Marktechpost

MAY 2, 2024

This study’s research area is artificial intelligence (AI) and machine learning, specifically focusing on neural networks that can understand binary code. The research addresses a significant problem: understanding what binary code does is difficult because it requires specialized skills and knowledge. With over 1.1

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Unite.AI

JUNE 15, 2023

Typically, professionals working in metropolitan areas or tech hubs command higher salaries than those in smaller cities or rural areas. Keeping up with NLP research and advancements: The field of NLP is constantly evolving, and it's crucial for NLP Engineers to stay current with the latest research, techniques, and tools.

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Unite.AI

DECEMBER 14, 2023

This revelation calls into question the robustness of AI applications in critical areas and highlights the need for a deeper understanding of these vulnerabilities. In proof-of-concept testing, QuadAttac K was used to evaluate four widely used neural networks. It then manipulates the data to test the AI's vulnerability.

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IBM Journey to AI blog

APRIL 18, 2024

A world where computer minds pilot self-driving cars, delve into complex scientific research, provide personalized customer service and even explore the unknown. Researchers are actively exploring artificial consciousness, general problem-solving and common-sense reasoning within machines. Regardless, these are examples of narrow AI.

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Marktechpost

MARCH 26, 2024

Graph neural networks (GNNs) have revolutionized how researchers analyze and learn from data structured in complex networks. These models capture the intricate relationships inherent in graphs, which are omnipresent in social networks, molecular structures, and communication networks, to name a few areas.

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Marktechpost

APRIL 24, 2024

It will cover a brief history of deep RL, a basic theoretical explanation of deep RL networks, state-of-the-art deep RL algorithms, major application areas, and the future research scope in the field. In 2017, DeepMind researchers introduced a generalized version of AlphaGo, which they named AlphaZero.

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Marktechpost

DECEMBER 5, 2023

Researchers at the University of Geneva have made a groundbreaking stride in healthcare technology. They used Graph Neural Networks (GNNs) in healthcare to detect antimicrobial resistance (AMR) and multidrug-resistant (MDR) Enterobacteriaceae colonization. Researchers found the GNN model demonstrates a performance range of 0.91

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AI Weekly

MARCH 7, 2024

They are used in medicine, research, business, law and a variety of other areas. They are used in medicine, research, business, law and a variety of other areas. japantimes.co.jp theconversation.com Robotics AI Robotics Market to Reach US$39 Billion by 2028 The AI Robotics market is expected to rise from US$11.89

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Unite.AI

JANUARY 26, 2024

On complementary side wrt to the software architect side; to enable faster deployment of LLMs researchers have proposed serverless inference systems. Downloading checkpoints from remote storage is time-consuming, taking over 20 seconds even with optimized networks. This adds significant delays beyond container startup time.

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Large Language Models LLM Software Architect Chatbots 241

Marktechpost

FEBRUARY 12, 2024

Deep convolutional neural networks (DCNNs) have been a game-changer for several computer vision tasks. Model quantization, efficient neural architecture search, compact network design, knowledge distillation, and tensor decomposition are among the most popular DNN compression and acceleration approaches.

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Convolutional Neural Networks Neural Network Computer Vision Algorithm 133

Marktechpost

NOVEMBER 25, 2023

Addressing this, Jason Eshraghian from UC Santa Cruz developed snnTorch, an open-source Python library implementing spiking neural networks, drawing inspiration from the brain’s remarkable efficiency in processing data. Traditional neural networks lack the elegance of the brain’s processing mechanisms.

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Neural Network Python Deep Learning Artificial Intelligence 129

Towards AI

APRIL 10, 2024

This analysis examines the contributions of LLMs to diverse areas such as time series prediction, genomics, recommender systems, and strategic scenario planning, showcasing their versatility and innovative potential. From research to projects and ideas. It does this by converting time… Read the full blog for free on Medium.

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Neural Network Large Language Models Data Analysis ChatGPT 114

Marktechpost

OCTOBER 8, 2023

The area is impacting all spheres. By utilizing finely developed neural network architectures, we have models that are distinguished by extraordinary accuracy within their respective sectors. Despite their accurate performance, we must still fully understand how these neural networks function. Check out the Paper.

