IBM Journey to AI blog

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

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AI News

JUNE 3, 2024

delivers accurate and relevant information, making it an indispensable tool for professionals in these fields. Harnessing the Power of Machine Learning and Deep Learning At TickLab, our innovative approach is deeply rooted in the advanced capabilities of machine learning (ML) and deep learning (DL).

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Unite.AI

DECEMBER 26, 2024

AI algorithms can be trained on a dataset of countless scenarios, adding an advanced level of accuracy in differentiating between the activities of daily living and the trajectory of falls that necessitate concern or emergency intervention.

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Analytics Vidhya

JULY 25, 2022

Introduction Computer Vision Is one of the leading fields of Artificial Intelligence that enables computers and systems to extract useful information from digital photos, movies, and other visual inputs. It uses Machine Learning-based Model Algorithms and Deep Learning-based Neural Networks for its implementation. […].

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Unite.AI

JANUARY 17, 2025

Perception : Agentic AI systems are equipped with advanced sensors and algorithms that allow them to perceive their surroundings. These systems use sophisticated algorithms, including machine learning and deep learning, to analyze data, identify patterns, and make informed decisions.

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Unite.AI

FEBRUARY 21, 2025

At the core of its performance are its advanced reasoning models, powered by cutting-edge deep learning techniques. These models enable Grok-3 to process information with high accuracy, providing nuanced and contextually relevant responses that feel more human-like than ever before.

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Marktechpost

DECEMBER 8, 2023

Deep learning is finding its utility in all aspects of life. Its applications span diverse fields, from image and speech recognition to medical diagnosis and autonomous vehicles, showcasing its transformative potential in revolutionizing how machines comprehend and respond to information. It has become successful in robotics.

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Marktechpost

MAY 8, 2024

Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology. Deep learning and AI technologies play crucial roles in both modular and End2End systems for autonomous driving. Classical methodologies for these tasks are also explored.

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Marktechpost

MARCH 5, 2024

Deep Learning models have revolutionized our ability to process and understand vast amounts of data. However, a vast portion of the digital world comprises binary data, the fundamental building block of all digital information, which still needs to be explored by current deep-learning models.

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AI News

AUGUST 9, 2024

To elaborate, Machine learning (ML) models – especially deep learning networks – require enormous amounts of data to train effectively, often relying on powerful GPUs or specialised hardware to process this information quickly. On the other hand, AI thrives on massive datasets and demands high-performance computing.

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NVIDIA

MARCH 19, 2025

Everybody at NVIDIA is incentivized to figure out how to work together because the accelerated computing work that NVIDIA does requires full-stack optimization, said Bryan Catanzaro, vice president of applied deep learning research at NVIDIA. Learn more about NVIDIA Research at GTC.

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Unite.AI

AUGUST 28, 2024

Ethical and Privacy Issues Obtaining informed consent from patients on how AI systems will use their data can be complex , especially when the public does not fully understand the underlying logic. For example, an algorithm that predicts which patients need more intensive care based on healthcare costs rather than actual illness.

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Marktechpost

JANUARY 24, 2024

Artificial Intelligence has witnessed a revolution, largely due to advancements in deep learning. This shift is driven by neural networks that learn through self-supervision, bolstered by specialized hardware. Before the advent of deep learning, data representation often involved manually curated feature vectors.

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Unite.AI

SEPTEMBER 18, 2023

To prevent these scenarios, protection of data, user assets, and identity information has been a major focus of the blockchain security research community, as to ensure the development of the blockchain technology, it is essential to maintain its security.

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Aiiot Talk

MAY 6, 2023

AI comprises numerous technologies like deep learning, machine learning, natural language processing, and computer vision. With the help of these technologies, AI is now capable of learning, reasoning, and processing complex data. Deep learning algorithms have brought a massive improvement in medical imaging diagnosis.

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PyImageSearch

DECEMBER 23, 2024

These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. ANN algorithms are designed to quickly find data points close to a given query point without necessarily being the absolute closest.

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Marktechpost

APRIL 12, 2024

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models. This state is updated as the network processes each element of the sequence.

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AssemblyAI

MARCH 21, 2023

Traditional AI methods have been designed to extract information from objects encoded by somewhat “rigid” structures. Introduction Graph data is everywhere in the world: any system consisting of entities and relationships between them can be represented as a graph.

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Marktechpost

MARCH 30, 2024

In 2024, the landscape of Python libraries for machine learning and deep learning continues to evolve, integrating more advanced features and offering more efficient and easier ways to build, train, and deploy models. PyTorch PyTorch is a widely used open-source machine learning library based on the Torch library.

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Marktechpost

APRIL 21, 2024

MIT researchers proposed working with deep learning to address the challenges of understanding and accurately modeling the planetary boundary layer (PBL) to improve weather forecasting and climate projections and deal with issues like droughts. These methods work to some extent, but they can not solve very complicated PBL structures.

