Unite.AI

MARCH 19, 2025

While no AI today is definitively conscious, some researchers believe that advanced neural networks , neuromorphic computing , deep reinforcement learning (DRL), and large language models (LLMs) could lead to AI systems that at least simulate self-awareness.

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Unite.AI

MARCH 24, 2024

Central to this advancement in NLP is the development of artificial neural networks, which draw inspiration from the biological neurons in the human brain. These networks emulate the way human neurons transmit electrical signals, processing information through interconnected nodes.

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AI Weekly

OCTOBER 26, 2023

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics. voxeurop.eu

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Marktechpost

SEPTEMBER 3, 2023

Credit assignment in neural networks for correcting global output mistakes has been determined using many synaptic plasticity rules in natural neural networks. Methods of biological neuromodulation have inspired several plasticity algorithms in models of neural networks.

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Marktechpost

OCTOBER 1, 2023

Both spatial and temporal information are crucial in spatial-temporal applications like traffic and weather forecasting. Researchers have created Memory-based Temporal Graph Neural Networks (M-TGNNs) that store node-level memory vectors to summarize independent node history to make up for the lost history.

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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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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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Marktechpost

OCTOBER 28, 2024

It’s a great way to explore AI’s capabilities and see how these technologies can be applied to real-world problems. This platform provides a valuable opportunity to understand the potential of AI in natural language processing. It’s a great tool for beginners wanting to start with machine learning.

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Unite.AI

NOVEMBER 25, 2023

By integrating these constraints, the AI not only mirrors aspects of human intelligence but also unravels the intricate balance between resource expenditure and information processing efficiency. More intriguing, however, was the shift in how individual nodes processed information.

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Marktechpost

DECEMBER 19, 2023

A new AI research introduces TorchExplorer, a novel AI tool designed for researchers working with unconventional neural network architectures, which provides an interactive and insightful exploration of network layers.

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Unite.AI

MARCH 2, 2025

Artificial Intelligence (AI) is evolving at an unprecedented pace, with large-scale models reaching new levels of intelligence and capability. From early neural networks to todays advanced architectures like GPT-4 , LLaMA , and other Large Language Models (LLMs) , AI is transforming our interaction with technology.

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Marktechpost

JULY 7, 2024

Artificial neural networks (ANNs) traditionally lack the adaptability and plasticity seen in biological neural networks. The inability of ANNs to continuously adapt to new information and changing conditions hinders their effectiveness in real-time applications such as robotics and adaptive systems.

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Marktechpost

DECEMBER 17, 2023

Neural networks, the marvels of modern computation, encounter a significant hurdle when confronted with tabular data featuring heterogeneous columns. The essence of this challenge lies in the networks’ inability to handle diverse data structures within these tables effectively.

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Marktechpost

SEPTEMBER 15, 2023

The traditional theory of how neural networks learn and generalize is put to the test by the occurrence of grokking in neural networks. This behavior is basically grokking in neural networks. Generalizing Solution: With this approach, the neural network is well-suited to generalizing to new data.

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AI Weekly

NOVEMBER 23, 2023

In light of the ongoing excitement in OpenAI leadership musical chairs over the last week, the topic of AI ethics has never been more critical and public — especially highlighting the need for broader discourse on the topic, rather than the self-sealing group-think that can occur in small, powerful groups. singularitynet.io

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Unite.AI

FEBRUARY 19, 2025

It involves identifying and correcting inconsistencies, generating novel insights rather than just providing information, making decisions in ambiguous situations, and engaging in causal understanding and counterfactual thinking like What if? Reasoning is the process of deriving new conclusions from given premises using logic and inference.

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Marktechpost

NOVEMBER 26, 2023

Neural network architectures, particularly created and trained for few-shot knowledge the ability to learn a desired behavior from a small number of examples, were the first to exhibit this capability. Since then, a substantial amount of research has examined or documented instances of ICL.

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Marktechpost

JANUARY 13, 2024

These documents, often in PDF or image formats, present a complex interplay of text, layout, and visual elements, necessitating innovative approaches for accurate information extraction. Researchers at JPMorgan AI Research and the Dartmouth College Hanover have innovated a novel framework named ‘DocGraphLM’ to bridge this gap.

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AI Weekly

AUGUST 10, 2023

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Marktechpost

SEPTEMBER 26, 2023

Microsoft researchers propose a groundbreaking solution to these challenges in their recent “Neural Graphical Models” paper presented at the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2023). The dataset also included information on infant mortality.

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AI Weekly

JANUARY 2, 2025

In the last year, AI has also been associated with the latest technology revolution for generative AI, large language models, and solutions that promise to change the way we do work, process information and interface with electronic technology in general. moderndiplomacy.eu decrypt.co You can also subscribe via email.

