IBM Journey to AI blog

NOVEMBER 2, 2023

According to a Cloud Native Computing Foundation (CNCF) report (link resides outside ibm.com), Kubernetes is the second largest open-source project in the world after Linux and the primary container orchestration tool for 71% of Fortune 100 companies. Control plane nodes , which control the cluster.

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Dataconomy

AUGUST 9, 2023

Nvidia AI Workbench has been unveiled, signaling a potentially transformative moment in the creation and deployment of generative AI. By leveraging the Nvidia AI Workbench, developers can expect a more streamlined process, allowing them to work on different Nvidia AI platforms, such as PCs and workstations.

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AWS Machine Learning Blog

JULY 17, 2023

With cloud computing, as compute power and data became more available, machine learning (ML) is now making an impact across every industry and is a core part of every business and industry. Amazon SageMaker Studio is the first fully integrated ML development environment (IDE) with a web-based visual interface.

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Dataconomy

SEPTEMBER 1, 2024

In this era of modern business operations, cloud computing cannot be overlooked, thanks to its scalability, flexibility, and accessibility for data processing, storage, and application deployment. This raises a lot of security questions about the suitability of the cloud. These two intersect in many ways discussed below.

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IBM Journey to AI blog

OCTOBER 31, 2023

Leveraging cloud computing to speed time to market Firms (irrespective of size) aiming to expand their business horizons and gain a competitive edge in terms of time-to-market can strategically leverage two key elements to enhance opportunities: cloud computing and new EDA licensing.

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Applied Data Science

AUGUST 2, 2021

This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI  — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. Case-studies from real-life business scenarios and advice you can act on. Download the free, unabridged version here.

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Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). Artificial intelligence (AI). Messages and notification.

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Smart Data Collective

JUNE 4, 2021

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Clustering (Unsupervised). With Clustering the data is divided into groups. By applying clustering based on distance, the villages are divided into groups. Domain experts of all fields use it.

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IBM Journey to AI blog

NOVEMBER 13, 2023

Nodes run the pods and are usually grouped in a Kubernetes cluster, abstracting the underlying physical hardware resources. Large-scale app deployment Heavily trafficked websites and cloud computing applications receive millions of user requests each day.

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AWS Machine Learning Blog

MARCH 10, 2025

The intersection of AI and financial analysis presents a compelling opportunity to transform how investment professionals access and use credit intelligence, leading to more efficient decision-making processes and better risk management outcomes. The use of multiple external cloud providers complicated DevOps, support, and budgeting.

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Towards AI

JULY 23, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This was another huge week for foundation LLMs, with the release of GPT-4o mini, the leak of LLama 3.1 Publishers are updating robots.txt and changing terms of service to prevent AI scraping.

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O'Reilly Media

SEPTEMBER 19, 2023

Cloud computing? It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” Goodbye, Hadoop.

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Dataconomy

APRIL 26, 2023

This is particularly true in the field of edge computing, where the need for innovative solutions has never been more pressing. We will review some of the current market leaders in edge computing and examine the unique strengths that have helped them rise to the top of the industry.

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Data Science Dojo

AUGUST 18, 2023

Large language models (LLMs) are AI models that can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. They are typically trained on clusters of computers or even on cloud computing platforms. LLMs are a type of generative AI.

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AWS Machine Learning Blog

AUGUST 8, 2023

You can run Spark applications interactively from Amazon SageMaker Studio by connecting SageMaker Studio notebooks and AWS Glue Interactive Sessions to run Spark jobs with a serverless cluster. With interactive sessions, you can choose Apache Spark or Ray to easily process large datasets, without worrying about cluster management.

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IBM Journey to AI blog

AUGUST 8, 2023

In recent years, the rapid adoption of Kubernetes has emerged as a transformative force in the world of cloud computing. This inefficient utilization can create workload scheduling issues, hamper cluster performance and trigger additional scaling events, further amplifying expenses.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

One of the key drivers of Philips’ innovation strategy is artificial intelligence (AI), which enables the creation of smart and personalized products and services that can improve health outcomes, enhance customer experience, and optimize operational efficiency.

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Dataconomy

MAY 12, 2023

When more processing power is required, new nodes can be added to the distributed computing network. AI computers are redefining how we think about computing Availability In the event of a failure in any of the machines within your distributed computing system, the overall functionality of the system will not be compromised.

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Smart Data Collective

APRIL 8, 2020

In order to circumvent this issue and ensure more efficient big data analytics systems, engineers from companies like Yahoo created Hadoop in 2006, as an Apache open source project, with a distributed processing framework which made the running of big data applications possible even on clustered platforms.