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Marktechpost

MARCH 23, 2024

AI researchers are taking the game to a new level with geometric deep learning. However, for the algorithms of TacticAI, it’s a complex physics problem that is just waiting to be solved through data and prediction. The future of football coaching has arrived – and it’s taking geometric deep learning to heart.

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Unite.AI

MARCH 28, 2024

Powered by AI algorithms, these robots possess the ability to adapt, learn, and optimize operations in real-time. By harnessing vast amounts of data generated throughout the production lifecycle, AI algorithms can uncover insights, predict outcomes, and optimize operations with unprecedented precision.

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Unite.AI

NOVEMBER 6, 2023

Traditional machine learning is a broad term that covers a wide variety of algorithms primarily driven by statistics. The two main types of traditional ML algorithms are supervised and unsupervised. These algorithms are designed to develop models from structured datasets. K-means Clustering. K-means Clustering.

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Unite.AI

SEPTEMBER 14, 2023

Blockchain : A distributed and immutable ledger that securely stores data and information in a decentralized and trusted manner. Enhanced Data Security A major reason behind blockchain’s immense popularity is that it offers a highly safe & secure method to store information on the web.

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AssemblyAI

SEPTEMBER 4, 2024

  Today, deep learning technology, heavily influenced by Baidu’s seminal paper Deep Speech: Scaling up end-to-end speech recognition , dominates the field. In the next section, we’ll discuss how these deep learning approaches work in more detail. How does speech recognition work?

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Marktechpost

JANUARY 15, 2025

This gap has led to the evolution of deep learning models, designed to learn directly from raw data. What is Deep Learning? Deep learning, a subset of machine learning, is inspired by the structure and functioning of the human brain. High Accuracy: Delivers superior performance in many tasks.

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PyImageSearch

DECEMBER 9, 2024

Citation Information 3D Gaussian Splatting vs NeRF: The End Game of 3D Reconstruction? In this tutorial, you will learn about 3D Gaussian Splatting. Essentially, you send 30+ input images to an SfM algorithm, and it returns a point cloud. 2023 ) See how we added 3 blocks? Thats A, B, and C. So, where do we begin?

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Towards AI

NOVEMBER 19, 2023

Photo by Pietro Jeng on Unsplash Deep learning is a type of machine learning that utilizes layered neural networks to help computers learn from large amounts of data in an automated way, much like humans do. Loss functions guide learning by measuring errors. Activation functions introduce non-linear patterns.

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AssemblyAI

SEPTEMBER 4, 2023

Data compression plays a pivotal role in today’s digital world, facilitating efficient storage and transmission of information. The MP3 encoding algorithm significantly changed how we store and share music data and stands as a famous example. Let’s now take an overview of how quantization works.

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Unite.AI

OCTOBER 12, 2023

research scientist with over 16 years of professional experience in the fields of speech/audio processing and machine learning in the context of Automatic Speech Recognition (ASR), with a particular focus and hands-on experience in recent years on deep learning techniques for streaming end-to-end speech recognition.

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Unite.AI

SEPTEMBER 25, 2023

Initially, the attempts were simple and intuitive, with basic algorithms creating monotonous tunes. However, as technology advanced, so did the complexity and capabilities of AI music generators, paving the way for deep learning and Natural Language Processing (NLP) to play pivotal roles in this tech.

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AI Weekly

NOVEMBER 23, 2023

forbes.com Applied use cases From Data To Diagnosis: A Deep Learning Approach To Glaucoma Detection When the algorithm is implemented in clinical practice, clinicians collect data such as optic disc photographs, visual fields, and intraocular pressure readings from patients and preprocess the data before applying the algorithm to diagnose glaucoma.

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Analytics Vidhya

JANUARY 16, 2024

It’s an information titan, handling billions of queries daily, with a user base that spans across the globe. Its algorithm, founded on keyword matching and user behavior analysis, has established the benchmark for swift […] The post Perplexity AI is going to change the way we search, Beware Google!

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Unite.AI

OCTOBER 7, 2023

But to enable IoE globally, we need technologies that can connect “everything” and understand massive amounts of information to deliver intelligent outcomes. This increased connectedness creates an intelligence ecosystem beyond anything we have encountered.

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Unite.AI

JANUARY 18, 2025

This parallelism is critical for deep learning tasks, where training and inference involve large batches of data. Just as billions of neurons and synapses process information in parallel, an NPU is composed of numerous processing elements capable of simultaneously handling large datasets.

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Unite.AI

NOVEMBER 3, 2023

Below are the most common types of fraud found in the gaming world: Credit Card Theft and Fraudulent Transactions Fraudsters often use stolen credit card information to purchase in-game currency, items, or even full games. They may also inadvertently disclose sensitive information while registering for a bogus tournament.

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AI News

OCTOBER 15, 2024

Machine learning (ML) is revolutionising the way businesses operate, driving innovation, and unlocking new possibilities across industries. By leveraging vast amounts of data and powerful algorithms, ML enables companies to automate processes, make accurate predictions, and uncover hidden patterns to optimise performance.

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