Heartbeat

AUGUST 4, 2023

“Our intelligence is what makes us human, and AI is an extension of that quality.” — Yann LeCun A new milestone is recorded almost every week as we experience the renaissance of artificial intelligence (AI) research and development. What is the corresponding model architecture? What data can power this task and model?

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Google Research AI blog

FEBRUARY 14, 2023

Before robotics can be broadly useful in helping with practical day-to-day tasks in people-centered spaces — spaces designed for people, not machines — they need to be able to safely & competently provide assistance to people. In this blog post, we’ll review key learnings and themes from our explorations in 2022.

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Defined.ai blog

MARCH 20, 2023

At Defined.ai, it is essential that we keep our fingers on the pulse of the technology industry. In honor of Defined.ai’s new API-based solution for HITL annotations , we wanted to learn more about what implications a crowd-based workforce could have on the tech giants building these new models. How can I help you today?

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Heartbeat

MARCH 5, 2024

Image by istockphoto Computer vision has become a ground-breaking area in artificial intelligence and machine learning with revolutionary applications. The brains of this technology are complex models that can comprehend and interpret visual data. Developing algorithms that can handle such variations is a significant challenge.

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Snorkel AI

JUNE 12, 2023

They trained it on 100x the amount of data. Better data almost always has a greater impact than fancier models or algorithms in AI—and yet, data development has always been undersupported by AI formalisms and technology. In practice, data-centric operations have become one of the largest blockers to AI value realization.

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Towards AI

APRIL 1, 2023

Learn to monitor your mo in production Photo by Alexander Sinn on Unsplash Introduction Machine learning models are designed to make predictions based on data. However, the data in the real world is constantly changing, and this can affect the accuracy of the model. Table of Contents What is Data Drift?

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Snorkel AI

JUNE 12, 2023

They trained it on 100x the amount of data. Better data almost always has a greater impact than fancier models or algorithms in AI—and yet, data development has always been undersupported by AI formalisms and technology. In practice, data-centric operations have become one of the largest blockers to AI value realization.

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AWS Machine Learning Blog

MAY 5, 2023

In this post, we show how to repurpose an existing dataset via data cleaning, preprocessing, and pre-labeling with a zero-shot classification model in FiftyOne , and adjusting these labels with Amazon SageMaker Ground Truth. You can use Ground Truth and FiftyOne to accelerate your data labeling project. Is it a shirt? A pair of pants?

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The MLOps Blog

MARCH 20, 2023

Long-term ML project involves developing and sustaining applications or systems that leverage machine learning models, algorithms, and techniques. However, dataset version management can be a pain for maturing ML teams, mainly due to the following: 1 Managing large data volumes without utilizing data management platforms.

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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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Defined.ai blog

SEPTEMBER 14, 2022

Data annotation helps machines make sense of text, video, image or audio data. One of the stand-out characteristics of Artificial Intelligence (AI) is its ability to learn, for better or for worse. This annotated data is then used for model training.

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deepsense.ai

FEBRUARY 6, 2024

Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle – the limited availability of training data. Over the years, various successful deep learning architectures have been developed for this task, such as U-Net or SegFormer.

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Bugra Akyildiz

JANUARY 20, 2024

The blog post introduces AMIE, a research AI system designed for diagnostic medical reasoning and conversations. Integration with clinical workflows: Seamless integration of AI systems like AMIE into existing clinical workflows is essential for successful adoption.

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Defined.ai blog

OCTOBER 9, 2022

In the case of Zoom, hackers succeeded in April 2020, with a large data breach that exposed an estimated 500,000 user passwords. The average cost of a data breach was $4.35M in 2022 , and it took an average of 277 days for a company to identify and contain a breach. They also became prime targets for the next big cyberattack.

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Heartbeat

SEPTEMBER 20, 2023

This technology has broad applications, including aiding individuals with visual impairments, improving image search algorithms, and integrating optical recognition with advanced language generation to enhance human-machine interactions. These algorithms can learn and extract intricate features from input images by using convolutional layers.

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AssemblyAI

MAY 3, 2023

In the past months, an exquisitely human-centric approach called Reinforcement Learning from Human Feedback (RLHF) has rapidly emerged as a tour de force in the realm of AI alignment. What is the learning process of a language model? What is RLHF and how to make language models more aligned with human values?

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Sebastian Ruder

AUGUST 15, 2021

Samuel Bowman's and George Dahl's position paper asking " What Will it Take to Fix Benchmarking in Natural Language Understanding? " " I've also written a longer blog post that provides a broader overview of different perspectives, challenges, and potential solutions to improve benchmarking in NLP.

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Explosion

AUGUST 21, 2016

In this post I’ll discuss three ways in which front-end development can improve AI technology: by improving the collection of annotated data, communicating the capabilities of the technology to key stakeholders, and exploring the system’s behaviours and errors. It’s easy to search for exactly those words across your data.

