How AI is Transforming Recruiting for a Better Future

This blog post focuses on new features and improvements. For a comprehensive list, including bug fixes, please see the release notes. Compute Orchestration [Private Preview] Clarifai’s new Compute Orchestration system provides you with an efficient way to deploy inference workloads on any compute, in any bare metal, or cloud environment. This feature is currently in Private Preview. … Read more

In the fast-paced world of insurance, handling claims is both an art and a science. The goal is not just to process claims faster but to do so with precision, prioritizing critical information that directly impacts outcomes. However, claims professionals are often flooded with mountains of documents, making it nearly impossible to manually sift through … Read more

object(WP_Post)#7057 (24) { [“ID”]=> int(35151) [“post_author”]=> string(2) “36” [“post_date”]=> string(19) “2024-10-16 22:29:38” [“post_date_gmt”]=> string(19) “2024-10-16 22:29:38” [“post_content”]=> string(10781) “ It’s become a truism to state that local journalism is in decline. But that story has been complicated by a new form of socially conscious ‘start-up’ publication cropping up across both ANZ and the wider world.  … Read more

Artificial intelligence is transforming the business landscape at a pace never witnessed before, and it is not over yet. As we enter 2024, staying up-to-date on the latest trends is good for business leaders but essential if they want to maintain a competitive edge. Here are some AI trends that every business leader should know: … Read more

This article demystifies the ML learning modeling process under the prism of statistics. We will understand how our assumptions on the data enable us to create meaningful optimization problems. In fact, we will derive commonly used criteria such as cross-entropy in classification and mean square error in regression. Finally, I am trying to answer an … Read more

Multimodal learning refers to the process of learning representations from different types of modalities using the same model. Different modalities are characterized by different statistical properties. In the context of machine learning, input modalities include images, text, audio, etc. In this article, we will discuss only images and text as inputs and see how we … Read more

In this hands-on tutorial, we will provide you with a reimplementation of SimCLR self-supervised learning method for pretraining robust feature extractors. This method is fairly general and can be applied to any vision dataset, as well as different downstream tasks. In a previous tutorial, I wrote a bit of a background on the self-supervised learning … Read more

This blog post focuses on new features and improvements. For a comprehensive list, including bug fixes, please see the release notes. Introduced app templates for streamlined app creation. We now provide pre-built, ready-to-use templates that expedite the app creation process. Each template comes with a range of resources, such as datasets, models, workflows, and modules, allowing … Read more

In this tutorial, we will learn how to use nn.parallel.DistributedDataParallel for training our models in multiple GPUs. We will take a minimal example of training an image classifier and see how we can speed up the training. Let’s start with some imports. import torchimport torchvisionimport torchvision.transforms as transformsimport torch.nn as nnimport torch.nn.functional as Fimport torch.optim … Read more