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Deep Learning Neural Network Explainability Artificial Intelligence 140

AI Weekly

OCTOBER 26, 2023

siliconangle.com A Primer on Generative AI’s Alphabet Soup of Acronyms Deep learning (DL) is a subfield of machine learning that focuses on training artificial neural networks (ANNs) with multiple layers (deep neural networks) to learn and make predictions from data. androidguys.com Ethics Should we be afraid of AI?

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Neural Network Convolutional Neural Networks Robotics Deep Learning 197

Marktechpost

DECEMBER 30, 2023

A new area called Scientific Machine Learning (SciML), which combines classic modeling methods based on partial differential equations (PDEs) with machine learning’s approximation capabilities, has recently been in the talks. SciML consists of three primary subfields, which include PDE solvers, PDE discovery, and operator learning.

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Marktechpost

MARCH 4, 2024

The area has advanced quickly in both theoretical development and practical applications, from the early days of Recurrent Neural Networks (RNNs) to the current dominance of Transformer models. To address these issues, researchers from Google DeepMind have introduced two unique models, Hawk and Griffin.

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Machine Learning Neural Network Natural Language Processing Deep Learning 126

Unite.AI

FEBRUARY 8, 2024

This importance has made object segmentation a consistently hot research topic, with significant work done in areas like instance segmentation, semantic segmentation, and panoptic segmentation. The TinySAM framework distills the student network in an end to end manner under the supervision of the teacher network from different stages.

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Marktechpost

OCTOBER 24, 2023

It introduces five key research areas in lifelong learning for decision-making (LLDM) and offers a procedural task generation pipeline with four task suites comprising 130 tasks. Their research introduces LIBERO, a benchmark focusing on lifelong learning in decision-making for robot manipulation.

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Robotics BERT Algorithm AI Researcher 124

Marktechpost

OCTOBER 8, 2023

The brain is hierarchically organized, with lower-level sensory processing areas sending information to higher-level cognitive and decision-making regions. The brain processes information in parallel, with different regions and networks simultaneously working on various aspects of perception, cognition, and motor control.

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Neural Network Automation Deep Learning Algorithm 129

AI Weekly

JANUARY 18, 2024

Connect with 5,000+ attendees including industry leaders, heads of state, entrepreneurs and researchers to explore the next wave of transformative AI technologies. Connect with 5,000+ attendees including industry leaders, heads of state, entrepreneurs and researchers to explore the next wave of transformative AI technologies.

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Robotics Artificial Intelligence Artificial Intelligence Machine Learning 207

IBM Journey to AI blog

JANUARY 15, 2024

This technology excels at applying foundation models, which are large neural networks trained on extensive unlabeled data and fine-tuned for various tasks. It can empower government workers with more powerful tools for answering questions and conducting research.

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Unite.AI

DECEMBER 11, 2023

Cross-modal Attention Network: This network is the heart of Gemini. Multimodal Decoder: This module utilizes the enriched representations generated by the cross-modal attention network to perform various tasks, such as image captioning, text-to-image generation, and code generation.

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Marktechpost

FEBRUARY 22, 2024

In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet. All credit for this research goes to the researchers of this project.

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Marktechpost

JANUARY 11, 2024

This one-size-fits-all methodology often degrades high-quality areas while attempting to enhance lower-quality regions, presenting a nuanced challenge in the quest for optimal image quality. Based on this assessment, the model applies one of three refining pipelines, each meticulously designed for specific quality areas.

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Neural Network AI AI Algorithm 119

Unite.AI

MARCH 22, 2024

By integrating digital twins into clinical trials, Unlearn is able to accelerate clinical research and help bring life-saving new treatments to patients in need. Deep neural networks have given us a new set of tools for complex systems, and automation is helping create the large-scale biological datasets required.

