Marktechpost

OCTOBER 20, 2024

While AI has emerged as a powerful tool for materials discovery, the lack of publicly available data and open, pre-trained models has become a major bottleneck. They also present the EquiformerV2 model, a state-of-the-art Graph Neural Network (GNN) trained on the OMat24 dataset, achieving leading results on the Matbench Discovery leaderboard.

Neural Network 113

Neural Network Inference Engine AI AI 113

Marktechpost

OCTOBER 23, 2024

Shallow neural networks are used to map these relationships, so they fail to capture their depth. It may provide avenues for improving NLP applications, which would lead to inspiration for future developments in adaptive AI systems. Words are treated as isolated entities without considering their nested relationships.

NLP 113

NLP Neural Network Natural Language Processing Inference Engine 113

Marktechpost

OCTOBER 23, 2024

The ultimate aim of mechanistic interpretability is to decode neural networks by mapping their internal features and circuits. Two methods to reduce nonlinear error were explored: inference time optimization and SAE outputs from earlier layers, with the latter showing greater error reduction.

Neural Network 109

Neural Network Inference Engine Explainability NLP 109

Marktechpost

OCTOBER 22, 2024

When a model receives an input, it processes it through multiple layers of neural networks, where each layer adjusts the model’s understanding of the task. Activation steering operates by identifying and manipulating the internal layers of the model responsible for instruction-following.

Large Language Models 113

Large Language Models Neural Network Inference Engine AI 113

Unite.AI

JUNE 21, 2024

The field of artificial intelligence (AI) has witnessed remarkable advancements in recent years, and at the heart of it lies the powerful combination of graphics processing units (GPUs) and parallel computing platform. Installation When setting AI development, using the latest drivers and libraries may not always be the best choice.

Deep Learning 130

Deep Learning Neural Network Convolutional Neural Networks Large Language Models 130

Marktechpost

OCTOBER 14, 2024

raising widespread concerns about privacy threats of Deep Neural Networks (DNNs). Additionally, setting up access controls and limiting how often each user can access the data is important for building responsible AI systems, and reducing potential conflicts with people’s private data. Check out the Paper.

Categorization 104

Categorization Neural Network Inference Engine Deep Learning 104

Marktechpost

OCTOBER 21, 2024

The proposed methodology is rooted in the concept of Walk-Jump Sampling, where noise is added to clean data, followed by training a neural network to denoise it, thereby allowing a smooth sampling process. If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

Neural Network 104

Neural Network Inference Engine Machine Learning ML 104

Marktechpost

OCTOBER 17, 2024

Static Embeddings are bags of token embeddings that are summed together to create text embeddings, allowing for lightning-fast embeddings without requiring neural networks. [link] Introduction of Static Embeddings Another major feature is Static Embeddings, a modernized version of traditional word embeddings like GLoVe and word2vec.

Neural Network 104

Neural Network Inference Engine NLP ML 104

Marktechpost

OCTOBER 19, 2024

Inaccurate predictions in these cases can have real-world consequences, such as in engineering designs or scientific simulations where precision is critical. HNNs are particularly effective for systems where energy conservation holds but struggle with systems that violate this principle. If you like our work, you will love our newsletter.

Deep Learning 104

Deep Learning Neural Network Robotics Inference Engine 104

Towards AI

JULY 19, 2023

Last Updated on July 19, 2023 by Editorial Team Author(s): Ricky Costa Originally published on Towards AI. github.com Their core repos consist of SparseML: a toolkit that includes APIs, CLIs, scripts and libraries that apply optimization algorithms such as pruning and quantization to any neural network. The Vision of St.

NLP 98

NLP Neural Network Natural Language Processing BERT 98

Mlearning.ai

MAY 16, 2023

Deployment of deep neural network on mobile phone. (a) Introduction As more and more deep neural networks, like CNNs, Transformers, and Large Language Models (LLMs), generative models, etc., to boost the usages of the deep neural networks in our lives. Local AI Solutions Mlearning.ai 2] Android.

Neural Network 98

Neural Network Convolutional Neural Networks Deep Learning Inference Engine 98

Marktechpost

OCTOBER 15, 2024

XAI, or Explainable AI, brings about a paradigm shift in neural networks that emphasizes the need to explain the decision-making processes of neural networks, which are well-known black boxes. Today, we talk about TDA, which aims to relate a model’s inference from a specific sample to its training data.

