Towards AI

DECEMBER 16, 2024

Kernel Arnold Networks (KAN) Summary: Kernel Arnold Networks (KAN) propose a new way of representing and processing data, challenging traditional deep neural networks. Key Contributions: Unique combination of kernel methods with deep learning principles. Efficient handling of non-linear relationships.

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Unite.AI

SEPTEMBER 18, 2023

On the other hand, AI or Artificial Intelligence is a branch in modern science that focuses on developing machines that are capable of decision-making, and can simulate autonomous thinking comparable to a human’s ability. Deep learning frameworks can be classified into two categories: Supervised learning, and Unsupervised learning.

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Pickl AI

DECEMBER 29, 2024

Structured for clarity, the blog breaks down complex topics into actionable insights, ensuring a seamless learning journey for readers. Key Takeaways Mathematics is crucial for optimising AI algorithms and models. Linear algebra helps in data manipulation and neural network training.

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NVIDIA

JANUARY 6, 2025

As a result, were able to render at incredibly high performance, because AI does a lot less computation. RTX Neural Shaders use small neural networks to improve textures, materials and lighting in real-time gameplay. Inside the company, it was called Project DIGITS deep learning GPU intelligence training system.

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Marktechpost

MARCH 28, 2024

One way an individual can stay updated with the latest trends is by reading books on various facets of AI. Following are the top AI books one should read in 2024. It also provides information on the different deep learning techniques used in various industrial applications.

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NVIDIA

OCTOBER 26, 2023

Researchers are taking deep learning for a deep dive, literally. The Woods Hole Oceanographic Institution (WHOI) Autonomous Robotics and Perception Laboratory ( WARPLab ) and MIT are developing a robot for studying coral reefs and their ecosystems. candidate at MIT and AI developer at WARPLab.

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Unite.AI

OCTOBER 22, 2024

Understanding Computational Complexity in AI The performance of AI models depends heavily on computational complexity. In AI, particularly in deep learning , this often means dealing with a rapidly increasing number of computations as models grow in size and handle larger datasets.

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IBM Journey to AI blog

JANUARY 10, 2024

But even with the myriad benefits of AI, it does have noteworthy disadvantages when compared to traditional programming methods. AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended.

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Unite.AI

APRIL 9, 2024

Composite AI is a cutting-edge approach to holistically tackling complex business problems. These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Decision trees and rule-based models like CART and C4.5

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IBM Journey to AI blog

DECEMBER 15, 2023

Additionally, the vendor neutrality of open-source AI ensures organizations aren’t tied to a specific vendor. While open-source AI offers enticing possibilities, its free accessibility poses risks that organizations must navigate carefully.

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NVIDIA

MARCH 18, 2024

At its booth, NVIDIA will showcase how it’s building automotive assistants to enhance driver safety, security and comfort through enhanced perception, understanding and generative capabilities powered by deep learning and transformer models.

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Marktechpost

JUNE 28, 2024

One way an individual can stay updated with the latest trends is by reading books on various facets of AI. Following are the top AI books one should read in 2024. It also provides information on the different deep learning techniques used in various industrial applications.

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Unite.AI

JUNE 21, 2024

The Rise of CUDA-Accelerated AI Frameworks GPU-accelerated deep learning has been fueled by the development of popular AI frameworks that leverage CUDA for efficient computation. Installation When setting AI development, using the latest drivers and libraries may not always be the best choice.

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Marktechpost

NOVEMBER 16, 2024

One way an individual can stay updated with the latest trends is by reading books on various facets of AI. Following are the top AI books one should read in 2024. It also provides information on the different deep learning techniques used in various industrial applications.

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NVIDIA

OCTOBER 11, 2024

The parallel power that transformed gaming graphics caught the attention of researchers, who realized these GPUs could also unlock massive computational potential in AI, enabling breakthroughs far beyond the gaming world. Traditional CPUs, designed for sequential tasks, couldn’t efficiently handle this workload.

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Marktechpost

JUNE 14, 2024

Its AI courses, taught by leading experts, offer comprehensive and practical knowledge, equipping students with the skills to tackle real-world challenges and drive future AI developments. This beginner-friendly program, developed by DeepLearning.AI

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Unite.AI

DECEMBER 1, 2023

Exploring the Techniques of LIME and SHAP Interpretability in machine learning (ML) and deep learning (DL) models helps us see into opaque inner workings of these advanced models. Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) are two such mainstream interpretability techniques.