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Neural Network Machine Learning AI Modeling Explainability 182

Towards AI

FEBRUARY 16, 2024

Image adapted from Adobe Stock Machine learning is becoming a significant tool in the field of chemistry, providing new opportunities in various areas such as drug discovery and materials science. From research to projects and ideas. Recently, the combination of machine learning and chemistry has made significant progress.

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Machine Learning Neural Network Explainability Algorithm 100

AI Weekly

JANUARY 25, 2024

Connect with 5,000+ attendees including industry leaders, heads of state, entrepreneurs and researchers to explore the next wave of transformative AI technologies. Connect with 5,000+ attendees including industry leaders, heads of state, entrepreneurs and researchers to explore the next wave of transformative AI technologies.

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Robotics Artificial Intelligence Artificial Intelligence Neural Network 222

Marktechpost

OCTOBER 22, 2023

In the pursuit of replicating the complex workings of the human sensory systems, researchers in neuroscience and artificial intelligence face a persistent challenge: the disparity in invariances between computational models and human perception. All Credit For This Research Goes To the Researchers on This Project.

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Neural Network Artificial Intelligence Artificial Intelligence AI 142

Unite.AI

FEBRUARY 16, 2024

It has been the guiding vision of AI research since the earliest days and remains its most divisive idea. Various research directions and paradigms have been proposed and explored in the pursuit of AGI, each with strengths and limitations. AGI is not a new concept.

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NVIDIA

MAY 12, 2024

From planes and trains to bridges, silicon chips and pharmaceuticals — testing and improving products in simulation saves researchers and developers billions of dollars. AI for Scientific Computing New Blackwell accelerators and networking will deliver leaps in performance for advanced simulation.

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Large Language Models Algorithm LLM Data Science 84

Marktechpost

DECEMBER 30, 2023

A new research paper from CSIRO, Australia, addresses these challenges by introducing a novel solution, ML-SEISMIC, a physics-informed deep neural network designed to align stress orientation data with an elastic model autonomously. The research team introduces ML-SEISMIC as a groundbreaking alternative. Check out the Paper.

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Marktechpost

APRIL 26, 2024

Key algorithms include: Spiking Neural Networks (SNNs): Unlike traditional neural networks, which process continuous data, SNNs manage binary events or “spikes.” Neuromodulation Techniques involve modulating neural activity through mechanisms that alter network dynamics, improving learning efficiency and adaptability.

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Algorithm Neural Network Robotics Artificial Intelligence 122

Marktechpost

DECEMBER 1, 2023

Computer vision, NLP, and other domains have seen remarkable success with deep machine learning (ML) approaches based on deep neural networks (NNs). Bayesian networks, Boltzmann machines, and other probabilistic ML models are considered “white boxes” since they are inherently interpretable.

Machine Learning 122

Machine Learning Neural Network Computer Vision ML 122

Marktechpost

DECEMBER 7, 2023

The subfields of human NVS have the potential to significantly contribute to real-time efficiency and consistent 3D appearances in areas such as holographic communication, stage performances, and 3D/4D immersive scene capture for sports broadcasting. The researchers believe that this difficulty can be solved by using time-related data.

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Marktechpost

APRIL 6, 2024

Understanding Transformers The transformer model was introduced in the research paper “ Attention is All You Need ” by Vaswani et al. in 2017, marking a departure from the previous reliance on recurrent neural networks (RNNs) and convolutional neural networks (CNNs) for processing sequential data.

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Large Language Models NLP Convolutional Neural Networks Neural Network 124

Marktechpost

DECEMBER 26, 2023

This research niche is crucial as it promises to bridge the gap between current robotic capabilities and the nuanced dexterity found in human actions. A central challenge in this area is developing models that can accurately indicate the outcomes of robotic actions in dynamic environments. Check out the Paper.

Neural Network 111

Neural Network Robotics Automation AI Researcher 111

IBM Journey to AI blog

MAY 6, 2024

Yet, clinical trial professionals across the globe grapple with notable challenges in these areas. Additionally, generative adversarial networks (GANs) can be used to simulate real recruitment scenarios, further optimizing protocol design. Successful clinical studies hinge on efficiently recruiting and retaining diverse participants.

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