Explainability 57

Explainability Explainable AI Python Neural Network 57

Marktechpost

OCTOBER 21, 2024

Artificial intelligence (AI) and machine learning (ML) revolve around building models capable of learning from data to perform tasks like language processing, image recognition, and making predictions. A significant aspect of AI research focuses on neural networks, particularly transformers.

Machine Learning 62

Machine Learning Neural Network Natural Language Processing Inference Engine 62

Marktechpost

OCTOBER 16, 2024

More sophisticated machine learning approaches, such as artificial neural networks (ANNs), may detect complex relationships in data. Furthermore, deep learning techniques like convolutional networks (CNNs) and long short-term memory (LSTM) models are commonly employed due to their ability to analyze temporal and meteorological data.

Machine Learning 67

Machine Learning Neural Network Deep Learning Inference Engine 67

Mlearning.ai

JANUARY 28, 2023

TensorFlow: TensorFlow is an open source library for building neural networks and other deep learning algorithms on top of GPUs. Keras : Keras is a high-level neural network library that makes it easy to develop and deploy deep learning models. How Do I Use These Libraries?

Data Science 52

Data Science Machine Learning ML Python 52

Marktechpost

OCTOBER 18, 2024

Weight averaging, originating from Utans’ work in 1996, has been widely applied in deep neural networks for combining checkpoints, utilizing task-specific information, and parallel training of LLMs. Researchers have explored various approaches to address the challenges of model merging and multitask learning in LLMs.

Large Language Models 62

Large Language Models Neural Network Inference Engine LLM 62

Viso.ai

MAY 24, 2024

Although still under research and development, these models can be a transformative force in the Artificial Intelligence (AI) world. Get ready for a journey in Large Action Models, where AI is not just talking, but taking action. This technique combines learning capabilities and logical reasoning from neural networks and symbolic AI.

Neural Network 52

Neural Network Robotics Automation Explainability 52

Towards AI

JULY 21, 2023

Last Updated on July 21, 2023 by Editorial Team Author(s): Ricky Costa Originally published on Towards AI. github.com Their core repos consist of SparseML: a toolkit that includes APIs, CLIs, scripts and libraries that apply optimization algorithms such as pruning and quantization to any neural network. The Vision of St.

NLP 52

NLP Neural Network Natural Language Processing BERT 52

Mlearning.ai

JUNE 2, 2023

Revolutionising the nature of AI programmability, usability, scalability & compute! In the first part of this blog, we are going to explore how Modular came into existence, who are it’s founding members, and what they have to offer to the AI community. Designed by Canva Have you guys ever heard of Modular?

Inference Engine 52

Inference Engine Python Machine Learning Neural Network 52

Bugra Akyildiz

SEPTEMBER 22, 2024

Skip connections: These are used to facilitate gradient flow in deep SSM architectures, similar to their use in other deep neural networks. Support AI, Search, and other product use cases requiring denormalized data and they made the following key design decisions: Using S3 as the data repository and lake.

Neural Network 59

Neural Network LLM Large Language Models Data Ingestion 59

deepsense.ai

APRIL 25, 2024

In today’s rapidly evolving generative AI world, keeping pace requires more than embracing cutting-edge technology. Tech Stack Tech Stack Below, we provide a quick overview of the project, divided into research and inference sites. Methods and Tools Let’s start with the inference engine for the Small Language Model.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Inference Engine LLM 52

Mlearning.ai

JULY 9, 2023

LLM from a CPU-Optimized (GGML) format: LLaMA.cpp is a C++ library that provides a high-performance inference engine for large language models (LLMs). It is based on the GGML (Graph Neural Network Machine Learning) library, which provides a fast and efficient way to represent and process graphs.

Large Language Models 52

Large Language Models LLM Python Auto-complete 52

Marktechpost

OCTOBER 28, 2024

Deep neural networks, typically fine-tuned foundational models, are widely used in sectors like healthcare, finance, and criminal justice, where biased predictions can have serious societal impacts. Datasets and pre-trained models come with intrinsic biases. If you like our work, you will love our newsletter.

Neural Network 113

Neural Network Inference Engine Machine Learning Automation 113

Marktechpost

OCTOBER 28, 2024

The OCM methodology offers a streamlined approach to estimating covariance by training a neural network to predict the diagonal Hessian, which allows for accurate covariance approximation with minimal computational demands. If you like our work, you will love our newsletter. Don’t Forget to join our 55k+ ML SubReddit.

Neural Network 103

Neural Network Inference Engine AI AI 103