AWS Machine Learning Blog

MARCH 4, 2024

Amazon Bedrock is the best place to build and scale generative AI applications with large language models (LLM) and other foundation models (FMs). It enables customers to leverage a variety of high-performing FMs, such as the Claude family of models by Anthropic, to build custom generative AI applications.

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Becoming Human

FEBRUARY 1, 2023

Meet Mr. ChatGPT: A Large Language Model Trained by OpenAI Hello and welcome to the blog! My name is ChatGPT, and I am a large language model trained by OpenAI. For credits, of image goes to openai.com Language models are a type of artificial intelligence (AI) that is trained to generate human-like text.

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Dataconomy

OCTOBER 27, 2023

.” This newly formed team is dedicated to assessing and mitigating the potential dangers of advanced AI models. Heading the Preparedness Challenge team is Aleksander Madry, renowned for his work in machine learning. Madry also serves as the director of MIT’s Center for Deployable Machine Learning.

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Heartbeat

MARCH 13, 2024

Using Comet to monitor pre-trained models Photo by Daniel Korpai on Unsplash Transfer learning involves using a pre-trained model to solve a deep-learning problem. If your problem is not necessarily unique, it is better to create a model that has already been trained on a given task. A fierce learning spirit.

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Data Science Dojo

AUGUST 22, 2023

Unlocking the Power of LLM Use-Cases: AI applications now excel at summarizing articles, weaving narratives, and sparking conversations, all thanks to advanced large language models. Large language models, which are a prominent category of transformer models, have proven to be exceptionally versatile.

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AWS Machine Learning Blog

APRIL 5, 2024

It’s based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily. It requires no machine learning (ML) expertise to use and we’re continually adding new computer vision features to the service. Graphic Violence L2 92.6%

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Dataconomy

AUGUST 8, 2023

Zoom’s new terms of service enable the use of customer data to enhance Zoom AI models. Effective from July 27, the updated terms endorse Zoom’s entitlement to use select facets of customer data to refine its AI or machine-learning models.

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Towards AI

FEBRUARY 15, 2023

Last Updated on February 15, 2023 by Editorial Team What happened this week in AI by Louis This week was rather chaotic in the world of large language models (LLMs) and “Generative AI” as large tech companies scrambled to display their technology in the wake of ChatGPT’s success. Three 5-minute reads/videos to keep you learning 1.

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ODSC - Open Data Science

DECEMBER 4, 2023

ChatGPT’s explosion in popularity has created a surge in AI-generated blogs, articles, emails, resumes, and academic papers. AI content detectors use machine learning models to look for patterns common in AI-generated text. By analyzing each category, these models can learn common differences between them.

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Snorkel AI

OCTOBER 23, 2023

Wayfair relies on machine learning (ML) and product tagging to ensure customer searches result in relevant products. With Snorkel Flow, Wayfair built a data-centric AI development workflow to help improve automated catalog tagging across their products. To ensure that relevant products appear in customer searches (e.g.

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AWS Machine Learning Blog

OCTOBER 18, 2023

Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. The solution focuses on the fundamental principles of developing an AI/ML application workflow of data preparation, model training, model evaluation, and model monitoring.

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Dataconomy

AUGUST 16, 2023

In this blog post, we’re embarking on a thrilling expedition to demystify the enigmatic role of data scientists. Data scientists waltz through intricate datasets, twirling with statistical tools and machine learning techniques. A model builder: Data scientists create models that simulate real-world processes.

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AWS Machine Learning Blog

SEPTEMBER 7, 2023

Finding optimal control policies is a complex task because physical systems, such as chemical reactors and wind turbines, are often hard to model and because drift in process dynamics can cause performance to deteriorate over time. To learn more about reinforcement learning, see Use Reinforcement Learning with Amazon SageMaker.

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AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

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IBM Journey to AI blog

MAY 1, 2023

I love the game of chess and was shocked when IBM’s Deep Blue chess-playing machine defeated the world chess champion in 1997. That ground-shaking event divided the world with excitement and trepidation about a future with thinking machines. It turned out to be a fraud, with a human player behind the machine.

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Defined.ai blog

JANUARY 31, 2023

We’re living in an exciting and transformational time for AI, but what most of us—even those in the machine learning and artificial intelligence industry—couldn’t have anticipated is how exponential AI’s progress has been. We’ll still need prompt and attentive customer service as a result.

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AWS Machine Learning Blog

FEBRUARY 16, 2024

Today, we are excited to announce that Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. In this post, we walk through how to discover and deploy the Code Llama model via SageMaker JumpStart.

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AWS Machine Learning Blog

OCTOBER 10, 2023

Today, we’re excited to announce that the OpenAI Whisper foundation model is available for customers using Amazon SageMaker JumpStart. Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. The OpenAI Whisper model uses the huggingface-pytorch-inference container.

