AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. However, bringing such solutions and models to the business-as-usual operations is not an easy task. Our approach applies to both open-source and proprietary models equally.

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Ocean Protocol

MARCH 10, 2023

Dapp Developers served by team Eagle-Rays (Stream 1) 4. Data Scientists served by team Thresher (Stream 2) 5. Data Scientists served by team Thresher (Stream 2) 5. Crypto-Enthusiasts served by team Sailfish (Stream 3) 6. Contents 1. Abstract 2. Introduction 3. Conclusion 1. Introduction 2.1.

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Chatbots Life

MAY 16, 2023

Top 5 Generative AI Integration Companies to Drive Customer Support in 2023 If you’ve been following the buzz around ChatGPT, OpenAI, and generative AI, it’s likely that you’re interested in finding the best Generative AI integration provider for your business. This can lead to frustrating user experiences and low customer satisfaction rates.

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The MLOps Blog

NOVEMBER 30, 2022

Data science practitioners experiment with algorithms, data, and hyperparameters to develop a model that generates business insights. However, the increasing scale of experiments and projects, especially in mid to large-size enterprises, requires effective model management. ML model versioning: where are we at?

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The MLOps Blog

JANUARY 18, 2023

Model monitoring is an essential part of the CI/CD pipeline. One of the major issues with any model is that it may perform well in the development phase, but when deployed, it may perform poorly or may even fail. This is especially true with the time series model, as the changes in the dataset can be quite rapid.

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Pickl AI

JULY 25, 2023

Algorithmic bias refers to the presence of unfair or discriminatory outcomes produced by algorithms or machine learning models due to biased data or design choices. Prejudiced Training: Sometimes, algorithms are intentionally designed with biased objectives or trained with prejudiced data to serve specific interests or agendas.

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The MLOps Blog

DECEMBER 19, 2022

As Data Scientists, we all have worked on an ML classification model. Will the same model architecture work when the number of classes exceeds 10000? Traditional Machine Learning and Deep Learning methods are used to solve Multiclass Classification problems, but the model’s complexity increases as the number of classes increases.

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AWS Machine Learning Blog

DECEMBER 13, 2023

In this post, we showcase fine-tuning a Llama 2 model using a Parameter-Efficient Fine-Tuning (PEFT) method and deploy the fine-tuned model on AWS Inferentia2. We then use a large model inference container powered by Deep Java Library (DJLServing) as our model serving solution.

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The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.

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AWS Machine Learning Blog

MARCH 13, 2024

Today, we’re excited to announce that the Gemma model is now available for customers using Amazon SageMaker JumpStart. Gemma is a family of language models based on Google’s Gemini models, trained on up to 6 trillion tokens of text. Gemma released the model weights to support developer innovation using Gemma models.

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AWS Machine Learning Blog

APRIL 22, 2024

This post serves as a starting point for any executive seeking to navigate the intersection of generative artificial intelligence (generative AI) and sustainability. This post serves as a starting point for any executive seeking to navigate the intersection of generative artificial intelligence (generative AI) and sustainability.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Third, a number of sessions will be of interest to ML practitioners who build, deploy, and operationalize both traditional and generative AI models. The greater the power of latest transformer-based models, the greater the responsibility of all ML practitioners to do this right. This year, learn about LLMOps, not just MLOps!

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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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Iguazio

DECEMBER 5, 2023

Successfully training AI and ML models relies not only on large quantities of data, but also on the quality of their annotations. Data annotation accuracy directly impacts the accuracy of a model and the reliability of its predictions. This will ensure the successful implementation of your model. Get the dataset here.

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The MLOps Blog

MARCH 23, 2023

NLP models in commercial applications such as text generation systems have experienced great interest among the user. These models have achieved various groundbreaking results in many NLP tasks like question-answering, summarization, language translation, classification, paraphrasing, et cetera. Sure there is.

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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. This conversational model allows for building customized chatbots and assistants.

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PyImageSearch

SEPTEMBER 25, 2023

Overview The YouTube recommendation algorithm is extremely challenging because of three main reasons: Scale: The platform serves billions of users with billions of videos. YouTube is the world’s largest platform to create, consume, and share video content. Figure 2: Overview of YouTube recommendation algorithm (source: Covington et al.,

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PyImageSearch

OCTOBER 2, 2023

However, in the realm of unsupervised learning, generative models like Generative Adversarial Networks (GANs) have gained prominence for their ability to produce synthetic yet realistic images. Before the rise of GANs, there were other foundational neural network architectures for generative modeling. Let’s get started!

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Heartbeat

MAY 29, 2023

These models have the potential to revolutionize industries ranging from customer service to scientific research, but their capabilities and limitations are still not fully understood. We will explore how to better understand the data that these models are trained on, and how to evaluate and optimize them for real-world use.

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AWS Machine Learning Blog

JANUARY 17, 2024

Apart from GPS pings and app publishers, other sources are used to augment the dataset, such as Wi-Fi access points, bid stream data obtained via serving ads on mobile devices, and specific hardware transmitters placed by businesses (for example, in physical stores). There are two types of geospatial data: vector data and raster data.

