AI News

AUGUST 11, 2023

IBM Research has unveiled a groundbreaking analog AI chip that demonstrates remarkable efficiency and accuracy in performing complex computations for deep neural networks (DNNs). These digital systems entail constant data transfer between memory and processing units, slowing down computations and reducing energy optimisation.

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AI News

AUGUST 13, 2024

Enter SingularityNET’s ambitious plan: a “multi-level cognitive computing network” designed to host and train the incredibly complex AI architectures required for AGI. Only time will tell if this global network of silicon brains will birth the next great leap in artificial intelligence.

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AI News

MAY 13, 2024

At the core of Aurora lies the Intel Data Center GPU Max Series, built on the innovative Intel Xe GPU architecture, optimised for both AI and HPC tasks. This technological foundation enables parallel processing capabilities, crucial for handling complex neural network AI computations.

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Marktechpost

JANUARY 24, 2024

This shift is driven by neural networks that learn through self-supervision, bolstered by specialized hardware. Data was historically represented in simpler forms, often as hand-crafted feature vectors. This method represents a substantial progression in managing and utilizing the ever-growing data in our digital age.

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AI News

MAY 14, 2024

Pioneering capabilities The introduction of GPT-4o marks a leap from its predecessors by processing all inputs and outputs through a single neural network. Image Credit: OpenAI ) See also: OpenAI takes steps to boost AI-generated content transparency Want to learn more about AI and big data from industry leaders?

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Marktechpost

DECEMBER 23, 2023

Deep Neural Networks (DNNs) represent a powerful subset of artificial neural networks (ANNs) designed to model complex patterns and correlations within data. These sophisticated networks consist of multiple layers of interconnected nodes, enabling them to learn intricate hierarchical representations.

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AI News

JULY 24, 2023

However, Neural Magic tackles this issue head-on through a concept called compound sparsity. Compound sparsity combines techniques such as unstructured pruning, quantisation, and distillation to significantly reduce the size of neural networks while maintaining their accuracy. “We

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Marktechpost

JUNE 9, 2024

xECGArch uniquely separates short-term (morphological) and long-term (rhythmic) ECG features using two independent Convolutional Neural Networks CNNs. The architecture was optimized for atrial fibrillation (AF) detection across four public ECG databases, achieving a 95.43% F1 score on unseen data. Check out the Paper.

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AI News

AUGUST 15, 2023

With its unprecedented efficiency and support for transformer neural networks, we are empowering users across industries to unlock the full potential of AI without compromising on data privacy and security.” Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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AI Weekly

JULY 20, 2023

businessinsider.com AI and Big Data: How AI Is Transforming the Business Landscape In today’s business world, artificial intelligence is a disruptive technology that promises to transform the business landscape, bringing together computer technology and big data to drive powerful tech tools that simulate human intelligence.

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AI News

JULY 27, 2023

Gcore trained a Convolutional Neural Network (CNN) – a model designed for image analysis – using the CIFAR-10 dataset containing 60,000 labelled images, on these devices. Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.

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AI News

JUNE 28, 2023

MosaicML’s machine learning and neural networks experts are at the forefront of AI research, striving to enhance model training efficiency. Photo by Glen Carrie on Unsplash ) See also: MosaicML’s latest models outperform GPT-3 with just 30B parameters Want to learn more about AI and big data from industry leaders?

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AI Weekly

OCTOBER 17, 2024

medium.com Similarity-driven adversarial testing of neural networks As similarity is one of the key components of human cognition and categorization, the approach presents a shift towards a more human-centered security testing of deep neural networks. Explore its AI-powered versatility. Explore its AI-powered versatility.

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Marktechpost

JULY 29, 2023

Join the fastest growing ML Community on Reddit Massive machine learning models that mimic the brain’s information processing are the basis of deep neural networks (DNNs) like the one powering ChatGPT. In addition, they are often only found in very big data centers due to their extreme energy needs.

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AI News

AUGUST 9, 2023

These neural networks power the most complex and compute-intensive generative AI applications, spanning from question answering and code generation to audio, video, image synthesis, and speech recognition. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Analytics Vidhya

MARCH 8, 2022

This article was published as a part of the Data Science Blogathon. Image Source: Author Introduction Deep learning, a subset of machine learning, is undoubtedly gaining popularity due to big data.

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Unite.AI

SEPTEMBER 4, 2024

My experiences have taught me that the future of adtech lies in harmonizing big data, machine learning, and human creativity. Our multi-layered approach combines proprietary algorithms with third-party data to stay ahead of evolving fraud tactics. What specific advantages does it offer over traditional adtech solutions?

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ODSC - Open Data Science

MARCH 10, 2025

Over the past decade, data science has undergone a remarkable evolution, driven by rapid advancements in machine learning, artificial intelligence, and big data technologies. By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow.