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Snorkel AI

OCTOBER 23, 2023

Wayfair relies on machine learning (ML) and product tagging to ensure customer searches result in relevant products. With Snorkel Flow, Wayfair built a data-centric AI development workflow to help improve automated catalog tagging across their products. To ensure that relevant products appear in customer searches (e.g.

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ODSC - Open Data Science

DECEMBER 7, 2023

We’ll also discuss some of the benefits of using set union(), and we’ll see why it’s a popular tool for Python developers. We’ll also discuss some of the benefits of using set union(), and we’ll see why it’s a popular tool for Python developers.

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IBM Journey to AI blog

MAY 18, 2023

This report outlines the combination of traditional decision automation tools with machine learning models and other technologies. ” You can download a complimentary copy of the full Forrester Wave™ report to learn more about IBM and other vendors’ offerings.

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DataRobot

AUGUST 25, 2021

In a recent blog, we talked about how, at DataRobot , we organize trust in an AI system into three main categories: trust in the performance in your AI/machine learning model , trust in the operations of your AI system, and trust in the ethics of your modelling workflow, both to design the AI system and to integrate it with your business process.

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Google Research AI blog

MARCH 14, 2023

Developing machine learning (ML) tools in pathology to assist with the microscopic review represents a compelling research area with many potential applications. This is in contrast to training models to predict “intermediate” human-annotated labels for known pathologic features and then using those features to predict outcomes.

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Heartbeat

JANUARY 24, 2024

The importance of EDA in the machine learning world is well known to its users. EDA is the first step in every machine learning problem solution. It is most likely the crucial component of a machine learning project. In the end, this is what we need to accomplish to develop a robust model.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. One such component is a feature store, a tool that stores, shares, and manages features for machine learning (ML) models. A feature store maintains user profile data.

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Heartbeat

FEBRUARY 7, 2023

image by rawpixel.com Understanding the concept of language models in natural language processing (NLP) is very important to anyone working in the Deep learning and machine learning space. They are essential to a variety of NLP activities, including speech recognition, machine translation, and text summarization.

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IBM Journey to AI blog

MAY 25, 2023

The Center of Excellence (CoE) already has more than 1,000 consultants with specialized generative AI expertise that are engaging with a global set of clients to drive productivity in IT operations and core business processes like HR or marketing, elevate their customer experiences and create new business models.

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AWS Machine Learning Blog

NOVEMBER 6, 2023

We are excited to announce that Amazon SageMaker JumpStart can now stream large language model (LLM) inference responses. Token streaming allows you to see the model response output as it is being generated instead of waiting for LLMs to finish the response generation before it is made available for you to use or display.

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The MLOps Blog

FEBRUARY 22, 2024

TL;DR: In many machine-learning projects, the model has to frequently be retrained to adapt to changing data or to personalize it. Continual learning is a set of approaches to train machine learning models incrementally, using data samples only once as they arrive. What is continual learning?

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Heartbeat

JANUARY 29, 2024

Photo by Brett Jordan on Unsplash In the ever-evolving landscape of artificial intelligence and machine learning, researchers and practitioners continuously seek to elevate the capabilities of intelligent systems. Among the myriad breakthroughs in this field, Meta-Learning is pushing the boundaries of machine learning.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. Additionally, usage details of shared resources can be monitored with Amazon CloudWatch and AWS CloudTrail.

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Heartbeat

APRIL 17, 2023

Photo by Shahadat Rahman on Unsplash Introduction Machine learning (ML) focuses on developing algorithms and models that can learn from data and make predictions or decisions. In the same way, ML algorithms can be trained on large datasets to learn patterns and make predictions based on that data.

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Pickl AI

APRIL 25, 2023

Technology has enabled machines to learn and work on their own allowing businesses to find new possibilities at work. The following blog hence will contain detailed information on the 5 Important Subsets of AI (Artificial Intelligence). All of these subsets are not exclusive categories but are often useful when in combination.

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Pickl AI

JULY 25, 2023

Proficient in programming languages like Python or R, data manipulation libraries like Pandas, and machine learning frameworks like TensorFlow and Scikit-learn, data scientists uncover patterns and trends through statistical analysis and data visualization. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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AWS Machine Learning Blog

MARCH 22, 2023

With Amazon Rekognition Custom Labels , you can have Amazon Rekognition train a custom model for object detection or image classification specific to your business needs. Developing a Rekognition Custom Labels model to analyze images is a significant undertaking that requires time, expertise, and resources, often taking months to complete.

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Heartbeat

FEBRUARY 13, 2023

In-depth Analysis of Kangas Library using Python Photo by James Wainscoat on Unsplash Working with large datasets has always been a challenge for data developers, and it remains so in the current data industry. One of the main issues developers face is how to efficiently handle and process massive volumes of multimedia data, such as images.

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Dataconomy

MARCH 14, 2023

In recent years, natural language processing and conversational AI have gained significant attention as technologies that are transforming the way we interact with machines and each other. These fields involve the use of machine learning and artificial intelligence to enable machines to understand, interpret, and generate human language.

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