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Marktechpost

JULY 24, 2023

With the advent of Machine Learning (ML) and Deep Learning (DL), image and video editing have been progressively studied through several neural network architectures. The input to the decomposition network is composed by a video and a rough segmentation mask for the object of interest frame by frame (left, yellow box).

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Marktechpost

DECEMBER 7, 2023

Researchers contend that new risks, such as scalable disinformation, manipulation, fraud, election tampering, or the speculative risk of loss of control, arise from the potential for models to be deceptive (which they define as “the systematic inducement of false beliefs in the pursuit of some outcome other than the truth”).

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Marktechpost

JANUARY 3, 2024

The task is inherently complex due to the need for more information about unseen aspects of the object. Historically, neural 3D reconstruction methods relied on multiple images, requiring consistent views, appearances, and accurate camera parameters. If you like our work, you will love our newsletter.

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Marktechpost

DECEMBER 16, 2023

” This innovative code, which simulates spiking neural networks inspired by the brain’s efficient data processing methods, originates from the efforts of a team at UC Santa Cruz. This publication offers candid insights into the convergence of neuroscience principles and deep learning methodologies.

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Marktechpost

DECEMBER 19, 2023

Natural language processing, conversational AI, time series analysis, and indirect sequential formats (such as pictures and graphs) are common examples of the complicated sequential data processing jobs involved in these. Recurrent Neural Networks (RNNs) and Transformers are the most common methods; each has advantages and disadvantages.

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AssemblyAI

MAY 3, 2023

Effective methods allowing for better control, or steerability , of large-scale AI systems are currently in extremely high demand in the world of AI research. Artificial neural networks consist of interconnected layers of nodes, or “neurons” which work together to process and learn from data.

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Unite.AI

MAY 6, 2024

Unlike many traditional AI models that depend solely on neural networks , LAMs utilize a hybrid approach combining neuro-symbolic programming. This integration of symbolic programming aids in logical reasoning and planning, while neural networks contribute to recognizing complex sensory patterns.

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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. The discipline of data science is evolving due to the rise of deep neural networks (DNNs).

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AI Weekly

JULY 20, 2023

In the News Top 10 AI Tools Cooler Than ChatGPT For our list of AI tools cooler than ChatGPT, we conducted extensive research and considered various factors such as performance, versatility, innovation, user-friendliness, integration, and industry impact. readwrite.com Sponsor Your AI investing Co-Pilot With Pluto you can: ?

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AI Weekly

JULY 13, 2023

In the News Elon Musk unveils new AI company set to rival ChatGPT Elon Musk, who has hinted for months that he wants to build an alternative to the popular ChatGPT artificial intelligence chatbot, announced the formation of what he’s calling xAI, whose goal is to “understand the true nature of the universe.” Powered by pluto.fi theage.com.au

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Marktechpost

NOVEMBER 21, 2023

Their pioneering breakthrough, named Senseiver, showcases a neural network that achieves a remarkable feat: representing extensive data with minimal computational resources. The team developed a neural network that allows them to represent a large system in a very compact way. Check out the Paper and Reference Article.

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Towards AI

JANUARY 22, 2025

Setting the Stage: Why Augmentation Matters Imagine youre chatting with an LLM about complex topics like medical research or historical events. Despite its vast training, it occasionally hallucinates producing incorrect or fabricated information. Generates responses by synthesizing the retrieved information.

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Marktechpost

SEPTEMBER 8, 2023

QPI derives information about the refractive index and thickness of the sample by evaluating the phase shifts that light undergoes when interacting with a specimen. The post UCLA Researchers Introduce a Multispectral QPI System Designed Based on a Broadband Diffractive Optical Neural Network appeared first on MarkTechPost.

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Marktechpost

JANUARY 13, 2024

To fill this gap, a new study by MBZUAI and Meta AI Research investigates model characteristics beyond ImageNet correctness. The researchers examine four top models in computer vision: ConvNeXt, which stands for ConvNet, and Vision Transformer (ViT), all trained using supervised and CLIP methods.

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Marktechpost

DECEMBER 25, 2023

One of the major issues with CDI, though, is the phase retrieval problem, where the detectors fail to record the phase of the diffracted wave, leading to information loss. A considerable amount of research has been done to address this problem, focusing mainly on using artificial neural networks.

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AI Weekly

FEBRUARY 20, 2025

Usage is still growing at a rapid pace as the AI developer behind the AI chatbot, ChatGPT, only had 300 million users in December 2024. techcrunch.com Applied use cases What is Perplexity Deep Research, and how do you use it? Perplexity promises its Perplexity Deep Research can deliver the information you need.

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