCTOBER 11, 2023

What is the optimal framework and configuration for hosting large language models (LLMs) for text-generating generative AI applications? 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 default is 32.

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Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics.

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Marktechpost

NOVEMBER 26, 2024

Text-Encoder Design: Authors utilize Gemma -2, a small decoder-based large language model. Its small architecture has better instruction following and reasoning abilities with Chain of Thought, and Context Learning provides better performance than huge encoder-based models like T5.

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AWS Machine Learning Blog

JULY 24, 2024

Einstein has a list of over 60 features, unlocked at different price points and segmented into four main categories: machine learning (ML), natural language processing (NLP), computer vision, and automatic speech recognition. These models are designed to provide advanced NLP capabilities for various business applications.

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AWS Machine Learning Blog

JANUARY 29, 2025

Their DeepSeek-R1 models represent a family of large language models (LLMs) designed to handle a wide range of tasks, from code generation to general reasoning, while maintaining competitive performance and efficiency. An S3 bucket prepared to store the custom model. Choose Import model.

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AWS Machine Learning Blog

MARCH 28, 2024

When you create an AWS account, you get a single sign-on (SSO) identity that has complete access to all the AWS services and resources in the account. Signing in to the AWS Management Console using the email address and password that you used to create the account gives you complete access to all the AWS resources in your account.

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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

MAY 31, 2024

It’s a next generation model in the Falcon family—a more efficient and accessible large language model (LLM) that is trained on a 5.5 It’s built on causal decoder-only architecture, making it powerful for auto-regressive tasks. Deploy the model in SageMaker JumpStart Deployment starts when you choose Deploy.

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AWS Machine Learning Blog

MAY 4, 2023

Today, we are excited to announce that Amazon SageMaker supports AWS Inferentia2 (ml.inf2) and AWS Trainium (ml.trn1) based SageMaker instances to host generative AI models for real-time and asynchronous inference. ml.inf2 instances are available for model deployment on SageMaker in US East (Ohio) and ml.trn1 instances in US East (N.

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AWS Machine Learning Blog

JUNE 13, 2023

SupportGPT leverages state-of-the-art Information Retrieval (IR) systems and large language models (LLMs) to power over 30 million customer interactions annually. Forethought uses per-customer fine-tuned models to detect customer intents in order to solve customer interactions. 2xlarge instances.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The Test inference tab enables you to test your model by sending test requests to one of the in-service models directly from the SageMaker Studio interface. You can also edit the auto scaling policy on the Auto-scaling tab on this page. Some familiarity with SageMaker Studio is also assumed.

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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. Its model parameters scale from an impressive 7 billion to a remarkable 70 billion. Its model parameters scale from an impressive 7 billion to a remarkable 70 billion.

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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). Legacy hosting solutions used for smaller models typically don’t offer this type of functionality, adding to the difficulty. code_falcon40b_deepspeed/model.py add_as_json(result) That’s it!

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AWS Machine Learning Blog

JANUARY 8, 2024

However, they’re unable to gain insights such as using the information locked in the documents for large language models (LLMs) or search until they extract the text, forms, tables, and other structured data. When the script ends, a completion status along with the time taken will be returned to the SageMaker studio console.

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AWS Machine Learning Blog

SEPTEMBER 11, 2023

What is Falcon 180B Falcon 180B is a model released by TII that follows previous releases in the Falcon family. It’s an auto-regressive language model that uses an optimized transformer architecture. Inference and example prompts for Falcon 180B Falcon models can be used for text completion for any piece of text.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

We see the model error rate has increased, from an RMSE of 282K to an RMSE of 352K. From this, we can conclude that three simple questions from the images improved model accuracy by about 20%. In social media platforms, photos could be auto-tagged for subsequent use.

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The MLOps Blog

JUNE 27, 2023

Is it accessible from your language/framework/infrastructure, framework, or infrastructure? Model versioning, lineage, and packaging : Can you version and reproduce models and experiments? Can you see the complete model lineage with data/models/experiments used downstream? Can you render audio/video?