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Mlearning.ai

FEBRUARY 25, 2023

How does the Artificial Neural Network algorithm work? In the same way, artificial neural networks (ANNs) were developed inspired by neurons in the brain. ANN approach is a machine learning algorithm inspired by biological neural networks. Big data made it easy to train ANNs.

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Pickl AI

SEPTEMBER 5, 2024

Summary: Convolutional Neural Networks (CNNs) are essential deep learning algorithms for analysing visual data. Introduction Neural networks have revolutionised Artificial Intelligence by mimicking the human brai n’s structure to process complex data. What are Convolutional Neural Networks?

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Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

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Unite.AI

OCTOBER 22, 2024

We use Big O notation to describe this growth, and quadratic complexity O(n²) is a common challenge in many AI tasks. AI models like neural networks , used in applications like Natural Language Processing (NLP) and computer vision , are notorious for their high computational demands.

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IBM Journey to AI blog

JANUARY 10, 2024

AI can also work from deep learning algorithms, a subset of ML that uses multi-layered artificial neural networks (ANNs)—hence the “deep” descriptor—to model high-level abstractions within big data infrastructures.

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Unite.AI

AUGUST 22, 2023

You spent over 7 years at Google, where you helped to build and lead teams working on strategy, operations, big data and machine learning. We figured out how to use all the big data we had on how advertisers used our products to help sales teams. What was your favorite project and what did you learn from this experience?

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Pickl AI

OCTOBER 25, 2023

How Big Data and AI Work Together: Synergies & Benefits: The growing landscape of technology has transformed the way we live our lives. of companies say they’re investing in Big Data and AI. Although we talk about AI and Big Data at the same length, there is an underlying difference between the two.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? Deep learning teaches computers to process data the way the human brain does.

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Unite.AI

FEBRUARY 19, 2024

RPA Bots Becoming Super Bots: Driving Intelligent Decision Making RPA bots that originally operated on rule-based programs through learning patterns and emulating human behavior for performing repetitive and menial tasks have become super bots, with Conversational AI and Neural Network algorithms coming into force.

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Marktechpost

JULY 30, 2024

However, the application of LLMs to real-world big data presents significant challenges, primarily due to the enormous costs involved. These models utilize advanced technologies such as web-scale unsupervised pretraining, instruction fine-tuning, and value alignment, showcasing strong performance across various tasks.

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Viso.ai

OCTOBER 10, 2024

In supervised learning, images are annotated to train neural networks – Image Annotation with Viso Suite What Is the Goal of Pattern Recognition? Most prominently, fields of artificial intelligence aim to enable machines to solve complex human recognition tasks, such as deep neural network face recognition.

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IBM Journey to AI blog

JUNE 14, 2023

With IoT devices and sensors collecting data from machines, equipment and assembly lines, AI-powered algorithms can quickly process and analyze inputs to identify patterns and trends, helping manufacturers understand how production processes are performing. Companies can also use AI systems to identify anomalies and equipment defects.

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ODSC - Open Data Science

OCTOBER 28, 2024

A machine learning decision tree can help data science professionals prevent synthetic identity theft. A neural network operates comparably but on a higher level. Information is often more digestible in a graph or chart than in a spreadsheet — especially when big data is involved.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Companies also take advantage of ML in smartphone cameras to analyze and enhance photos using image classifiers, detect objects (or faces) in the images, and even use artificial neural networks to enhance or expand a photo by predicting what lies beyond its borders.

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NYU Center for Data Science

FEBRUARY 14, 2024

Davidson’s upcoming paper, “Spatial Relation Categorization in Infants and Deep Neural Networks,” co-authored with CDS Assistant Professor of Psychology and Data Science Brenden Lake and former CDS Research Scientist Emin Orhan , is set for publication in Cognition in early 2024.

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Marktechpost

DECEMBER 7, 2023

When combined with neural networks, point-based graphics provide an impressive explicit representation that is both realistic and more efficient than NeRF in the human NVS test. Conversely, explicit representations’ real-time and high-speed rendering capabilities, especially point clouds, have attracted sustained attention.

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Marktechpost

FEBRUARY 22, 2024

Traditionally, methods like pixel-based classifications struggled against the backdrop of complex environments, leading researchers to turn towards convolutional neural networks (CNNs) and deep learning for solutions.

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Mlearning.ai

MAY 5, 2023

Knowledge of Neural Networks : LLMs are typically built using deep learning techniques, so you should have a good understanding of neural networks and how they work. This includes understanding the basics of feedforward and recurrent neural networks, as well as more advanced architectures like transformers.

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AWS Machine Learning Blog

MAY 15, 2023

Algorithm Selection Amazon Forecast has six built-in algorithms ( ARIMA , ETS , NPTS , Prophet , DeepAR+ , CNN-QR ), which are clustered into two groups: statististical and deep/neural network. Deep/neural network algorithms also perform very well on sparse data set and in cold-start (new item introduction) scenarios.

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