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Flipboard

JULY 31, 2023

In this post, we’ll show you the datasets you can use to build your machine learning projects. After you create a free account, you’ll have access to the best machine learning datasets. Importance and Role of Datasets in Machine Learning Data is king. Many call this software 2.0.

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Probably Approximately a Scientific Blog

JANUARY 12, 2021

This long-overdue blog post is based on the Commonsense Tutorial taught by Maarten Sap, Antoine Bosselut, Yejin Choi, Dan Roth, and myself at ACL 2020. Neural models find shortcuts to the correct answers through dataset-specific input-output correlations , essentially solving the dataset but not the underlying task.

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Viso.ai

MAY 6, 2024

However, there is a subtle difference in exactly what they focus on. Therefore, for this article, we will occasionally refer to them as essentially the same. About us: Viso Suite allows machine learning teams to take control of the entire project lifecycle. To learn more, get a personalized demo from the Viso team.

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The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services.

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PyImageSearch

OCTOBER 16, 2023

This lesson is the last of a 3-part series on Docker for Machine Learning : Getting Started with Docker for Machine Learning Getting Used to Docker for Machine Learning Setting Up a GPU Development Environment Using Docker (this tutorial) To learn how to set up your GPU development environment, just keep reading.

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AssemblyAI

MARCH 21, 2023

This suggests a potential shift of perspective: graph-structured data provides a general and flexible framework for describing and analyzing any possible set of entities and their mutual interactions. What are the actual advantages of Graph Machine Learning? And why do Graph Neural Networks matter in 2023?

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Flipboard

SEPTEMBER 4, 2023

Home Table of Contents Getting Started with Docker for Machine Learning Overview: Why the Need? What Are Containers? How Do Containers Differ from Virtual Machines? Finally, we will top it off by installing Docker on our local machine with simple and easy-to-follow steps. What Are Containers?

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The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. What is DAGWorks? Stefan: Sure.

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John Snow Labs

SEPTEMBER 11, 2023

This blog article delves into the exciting synergy between the T5 model and Spark NLP, an open-source library built on Apache Spark, which enables seamless integration of cutting-edge NLP capabilities into your projects. If you are not familiar with annotation concept, you can review it and other general concepts in Spark on this page.

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PyImageSearch

OCTOBER 2, 2023

The highlight will be the VAE training on the Fashion-MNIST data, followed by a detailed post-training analysis. Jump Right To The Downloads Section A Deep Dive into Variational Autoencoder with PyTorch Introduction Deep learning has achieved remarkable success in supervised tasks, especially in image recognition.

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Flipboard

JULY 10, 2023

Home Table of Contents Introduction to Autoencoders What Are Autoencoders? Revisiting the Story Types of Autoencoder Vanilla Autoencoder Convolutional Autoencoder (CAE) Denoising Autoencoder Sparse Autoencoder Variational Autoencoder (VAE) Sequence-to-Sequence Autoencoder What Are the Applications of Autoencoders?

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PyImageSearch

NOVEMBER 20, 2023

Tools and Methodologies for Studying Causal Effects Welcome back to Part 3 of the 5-part series on Causality in Machine Learning. Picking up where we left off, let us revise what we learned in Part 1. Randomization, natural experiments, and conditioning, what are they? What do I mean by that?

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Google Research AI blog

FEBRUARY 28, 2023

Sharing knowledge is essential to Google’s research philosophy — it accelerates technological progress and expands capabilities community-wide. To do this well, collaborating with experts and researchers outside of Google is essential. You can find other posts in the series here.)

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AWS Machine Learning Blog

MAY 2, 2024

As more powerful large language models (LLMs) are used to perform a variety of tasks with greater accuracy, the number of applications and services that are being built with generative artificial intelligence (AI) is also growing. Human feedback varies in subjectivity across organizations and customer segments. Consider the following color spectrum.

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AWS Machine Learning Blog

DECEMBER 5, 2023

Structured data, defined as data following a fixed pattern such as information stored in columns within databases, and unstructured data, which lacks a specific form or pattern like text, images, or social media posts, both continue to grow as they are produced and consumed by various organizations.

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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. This can be further classified as supervised and unsupervised learning. What is Semi-supervised Learning (SSL)?

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Topbots

JULY 6, 2023

Building on the foundations of Transformer architecture and BERT’s bidirectional upgrade , several groundbreaking language models have emerged in recent years, pushing the boundaries of what machines can understand and generate. What is the goal? What are the results? Where to learn more about this research?

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PyImageSearch

JULY 3, 2023

In this blog post, we will dive deeper into the Netflix movies and series recommendation systems ( Figure 1 ). And, thanks to Netflix recommendations, we don’t have to worry about what to watch. This data includes your location, watch history, ratings, device information, whether you left the show in the middle, etc.

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Flipboard

OCTOBER 9, 2023

This lesson is the 2nd of a 3-part series on Docker for Machine Learning : Getting Started with Docker for Machine Learning Getting Used to Docker for Machine Learning (this tutorial) Lesson 3 To learn how to create a Docker Container for Machine Learning, just keep reading.

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