Unite.AI

MARCH 24, 2024

The capacity for an AI to intuitively grasp a task from minimal instruction and then articulate its understanding has remained elusive. This gap in AI capabilities highlights the limitations of existing models. These networks emulate the way human neurons transmit electrical signals, processing information through interconnected nodes.

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Marktechpost

DECEMBER 15, 2023

Complex tasks like text or picture synthesis, segmentation, and classification are being successfully handled with the help of neural networks. However, it can take days or weeks to obtain adequate results from neural network training due to its computing demands. If you like our work, you will love our newsletter.

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Unite.AI

OCTOBER 18, 2024

The 2024 Nobel Prizes have taken many by surprise, as AI researchers are among the distinguished recipients in both Physics and Chemistry. Hopfield received the Nobel Prize in Physics for their foundational work on neural networks. Geoffrey Hinton and John J.

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Marktechpost

FEBRUARY 4, 2024

Meta-learning, a burgeoning field in AI research, has made significant strides in training neural networks to adapt swiftly to new tasks with minimal data. This technique centers on exposing neural networks to diverse tasks, thereby cultivating versatile representations crucial for general problem-solving.

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Marktechpost

OCTOBER 16, 2023

In a recent paper, “Towards Monosemanticity: Decomposing Language Models With Dictionary Learning,” researchers have addressed the challenge of understanding complex neural networks, specifically language models, which are increasingly being used in various applications. Join our AI Channel on Whatsapp.

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Marktechpost

OCTOBER 1, 2023

Researchers have recently developed Temporal Graph Neural Networks (TGNNs) to take advantage of temporal information in dynamic graphs, building on the success of Graph Neural Networks (GNNs) in learning static graph representation. If you like our work, you will love our newsletter.

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AI Weekly

SEPTEMBER 26, 2024

for robotics simulation tech One of the most fundamental breakthroughs at Nvidia has been building processors that power and integrate with highly detailed, compute-intensive graphical simulations, which can be used in a wide range of applications, from games and industrial developments through to AI training.

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Unite.AI

MARCH 10, 2025

He pointed out that OpenAI despite its cutting-edge neural networks is not a model company; its a product company that happens to have fantastic models , underscoring that true advantage comes from building products around the models. This is the crux of the commoditization debate. OpenAIs own strategy reflects this shift.

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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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Marktechpost

OCTOBER 8, 2023

Yes, the field of study is called Neural networks. Researchers at the University of Copenhagen present a graph neural network type of encoding in which the growth of a policy network is controlled by another network running in each neuron. They call it a Neural Developmental Program (NDP).

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Marktechpost

OCTOBER 13, 2023

In the realm of deep learning, the challenge of developing efficient deep neural network (DNN) models that combine high performance with minimal latency across a variety of devices remains. Join our AI Channel on Whatsapp. However, this approach tends to overlook optimizing the search space itself. We are also on WhatsApp.

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Towards AI

JANUARY 29, 2025

Video Generation: AI can generate realistic video content, including deepfakes and animations. Generative AI is powered by advanced machine learning techniques, particularly deep learning and neural networks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

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Marktechpost

FEBRUARY 28, 2025

Traditional MCMC methods frequently struggle with convergence to equilibrium, leading researchers to combine them with non-equilibrium dynamics through techniques like annealed importance sampling (AIS) or sequential Monte Carlo (SMC).

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Marktechpost

DECEMBER 23, 2023

Deep Neural Networks (DNNs) represent a powerful subset of artificial neural networks (ANNs) designed to model complex patterns and correlations within data. These sophisticated networks consist of multiple layers of interconnected nodes, enabling them to learn intricate hierarchical representations.

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Marktechpost

DECEMBER 11, 2023

Moreover, since the models depend on the knowledge of climate scientists to improve equations, parameterizations, and algorithms, NWP forecast accuracy remains the same with additional data. Using historical data, like the ERA5 reanalysis dataset, deep neural networks are trained to forecast future weather conditions.

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Marktechpost

SEPTEMBER 8, 2023

Researchers suggest a new approach to design using heuristic optimization and artificial neural networks to simplify the optimization process drastically. A deep neural network model replaced the 3D electromagnetic simulation of a Si-based MZM. If you like our work, you will love our newsletter.

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AI Weekly

SEPTEMBER 12, 2024

ft.com OpenAI co-founder Sutskever's new safety-focused AI startup SSI raises $1 billion Safe Superintelligence (SSI), newly co-founded by OpenAI's former chief scientist Ilya Sutskever, has raised $1 billion in cash to help develop safe artificial intelligence systems that far surpass human capabilities, company executives told Reuters.

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AI Weekly

DECEMBER 21, 2023

About two-thirds of Australian employees report using generative AI for work. theconversation.com Stanford : What to Expect in AI in 2024 This past year marked major advances in generative AI as terms like ChatGPT and Bard become household names. yahoo.com Research The AI–quantum computing mash-up: will it revolutionize science?

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Marktechpost

DECEMBER 3, 2023

There is a steadily growing list of intriguing properties of neural network (NN) optimization that are not readily explained by classical tools from optimization. Likewise, the research team has varying degrees of understanding of the mechanical causes for each. If you like our work, you will love our newsletter.