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NVIDIA

FEBRUARY 11, 2025

They said transformer models , large language models (LLMs), vision language models (VLMs) and other neural networks still being built are part of an important new category they dubbed foundation models. Earlier neural networks were narrowly tuned for specific tasks. Trained on 355,000 videos and 2.8

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Unite.AI

JULY 25, 2024

The 1990s saw significant improvements in statistical machine translation as models learned from vast amounts of bilingual data, leading to better translations. A significant breakthrough came with neural networks and deep learning. IBM's Model 1 and Model 2 laid the groundwork for advanced systems.

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Unite.AI

MARCH 15, 2024

The main reason it's so popular is its unmatched capability for accelerating complex mathematical computations, crucial for deep learning. Additionally, it offers a rich ecosystem like cuDNN for deep neural networks, enhancing performance and ease of use.

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Kavita Ganesan

JANUARY 27, 2022

This is a guest post from Andrew Ferlitsch, author of Deep Learning Patterns and Practices. It provides an introduction to deep neural networks in Python. Andrew is an expert on computer vision, deep learning, and operationalizing ML in production at Google Cloud AI Developer Relations.

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Viso.ai

DECEMBER 17, 2024

PaddlePaddle (PArallel Distributed Deep LEarning), is a deep learning open-source platform. It was developed by the Chinese tech giant Baidu. It is China’s very first independent R&D deep learning platform. PaddlePaddle had initially been developed for Baidu’s internal operations.

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Marktechpost

OCTOBER 8, 2024

Additionally, the scarcity of annotated speech data and the computational cost associated with large-scale speech models further complicate the development of accurate and efficient speech processing systems. Current methods for speech and audio processing rely on various machine learning and deep learning models.

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Viso.ai

DECEMBER 20, 2023

Huawei’s Mindspore is an open-source deep learning framework for training and inference written in C++. license, MindSpore AI allows users to use, modify, and distribute the software. MindSpore offers a comprehensive developer platform to develop, deploy, and scale artificial intelligence models. Book a demo.

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ODSC - Open Data Science

MARCH 12, 2025

20212024: Interest declined as deep learning and pre-trained models took over, automating many tasks previously handled by classical ML techniques. While traditional machine learning remains fundamental, its dominance has waned in the face of deep learning and automated machine learning (AutoML).

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Unite.AI

JANUARY 12, 2024

Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones.

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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. Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others.

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Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

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Unite.AI

DECEMBER 27, 2023

Another breakthrough is the rise of generative language models powered by deep learning algorithms. These innovations have been, in fact, the foundation for the AI developments we witnessed recently. OpenAI's GPT-4 stands as a state-of-the-art generative language model, boasting an impressive over 1.7

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PyImageSearch

SEPTEMBER 23, 2024

Home Table of Contents Deploying a Vision Transformer Deep Learning Model with FastAPI in Python What Is FastAPI? You’ll learn how to structure your project for efficient model serving, implement robust testing strategies with PyTest, and manage dependencies to ensure a smooth deployment process. Testing main.py Testing main.py

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Unite.AI

AUGUST 27, 2024

The choice of programming language in Artificial Intelligence (AI) development plays a vital role in determining the efficiency and success of a project. These languages impact everything from the performance and scalability of AI systems to the speed at which solutions can be developed and deployed.

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Marktechpost

APRIL 28, 2024

It covers various topics like graph search algorithms, classification, optimization, machine learning, and large language models with the help of hands-on projects, allowing the students to incorporate them into their own Python programs. AI For Everyone “AI For Everyone” has been designed by DeepLearning.AI

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Towards AI

JULY 20, 2023

Oh and by the way, Maybe… the universe is just a giant neural network… ?‍♂️ ‍♂️ The Universe Might Be One Big Neural Network, Study Finds One scientist says the universe is a giant neural net. In machine learning and AI development, the aspects of data labeling are essential. Repo Cypher ?‍?

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NVIDIA

JANUARY 21, 2025

Its built using the NVIDIA Jetson edge AI platform, NVIDIA accelerated computing and the NVIDIA Metropolis vision AI developer stack. With NVIDIA accelerated computing, we achieved a 3x speedup in AI training and doubled AI Mobilitys energy efficiency, said Uriel Katz, cofounder and chief technology officer of NoTraffic.

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IBM Journey to AI blog

APRIL 18, 2024

The skills gap in gen AI development is a significant hurdle. Startups offering tools that simplify in-house gen AI development will likely see faster adoption due to the difficulty of acquiring the right talent within enterprises.

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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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Marktechpost

OCTOBER 7, 2024

Studies have shown that benign interpolation and double descent are not limited to deep learning but also occur in simpler models like kernel methods and linear regression. Some researchers have revisited the bias-variance tradeoff, noting its absence in deep neural networks and proposing updated decompositions of prediction error.

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