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AWS Machine Learning Blog

DECEMBER 14, 2023

Complete the following steps to edit an existing space: On the space details page, choose Stop space. Reconfigure the compute, storage, or runtime. To start using Amazon CodeWhisperer, make sure that the Resume Auto-Suggestions feature is activated. Choose Create JupyterLab space. For Name , enter a name for your Space.

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AWS Machine Learning Blog

OCTOBER 8, 2024

The diagram shows the workflow for building and deploying models using the AutoMLV2 API. 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. Data preparation The foundation of any machine learning project is data preparation.

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AWS Machine Learning Blog

JULY 18, 2023

Today, we are excited to announce that Llama 2 foundation models developed by Meta are available for customers through Amazon SageMaker JumpStart. The Llama 2 family of large language models (LLMs) is a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

If you’re not actively using the endpoint for an extended period, you should set up an auto scaling policy to reduce your costs. Manage Amazon SageMaker endpoints – Similarly, for organizations that aim for inference type selection and endpoints running time management, you can deploy open source models on Amazon SageMaker.

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AWS Machine Learning Blog

MAY 30, 2023

Furthermore, the CPUUtilization metric shows a classic pattern of periodic high and low CPU demand, which makes this endpoint a good candidate for auto scaling. You can start with a smaller instance and scale out first as your compute demand changes. For information, see Automatically Scale Amazon SageMaker Models.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

Today, we are excited to announce the capability to fine-tune Llama 2 models by Meta using Amazon SageMaker JumpStart. The Llama 2 family of large language models (LLMs) is a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters.

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AWS Machine Learning Blog

APRIL 17, 2023

Quantization and compression can reduce model size and serving cost by reducing the precision of weights or reducing the number of parameters via pruning or distillation. Compilation can optimize the computation graph and fuse operators to reduce memory and compute requirements of a model.

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Viso.ai

MAY 29, 2024

Some original Tesla features are embedded into the robot, such as a self-running computer, autopilot cameras, a set of AI tools, neural network planning , auto-labeling for objects, etc. The data from multiple sensors are combined and processed to create a complete understanding of the environment.

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AWS Machine Learning Blog

APRIL 16, 2024

Then we show how you can enhance the in-notebook SQL experience using Text-to-SQL capabilities provided by advanced large language models (LLMs) to write complex SQL queries using natural language text as input. Complete the following steps: On the Secrets Manager console, choose Store a new secret.

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TensorFlow

MAY 10, 2023

The rise of Large Language Models (LLMs) is sparking the imagination of developers worldwide, with new generative AI applications reaching hundreds of millions of people around the world. These models are trained on massive datasets, and used to solve a variety of tasks, from natural language processing to image generation.

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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. You have a valuable dataset and can choose from various base models. These models are usually based on an architecture called transformers.

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Flipboard

DECEMBER 2, 2024

With this feature, you can closely match your compute resource usage to your actual needs, potentially reducing costs during times of low demand. This enhancement builds upon the existing auto scaling capabilities in SageMaker, offering more granular control over resource allocation.

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AWS Machine Learning Blog

JUNE 29, 2023

Fine-tuning large language models (LLMs) allows you to adjust open-source foundational models to achieve improved performance on your domain-specific tasks. In this post, we discuss the advantages of using Amazon SageMaker notebooks to fine-tune state-of-the-art open-source models.

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AWS Machine Learning Blog

AUGUST 2, 2023

The fine-tuning process starts with preparing the images, including face cropping, background variation, and resizing for the model. Then we use Low-Rank Adaptation (LoRA), a parameter-efficient fine-tuning technique for large language models (LLMs), to fine-tune the model. The first is to define our model server.

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AWS Machine Learning Blog

JULY 23, 2024

collection of multilingual large language models (LLMs), which includes pre-trained and instruction tuned generative AI models in 8B, 70B, and 405B sizes, is available through Amazon SageMaker JumpStart to deploy for inference. is an auto-regressive language model that uses an optimized transformer architecture.

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Flipboard

APRIL 13, 2023

Prime Air (our drones) and the computer vision technology in Amazon Go (our physical retail experience that lets consumers select items off a shelf and leave the store without having to formally check out) use deep learning. To give a sense for the change in scale, the largest pre-trained model in 2019 was 330M parameters.

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