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IBM Journey to AI blog

FEBRUARY 29, 2024

For example, with some services, users can not only create Kubernetes clusters but also deploy scalable web apps and analyze logs. At present, Docker and Kubernetes are by far the most popularly used tools dealing with computer containers.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Companies are finding NLP to be one of the best applications of AI regardless of industry.

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AWS Machine Learning Blog

MAY 1, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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ODSC - Open Data Science

SEPTEMBER 16, 2024

In a move aimed at pushing the limits of AI and data processing, NVIDIA and Oracle have teamed up to launch the first zettascale Oracle Cloud Infrastructure (OCI) Supercluster. OCI Superclusters: Pioneering AI Compute OCI Superclusters offer unprecedented scalability. OCI will be powered by NVIDIA’s Blackwell platform.

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AWS Machine Learning Blog

AUGUST 9, 2024

This post provides an overview of a custom solution developed by the AWS Generative AI Innovation Center (GenAIIC) for Deltek , a globally recognized standard for project-based businesses in both government contracting and professional services. Deltek serves over 30,000 clients with industry-specific software and information solutions.

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The MLOps Blog

MARCH 23, 2023

Even for basic inference on LLM, multiple accelerators or multi-node computing clusters like multiple Kubernetes pods are required. But the issue we found was that MP is efficient in single-node clusters, but in a multi-node setting, the inference isn’t efficient. For instance, a 1.5B 2 Calculate the size of the model.

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Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

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IBM Journey to AI blog

JULY 18, 2024

Distributed computing even works in the cloud. And while it’s true that distributed cloud computing and cloud computing are essentially the same in theory, in practice, they differ in their global reach, with distributed cloud computing able to extend cloud computing across different geographies.

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Pickl AI

AUGUST 27, 2024

Read Blog: Virtualisation in Cloud Computing and its Diverse Forms. Edge Computing vs. Cloud Computing: Pros, Cons, and Future Trends. Cloud Computing : Many organisations use vSphere as a foundation for private clouds, leveraging its automation and management capabilities to deliver scalable cloud services.

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Pickl AI

NOVEMBER 28, 2024

Familiarity with cloud computing tools supports scalable model deployment. Key techniques in unsupervised learning include: Clustering (K-means) K-means is a clustering algorithm that groups data points into clusters based on their similarities. It’s often used in customer segmentation and anomaly detection.

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Heartbeat

DECEMBER 5, 2023

A significant player is pushing the boundaries and enabling data-intensive work like HPC and AI: NVIDIA! These improvements have enabled it to quickly become the hardware of choice for researchers working on artificial intelligence (AI) projects, such as LLMs. This blog will briefly introduce and compare the A100, H100, and H200 GPUs.

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Towards AI

FEBRUARY 11, 2025

Author(s): Richie Bachala Originally published on Towards AI. Beyond Scale: Data Quality for AI Infrastructure The trajectory of AI over the past decade has been driven largely by the scale of data available for training and the ability to process it with increasingly powerful compute & experimental models.

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Mlearning.ai

MAY 23, 2023

Check out this course to build your skillset in Seaborn —  [link] Big Data Technologies Familiarity with big data technologies like Apache Hadoop, Apache Spark, or distributed computing frameworks is becoming increasingly important as the volume and complexity of data continue to grow.

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ODSC - Open Data Science

JULY 11, 2023

Its first application was developed at the Massachusetts Institute of Technology in 1966, well before the dawn of personal computers. [1] 1] The typical application familiar to readers is much more recent, when AI operates as chatbots, enhancing or at least facilitating the user experience on many websites. Not a cloud computer?

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AWS Machine Learning Blog

OCTOBER 30, 2024

These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. About the Authors Kara Yang is a Data Scientist at AWS Professional Services in the San Francisco Bay Area, with extensive experience in AI/ML.

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Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

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Pickl AI

NOVEMBER 13, 2024

Machine Learning is a subset of Artificial Intelligence (AI) that focuses on developing algorithms that allow computers to learn from and make predictions based on data. Typically used for clustering (grouping data into categories) or dimensionality reduction (simplifying data without losing important information).

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The MLOps Blog

JUNE 27, 2023

With Azure Machine Learning, data scientists can leverage pre-built models, automate machine learning tasks, and seamlessly integrate with other Azure services, making it an efficient and scalable solution for machine learning projects in the cloud. Check out the Kubeflow documentation.

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