Towards AI

DECEMBER 26, 2024

Last Updated on December 27, 2024 by Editorial Team Author(s): Richard Warepam Originally published on Towards AI. 4 Things to Keep in Mind Before Deploying Your ML Models This member-only story is on us. medium.com Regardless of the project, it might be software development or ML Model building. Published via Towards AI

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Pickl AI

DECEMBER 26, 2024

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. In Data Science in a Cloud World, we explore how cloud computing has revolutionised Data Science.

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Dataconomy

JUNE 16, 2023

Gamma AI is a great tool for those who are looking for an AI-powered cloud Data Loss Prevention (DLP) tool to protect Software-as-a-Service (SaaS) applications. Any organization’s cybersecurity plan must include data loss prevention (DLP), especially in the age of cloud computing and software as a service (SaaS).

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Precisely

MAY 20, 2024

Cloud computing is more crucial than ever in 2024. With technology landscapes transforming at a breakneck pace, your ability to leverage cloud computing could be the game changer needed to boost efficiency and spark innovation in your business. Hybrid and multi-cloud adoption : The future is now, and it’s hybrid.

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Pickl AI

JANUARY 9, 2025

Summary: Cloud computing security architecture is essential for protecting sensitive data, ensuring compliance, and preventing threats. As technology advances, AI, machine learning, and blockchain play vital roles in strengthening cloud security frameworks to safeguard businesses against evolving risks. from 2024 to 2030.

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Pickl AI

APRIL 7, 2025

Summary: This blog explains the difference between cloud computing and grid computing in simple terms. Ideal for beginners and tech enthusiasts exploring modern computing trends. Introduction Welcome to our exploration, where we highlight the difference between cloud computing and grid computing.

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Pickl AI

JANUARY 31, 2025

Summary: In this cloud computing notes we offers the numerous advantages for businesses, such as cost savings, scalability, enhanced collaboration, and improved security. Embracing cloud solutions can significantly enhance operational efficiency and drive innovation in today’s competitive landscape.

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Data Science Dojo

FEBRUARY 20, 2023

Machine learning (ML) is the technology that automates tasks and provides insights. It comes in many forms, with a range of tools and platforms designed to make working with ML more efficient. It features an ML package with machine learning-specific APIs that enable the easy creation of ML models, training, and deployment.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

The AWS Neuron Monitor container , used with Prometheus and Grafana, provides advanced visualization of your ML application performance. To learn more about setting up and using these monitoring capabilities, see Scale and simplify ML workload monitoring on Amazon EKS with AWS Neuron Monitor container.

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Dataversity

DECEMBER 3, 2021

As edge cloud computing, AI/ML, and IoT revolutionize computing, many enterprises are considering pulling back on data center operations in favor of cloud-based solutions.

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Pickl AI

MARCH 1, 2023

What is Cloud Computing? Cloud computing is a way to use the internet to access different types of technology services. The term “cloud computing” was first used in a paper by computer scientist and mathematician Ramnath Chellappa in 1997.

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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. Give this technique a try to take your team’s ML modelling to the next level. Download the free, unabridged version here.

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Dataconomy

MAY 2, 2023

What do machine learning engineers do: ML engineers design and develop machine learning models The responsibilities of a machine learning engineer entail developing, training, and maintaining machine learning systems, as well as performing statistical analyses to refine test results. Is ML engineering a stressful job?

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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

JUNE 5, 2024

SaaS takes advantage of cloud computing infrastructure and economies of scale to provide clients a more streamlined approach to adopting, using and paying for software. AI in SaaS analytics Most industries have had to reckon with AI proliferation and AI-driven business practices to some extent.

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

The rise of generative artificial intelligence (AI) has brought an inflection of foundation models (FMs). Goldman Sachs estimated that generative AI could automate 44% of legal tasks in the US. AWS AI and machine learning (ML) services help address these concerns within the industry.

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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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AWS Machine Learning Blog

APRIL 7, 2025

These models are designed for industry-leading performance in image and text understanding with support for 12 languages, enabling the creation of AI applications that bridge language barriers. With SageMaker AI, you can streamline the entire model deployment process.

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Pickl AI

JULY 11, 2024

Summary: Platform as a Service (PaaS) offers a cloud development environment with tools, frameworks, and resources to streamline application creation. Introduction The cloud computing landscape has revolutionized the way businesses approach IT infrastructure and application development.

