Google Research AI blog

NOVEMBER 28, 2022

Posted by Cat Armato, Program Manager, Google This week marks the beginning of the 36th annual Conference on Neural Information Processing Systems ( NeurIPS 2022 ), the biggest machine learning conference of the year.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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AWS Machine Learning Blog

APRIL 19, 2023

Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. After reading a few blog posts and DJL’s official documentation, we were sure DJL would provide the best solution to our problem. Business requirements We are the US squad of the Sportradar AI department.

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AWS Machine Learning Blog

AUGUST 15, 2023

In 2022, 125 million customers contributed nearly 1.5 At the scale of product reviews submitted every month, it is essential to verify that these reviews align with Amazon Community Guidelines regarding acceptable language, words, videos, and images. Amazon has one of the largest stores with hundreds of millions of items available.

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DrivenData Labs

DECEMBER 7, 2023

His main research interests revolve around applications of Network Analysis and Natural Language Processing methods. Amongst other ML competitions, I have been in a prize-winning position for NASA SOHO comet search, NOAA Precipitation Prediction (Rodeo 2), the Spacenet-8 flood detection, and 2019 IEEE GRSS data fusion contest.

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Heartbeat

JANUARY 9, 2024

Large language models have emerged as ground-breaking technologies with revolutionary potential in the fast-developing fields of artificial intelligence (AI) and natural language processing (NLP). LLMs received a lot of media attention when ChatGPT was released in December 2022. BERT and GPT are examples.

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AWS Machine Learning Blog

SEPTEMBER 21, 2023

They wanted to take advantage of machine learning (ML) techniques such as computer vision (CV) and natural language processing (NLP) to automate document processing pipelines. The process relies on manual annotations to train ML models, which are very costly.

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IBM Journey to AI blog

OCTOBER 9, 2023

How HR departments are using AI AI use in HR refers to the deployment of machine learning (ML), natural language processing (NLP) and other AI technologies to automate human resources tasks and support decision-making. The post Artificial intelligence and a new era of human resources appeared first on IBM Blog.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Overall, $384 billion is projected as the cost of pharmacovigilance activities to the overall healthcare industry by 2022. In this post, we show how to develop an ML-driven solution using Amazon SageMaker for detecting adverse events using the publicly available Adverse Drug Reaction Dataset on Hugging Face.

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IBM Journey to AI blog

MARCH 27, 2024

A 2022 CDP study found that for companies that report to CDP, emissions occurring in their supply chain represent an average of 11.4x In recent years, remarkable strides have been achieved in crafting extensive foundation language models for natural language processing (NLP).

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AWS Machine Learning Blog

OCTOBER 4, 2023

The ability to automate this process using machine learning (ML) techniques allows healthcare professionals to more quickly diagnose certain cancers, coronary diseases, and ophthalmologic conditions. This user-friendly approach eliminates the steep learning curve associated with ML, which frees up clinicians to focus on their patients.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Today, 35% of companies report using AI in their business, which includes ML, and an additional 42% reported they are exploring AI, according to the IBM Global AI Adoption Index 2022. What is MLOps?

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AWS Machine Learning Blog

JANUARY 13, 2023

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. It involves training a shared ML model without moving or sharing data across sites or with a centralized server during the model training process, and can be implemented across multiple AWS accounts. Iterative process of model training.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Quantitative modeling and forecasting – Generative models can synthesize large volumes of financial data to train machine learning (ML) models for applications like stock price forecasting, portfolio optimization, risk modeling, and more. The agent answers the question “ What is Amazon’s net loss for fiscal year ending in December 2022?

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AWS Machine Learning Blog

MARCH 1, 2023

Amazon Comprehend is a managed AI service that uses natural language processing (NLP) with ready-made intelligence to extract insights about the content of documents. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

We also note that our models primarily work well for search, recommendation, and natural language processing tasks that typically feature large, high-dimensional output spaces and a requirement of extremely low inference latency. Instance vCPU RAM (GB) Processor On-Demand Price (us-east-1) c7g.8xlarge

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IBM Journey to AI blog

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

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AWS Machine Learning Blog

DECEMBER 14, 2023

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart , a machine learning (ML) hub offering models, algorithms, and solutions. This technique is particularly useful for knowledge-intensive natural language processing (NLP) tasks.