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Neural Network Explainability Algorithm AI Research 120

Marktechpost

AUGUST 21, 2023

The results of today’s neural networks in fields as diverse as language, mathematics, and vision are remarkable. These networks, however, typically employ elaborate structures that are resource-intensive to run. Each weight in a typical neural network specifies the link between two neurons.

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AI News

JUNE 28, 2023

Upon the completion of the transaction, the entire MosaicML team – including its renowned research team – is expected to join Databricks. MosaicML’s machine learning and neural networks experts are at the forefront of AI research, striving to enhance model training efficiency.

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Marktechpost

DECEMBER 16, 2023

Trained on a dataset from six UK hospitals, the system utilizes neural networks, X-Raydar and X-Raydar-NLP, for classifying common chest X-ray findings from images and their free-text reports. An NLP algorithm, X-Raydar-NLP, was trained on 23,230 manually annotated reports to extract labels.

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Marktechpost

AUGUST 31, 2024

Deep neural network training can be sped up by Fully Quantised Training (FQT), which transforms activations, weights, and gradients into lower precision formats. Researchers have been studying the viability of 1-bit FQT in an endeavor to explore these constraints. Check out the Paper.

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The MLOps Blog

MARCH 13, 2025

In his famous blog post Artificial Intelligence The Revolution Hasnt Happened Yet , Michael Jordan (the AI researcher, not the one you probably thought of first) tells a story about how he might have almost lost his unborn daughter due to a faulty AI prediction. It is 08:30 am, and you have to be at work by 09:00.

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AI Weekly

JULY 13, 2023

theguardian.com Sarah Silverman sues OpenAI and Meta claiming AI training infringed copyright The US comedian and author Sarah Silverman is suing the ChatGPT developer OpenAI and Mark Zuckerberg’s Meta for copyright infringement over claims that their artificial intelligence models were trained on her work without permission.

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AI Weekly

SEPTEMBER 21, 2023

pitneybowes.com In The News How Google taught AI to doubt itself Today let’s talk about an advance in Bard, Google’s answer to ChatGPT, and how it addresses one of the most pressing problems with today’s chatbots: their tendency to make things up. [Get your FREE eBook.] You can also subscribe via email.

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AI Weekly

FEBRUARY 20, 2025

nature.com A robust and adaptive controller for ballbots In a recent study, a team has proposed a novel proportional integral derivative controller that, in combination with radial basis function neural network, robustly controls ballbot motion. You can also subscribe via email.

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AssemblyAI

MAY 3, 2023

Thanks to the widespread adoption of ChatGPT, millions of people are now using Conversational AI tools in their daily lives. With these fairly complex algorithms often being described as “giant black boxes” in news and media, a demand for clear and accessible resources is surging.

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AI Weekly

JANUARY 25, 2024

Rapid AI innovation has fueled future predictions, as well, including everything from friendly home robots to artificial general intelligence (AGI) within a decade. Join the AI conversation and transform your advertising strategy with AI weekly sponsorship This RSS feed is published on [link]. decrypt.co

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Marktechpost

DECEMBER 27, 2024

Achieving this efficiently, without retraining the entire model, has been a key focus, particularly for complex models like deep neural networks. All credit for this research goes to the researchers of this project. Trending: LG AI Research Releases EXAONE 3.5: Dont Forget to join our 60k+ ML SubReddit.

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Marktechpost

DECEMBER 13, 2024

Neural networks have become foundational tools in computer vision, NLP, and many other fields, offering capabilities to model and predict complex patterns. This understanding is essential for designing more efficient training algorithms and enhancing the interpretability and robustness of neural networks.

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Marktechpost

DECEMBER 12, 2023

Numerous studies have been put forth to improve the generation quality by applying multiple optimization stages, concurrently optimizing the diffusion before the 3D representation, formulating the score distillation algorithm with greater precision, or improving the specifics of the entire pipeline.

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Marktechpost

FEBRUARY 1, 2025

Classical vs. Modern Approaches Classical Symbolic Reasoning Historically, AI researchers focused heavily on symbolic reasoning, where knowledge is encoded as rules or facts in a symbolic language. Some of the most prominent RL algorithms include: Q-Learning: Agents learn a value function Q(s, a) , where s state and a action.

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Marktechpost

AUGUST 7, 2023

With its innovative approach to T2I personalization, Perfusion has opened new avenues for creativity and expression, offering a glimpse into a future where human input and advanced algorithms harmoniously coexist. All Credit For This Research Goes To the Researchers on This Project. Check out the Paper and Project Page.

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Unite.AI

FEBRUARY 16, 2024

It has been the guiding vision of AI research since the earliest days and remains its most divisive idea. Some AI enthusiasts believe that AGI is inevitable and imminent and will lead to a new technological and social progress era. AGI is not a new concept.

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Pickl AI

SEPTEMBER 3, 2024

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. Introduction Artificial Neural Network (ANNs) have emerged as a cornerstone of Artificial Intelligence and Machine Learning , revolutionising how computers process information and learn from data.

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IBM Journey to AI blog

AUGUST 13, 2024

Where it all started During the second half of the 20 th century, IBM researchers used popular games such as checkers and backgammon to train some of the earliest neural networks, developing technologies that would become the basis for 21 st -century AI.

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