Dataconomy

OCTOBER 23, 2024

Other key technologies that have recently opened doors to unprecedented growth opportunities in the corporate world include Big Data , the Internet of Things (IoT), cloud computing, and blockchain. But all that changed when cloud computing happened. Image credit ) 1.

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Data Science Connect

JULY 26, 2023

The Emergence of Edge Computing: A Game-Changer Edge computing has emerged as a game-changing technology, revolutionizing how data is processed and delivered. Unlike traditional cloud computing, where data is sent to centralized data centers, edge computing brings processing closer to the data source.

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Dataconomy

APRIL 20, 2023

They have revolutionized the way we process and store information, and are used in a wide variety of applications, from personal devices like smartphones and laptops to large-scale data centers and cloud computing services.

Artificial Intelligence 154

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Heartbeat

MAY 23, 2023

However, complicated deep learning algorithms can strain conventional cloud computing infrastructures, resulting in poorer processing rates, significant security risks, and expensive bandwidth costs. Edge computing may change how we think about deep learning. But edge computing isn’t just about convenience.

Deep Learning 52

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Dataconomy

JULY 14, 2023

Machine learning is the science of teaching computers to learn on their own. By feeding computers large amounts of data, machine learning algorithms can learn to identify patterns and make predictions. Cloud computing services can provide scalability, reliability, and security for M2M data.

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IBM Journey to AI blog

JUNE 29, 2023

It integrates advanced technologies—like the Internet of Things (IoT), artificial intelligence (AI) and cloud computing —into an organization’s existing manufacturing processes. Industry 4.0 Companies can also use AI to identify anomalies and equipment defects.

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Dataconomy

MARCH 28, 2023

The emergence of the Internet of Things (IoT) has led to the proliferation of connected devices and sensors that generate vast amounts of data. An IoT ( Internet of Things ) ecosystem refers to a network of interconnected devices, sensors, and software applications that work together to collect, analyze, and share data.

Data Science 70

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Dataconomy

MARCH 28, 2023

The emergence of the Internet of Things (IoT) has led to the proliferation of connected devices and sensors that generate vast amounts of data. An IoT ( Internet of Things ) ecosystem refers to a network of interconnected devices, sensors, and software applications that work together to collect, analyze, and share data.

Data Science 70

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Smart Data Collective

MAY 7, 2023

New digital technologies such as artificial intelligence, data analytics, machine learning automation, and the Internet of Things (IoT) may seem like a breakthrough for decision-making, but they are not bulletproof. It uses algorithms to scramble data, making it unreadable to anyone without access to the decryption key.

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Dataconomy

APRIL 4, 2023

Anything as a Service is a cloud computing model that refers to the delivery of various services, applications, and resources over the internet. XaaS enables businesses to access a wide range of services and solutions by providing a flexible, cost-effective, and scalable model for cloud computing.

Cloud Computing 79

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Dataconomy

AUGUST 6, 2023

From the orchestration of meteorological forecasts to the intricate simulation of molecular interactions and the rapid training of artificial intelligence algorithms, parallel processing has propelled us into a realm of heightened efficiency and expedited insights.

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Dataconomy

APRIL 20, 2023

They have revolutionized the way we process and store information, and are used in a wide variety of applications, from personal devices like smartphones and laptops to large-scale data centers and cloud computing services.

Artificial Intelligence 103

Artificial Intelligence Artificial Intelligence Cloud Computing Internet of Things 103

Smart Data Collective

OCTOBER 26, 2023

Machine learning algorithms can adapt and improve over time, enabling them to recognize new, previously unseen attack patterns. Rapid growth in the use of recently developed technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud computing has introduced new security threats and vulnerabilities.

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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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Dataconomy

APRIL 4, 2023

Anything as a Service is a cloud computing model that refers to the delivery of various services, applications, and resources over the internet. XaaS enables businesses to access a wide range of services and solutions by providing a flexible, cost-effective, and scalable model for cloud computing.

Cloud Computing 70

Cloud Computing Internet of Things Azure Artificial Intelligence 70

IBM Journey to AI blog

JULY 26, 2023

Digital twin technology, an advancement stemming from the Industrial Internet of Things (IIoT), is reshaping the oil and gas landscape by helping providers streamline asset management, optimize performance and reduce operating costs and unplanned downtime.

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IBM Journey to AI blog

JANUARY 29, 2024

An example is machine learning, which enables a computer or machine to mimic the human mind. Another is augmented reality technology that uses algorithms to mimic digital information and understand a physical environment. The AI technology drives innovation to smart products and a more pointed focus on customer and user experience.

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Pickl AI

DECEMBER 6, 2024

Generative AI Generative AI refers to algorithms that can create new content, from text and images to music and videos. Quantum Computing Quantum computing harnesses the principles of quantum mechanics to process information at unprecedented speeds.

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Pickl AI

AUGUST 1, 2024

Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms. Understanding Deep Learning Engineer A Deep Learning engineer is primarily responsible for creating and optimising algorithms that enable machines to learn from data.

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Pickl AI

SEPTEMBER 3, 2024

Edge Computing With the rise of the Internet of Things (IoT), edge computing is becoming more prevalent. Professionals should stay informed about emerging trends, new algorithms, and best practices through online courses, workshops, and industry conferences.

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IBM Journey to AI blog

FEBRUARY 9, 2024

They can be run locally on smaller devices: this allows more sophisticated AI in scenarios like edge computing and the internet of things (IoT). Explainable AI is essential to understanding, improving and trusting the output of AI systems.

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AWS Machine Learning Blog

NOVEMBER 27, 2024

Prerequisites This post assumes you have the following: An AWS account The AWS Command Line Interface (AWS CLI) installed The AWS CDK Toolkit (cdk command) installed Node PNPM Access to models in Amazon Bedrock Chess with fine-tuned models Traditional approaches to chess AI have focused on handcrafted rules and search algorithms.

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