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Mlearning.ai

MAY 3, 2023

The built APP provides an easy web interface to access the large language models with several built-in application utilities for direct use, significantly lowering the barrier for the practitioners to use the LLM’s Natural Language Processing (NLP) capabilities in an amateur way focusing on their specific use cases.

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Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. Published online on April 17, 2022.

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Heartbeat

JANUARY 29, 2024

Imagine an AI system that becomes proficient in many tasks through extensive training on each specific problem and a higher-order learning process that distills valuable insights from previous learning endeavors. Natural Language Processing: With Meta-Learning, language models can be generalized across various languages and dialects.

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AWS Machine Learning Blog

JUNE 7, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. billion in Q3 2021 and Q3 2022, and $6 million and $(11.3) billion for the nine months ended September 30, 2021 and 2022. (2) billion as of December 31, 2021 and September 30, 2022, respectively.

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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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Mlearning.ai

FEBRUARY 9, 2023

This blog will guide you to understand the Hugging Face ecosystem. If you’re in the field of Natural Language Processing, you’ve probably heard about Hugging Face. Models In this Hub, you can discover and use dozens of thousands of open-source ML models shared by the community. link] What is Hugging Face?

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IBM Journey to AI blog

JULY 27, 2023

Since introducing IBM’s new skilling capabilities in October 2022 , we’ve seen more than 70,000 enrollments in one or more IBM badges across our partner organizations, resulting in more than 40,000 completed badges. Education is a cornerstone of our approach with partners.

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AWS Machine Learning Blog

MARCH 14, 2024

Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents. Did anyone make an ace at the 2022 Shriners Children’s Open? Grace Lang is an Associate Data & ML engineer with AWS Professional Services.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

As a first step, they wanted to transcribe voice calls and analyze those interactions to determine primary call drivers, including issues, topics, sentiment, average handle time (AHT) breakdowns, and develop additional natural language processing (NLP)-based analytics.

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DrivenData Labs

DECEMBER 10, 2023

degree in AI and ML specialization from Gujarat University, earned in 2019. He has diligently refined his abilities in the development, deployment, and scaling of AI and ML models, offering substantial contributions to GenAI projects. His educational background includes a Master's in AI and ML from John Moorse University, UK.

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Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Devlin et al.

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Heartbeat

NOVEMBER 21, 2023

From object detection and recognition to natural language processing, deep reinforcement learning, and generative models, we will explore how deep learning algorithms have conquered one computer vision challenge after another. But why is deep learning such a game-changer in this domain?

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AWS Machine Learning Blog

FEBRUARY 24, 2023

Amazon SageMaker multi-model endpoints (MMEs) provide a scalable and cost-effective way to deploy a large number of machine learning (ML) models. It gives you the ability to deploy multiple ML models in a single serving container behind a single endpoint. helping customers design and build AI/ML solutions.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

What is AWS year-over-year revenue in 2022? AWS revenue grew 29% year-over-year in 2022 on a $62 billion revenue base. Amazon has asked corporate employees to come back to office at least three days a week beginning May 2022. By what percentage did AWS revenue grow year-over-year in 2022?

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AWS Machine Learning Blog

NOVEMBER 22, 2023

An intelligent document processing (IDP) project typically combines optical character recognition (OCR) and natural language processing (NLP) to automatically read and understand documents. To reduce your carbon footprint, select a Region where, in 2022, the electricity consumed was attributable to 100% renewable energy.

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AWS Machine Learning Blog

FEBRUARY 28, 2023

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. For example, in the healthcare industry, ML-driven analytics can be used for diagnostic assistance and personalized medicine, while in health insurance, it can be used for predictive care management.

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AWS Machine Learning Blog

DECEMBER 6, 2023

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010. Filter down to keep the revenues of 2022 for each of them.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

These models have revolutionized various computer vision (CV) and natural language processing (NLP) tasks, including image generation, translation, and question answering. It provides access to a wide range of pre-trained models for different problem types, allowing you to start your ML tasks with a solid foundation.

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The MLOps Blog

MARCH 23, 2023

The size of large NLP models is increasing | Source Such large natural language processing models require significant computational power and memory, which is often the leading cause of high infrastructure costs. 2022 where they show how to train a model on a fixed-compute budget. 2020 or Hoffman et al.,

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