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PyImageSearch

JULY 3, 2023

The Internet has revolutionized how we consume television through Over-the-Top (OTT) content streaming platforms like Netflix, Amazon Prime, Disney, HBO, etc. Netflix recommendations are not just one algorithm but a collection of various state-of-the-art algorithms that serve different purposes to create the complete Netflix experience.

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Mlearning.ai

SEPTEMBER 4, 2023

“Take” “Take” refers to the traditional software-as-a-service (SaaS) model where you use the software “as is” off-the-shelf. They include: Public access: Access to closed tools like OpenAI’s ChatGPT may be viable for some organizations. Turbo model, this may be a better fit for some businesses.[2],[3] CA, NY, and MA).[1]

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Hacker News

JANUARY 9, 2024

Version 14.0 of Wolfram Language and Mathematica is available immediately both on the desktop and in the cloud. See also more detailed information on Version 13.1 , Version 13.2 and Version 13.3. of Wolfram Language and Mathematica. of Wolfram Language and Mathematica. Over the two years since we released Version 13.0 1 releases every six months.

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phData

DECEMBER 4, 2023

Get the Guide Defining a Chargeback Model Unlike traditionally licensed on-premises data solutions, Snowflake operates with a flexible pay-as-you-go model, allowing you to create an account and start using it without delay. Congratulations! Want to save this guide for later? Download a free PDF by filling out the form.

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PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? Why Do We Use Intersection over Union (IoU)? Object detection is no different. Haar cascades ( Viola and Jones, 2001 ); HOG + Linear SVM ( Dalal and Triggs, 2005 )) at every step of the way.

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PyImageSearch

JULY 17, 2023

We will then explore different testing situations (e.g., visualizing the latent space, uniform sampling of data points from this latent space, and recreating images using these sampled points). We’re about to dive deep into this tutorial. But first things first — you’ll need to access our dataset. Let’s rewind a bit.

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PyImageSearch

OCTOBER 30, 2023

Matrix Factorization Alternating Least Squares RNNs for Music Discovery Playlist Recommendation Using Reinforcement Learning Overview World Model Design Action Head DQN Approach Summary Citation Information Spotify Music Recommendation Systems In this tutorial, you will learn about Spotify’s music recommendation systems.

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phData

APRIL 10, 2023

In almost every modern organization, data and its respective analytics tools serve to be that big blue crayon. To define the concept of governed self-service analytics, it’s best to take a step back and think about the different analytics operating models. What is Governed Self-Service Analytics? How do they do that, exactly?

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IBM Journey to AI blog

JANUARY 17, 2024

Chatbots have become a sort of Swiss-Army-knife for many organizations, one tool that fulfills many business needs. In 1988, British-born programmer Rollo Carpenter created a “chatterbot” named Jabberwocky, among the first “conversational AI” to learn new responses instead of simply serving pre-written language.

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The MLOps Blog

DECEMBER 7, 2022

Given that the whole theory of machine learning assumes today will behave at least somewhat like yesterday, what can algorithms and models do for you in such a chaotic context ? And that includes data. Those were the questions that the guys at CTF Capital —a trading fund— had. With that out of the way, let’s dig in!

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AWS Machine Learning Blog

MAY 30, 2023

We provide tools for flexible cost management and improved visibility of detailed cost and usage of your workloads. Cost optimization is one of the pillars of the AWS Well-Architected Framework , and it’s a continual process of refinement and improvement over the span of a workload’s lifecycle.

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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Chatbots Life

MAY 3, 2023

We all remember conversing with a Chatbot at some point in our lives. And we also remember having to then connect with a Human because the chatbot couldn’t understand our query. It was simply too complex for the Bot to decipher. The customer support executive, however, could easily understand our intent and satisfy us with an appropriate solution.

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The MLOps Blog

DECEMBER 29, 2022

Every episode is focused on one specific ML topic, and during this one, we talked to Kyle Morris from Banana about deploying models on GPU. Who is an expert in today’s topic, which is deploying models on GPU. How would you explain deploying models on GPU in one minute? Sabine: Hello, everyone, and welcome to MLOps Live.

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AWS Machine Learning Blog

MAY 26, 2023

Text-to-image generation is a task in which a machine learning (ML) model generates an image from a textual description. This task is challenging because it requires the model to understand the semantics and syntax of the text and to generate photorealistic images.

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phData

NOVEMBER 13, 2023

Coalesce is where the brightest minds in data — from data practitioners to the largest companies — converge to share, inspire, and reshape the landscape with dbt, the gold standard tool for data transformation. In mid-2023, many companies were wrangling with more than 5,000 dbt models. But you can be a small company to use dbt mesh.

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PyImageSearch

DECEMBER 25, 2023

Now, Google brings the power of this technology directly to you, letting you experiment and understand the magic behind tools like Bard. Imagine tinkering with AI models, witnessing their fascinating responses as you adjust parameters. Generative AI is the term coined for ML models that can create new content (e.g.,

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