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AWS Machine Learning Blog

NOVEMBER 8, 2023

In this era of cloud computing, developers are now harnessing open source libraries and advanced processing power available to them to build out large-scale microservices that need to be operationally efficient, performant, and resilient. This can lead to higher latency and increased network bandwidth utilization.

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Smart Data Collective

JANUARY 13, 2022

The market size for AI in marketing is expected to grow ove r 31% a year through 2028. Unfortunately, there are a number of AI-driven marketing mistakes companies continue to make. AI technology is helping solve customer service problems. AI technology is helping solve customer service problems. Information Gap.

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Towards AI

APRIL 19, 2024

Last Updated on April 21, 2024 by Editorial Team Author(s): Jennifer Wales Originally published on Towards AI. Get a closer view of the top generative AI companies making waves in 2024. They are soaring with career opportunities for certified AI professionals with the best AI certification programs.

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IBM Journey to AI blog

FEBRUARY 6, 2024

It’s hard to imagine a business world without cloud computing. There would be no e-commerce, remote work capabilities or the IT infrastructure framework needed to support emerging technologies like generative AI and quantum computing. What is cloud computing?

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Flipboard

FEBRUARY 13, 2025

AI/ML engineers would prefer to focus on model training and data engineering, but the reality is that we also need to understand the infrastructure and mechanics […]

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AWS Machine Learning Blog

MARCH 14, 2024

Generative AI applications driven by foundational models (FMs) are enabling organizations with significant business value in customer experience, productivity, process optimization, and innovations. In this post, we explore different approaches you can take when building applications that use generative AI.

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AWS Machine Learning Blog

MAY 7, 2024

A more efficient way to manage meeting summaries is to create them automatically at the end of a call through the use of generative artificial intelligence (AI) and speech-to-text technologies. Hugging Face is an open-source machine learning (ML) platform that provides tools and resources for the development of AI projects.

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AWS Machine Learning Blog

MAY 30, 2024

Amazon Bedrock is a fully managed service that makes FMs from leading AI startups and Amazon available via an API, so one can choose from a wide range of FMs to find the model that is best suited for their use case. These factors led to the selection of Amazon Aurora PostgreSQL as the store for vector embeddings.

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IBM Journey to AI blog

MARCH 20, 2024

Most of us take for granted the countless ways public cloud-related services—social media sites (Instagram), video streaming services (Netflix), web-based email applications (Gmail), and more—permeate our lives. What is a public cloud? A public cloud is a type of cloud computing in which a third-party service provider (e.g.,

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Dataconomy

OCTOBER 23, 2024

Artificial intelligence (AI) and machine learning (ML) are arguably the frontiers of modern technology. AI and ML can streamline various business processes and help maximize your returns margins. Businesses can implement AI-driven software to ease support services like virtual assistance and product recommendations.

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Towards AI

SEPTEMBER 5, 2023

Last Updated on September 6, 2023 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. This wave of interest has also triggered a significant influx of venture capital investments into the AI sector. This policy had previously delayed the public release of LLM chatbots in China.

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The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Amazon Q Business addresses this need as a fully managed generative AI-powered assistant that helps you find information, generate content, and complete tasks using enterprise data. This solution enables you to interact with your file system data using conversational AI, making information discovery more intuitive and efficient.

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Mlearning.ai

APRIL 28, 2023

But there are some strategies that artificial intelligence(AI) developers can implement to optimize and decrease execution time for Python machine learning (ML) models, for instance: Using binary formats for saving models Saving machine learning models in binary formats like .pkl, pb can decrease execution time for Python.

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AWS Machine Learning Blog

MARCH 18, 2025

With this launch, you can now deploy NVIDIAs optimized reranking and embedding models to build, experiment, and responsibly scale your generative AI ideas on AWS. As part of NVIDIA AI Enterprise available in AWS Marketplace , NIM is a set of user-friendly microservices designed to streamline and accelerate the deployment of generative AI.

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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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IBM Journey to AI blog

DECEMBER 20, 2023

Artificial intelligence (AI) is a transformative force. By giving machines the growing capacity to learn, reason and make decisions, AI is impacting nearly every industry, from manufacturing to hospitality, healthcare and academia. Without an AI strategy, organizations risk missing out on the benefits AI can offer.

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Data Science Connect

JULY 28, 2023

This allows data scientists to access comprehensive datasets for in-depth analysis and AI-driven insights. Edge AI for Real-Time Decision-Making Edge AI brings AI processing capabilities to IoT devices at the network edge, reducing latency and empowering IoT devices to make real-time decisions without relying on cloud computing.

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