Towards AI

JANUARY 29, 2025

Along the way, expect a healthy dose of tea-fueled humor, cultural references, and some personal tales from my own adventures in AI research. Now, lets meet our first knight: Scaled-Up Deep Learning the tech equivalent of supersize me. Larger neural networks with trillions of parameters are like massive libraries.

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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

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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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

FEBRUARY 28, 2024

Parameter generation, distinct from visual generation, aims to create neural network parameters for task performance. Researchers from the National University of Singapore, University of California, Berkeley, and Meta AI Research have proposed neural network diffusion , a novel approach to parameter generation.

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AI Weekly

NOVEMBER 23, 2023

Connect with industry leaders, heads of state, entrepreneurs and researchers to explore the next wave of transformative AI technologies. igamingbusiness.com Ethics What’s the smart way of moving forward with AI? Be ready for a twofer. singularitynet.io

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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

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

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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Unite.AI

SEPTEMBER 29, 2024

Deepgram Deepgram is a cutting-edge speech recognition and transcription platform that leverages advanced AI and deep learning technologies to provide highly accurate and scalable speech-to-text solutions. The API offers a selection of preset voices and supports two model variants optimized for different use cases.

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Marktechpost

SEPTEMBER 1, 2023

Artificial intelligence’s allure has long been shrouded in mystique, especially within the enigmatic realm of deep learning. These intricate neural networks, with their complex processes and hidden layers, have captivated researchers and practitioners while obscuring their inner workings.

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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. If you like our work, you will love our newsletter. We are also on WhatsApp.

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AI Weekly

AUGUST 10, 2023

wired.com 47% of Warren Buffett's $375 Billion Portfolio Is Invested in 3 AI Stocks If you've ever wondered why Wall Street professionals and everyday investors pay so much attention to Berkshire Hathaway (BRK.A 1.41%) (BRK.B 1.57%) CEO Warren Buffett, just take a closer look at his track record since taking the reins in 1965.

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Marktechpost

OCTOBER 8, 2023

Can we adapt these hierarchy organization and parallel processing techniques in deep learning? Yes, the field of study is called Neural networks. This provides an advantage to NDP as it can operate upon any neural network of arbitrary size or architecture. Join our AI Channel on Whatsapp.

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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

SEPTEMBER 10, 2023

Researchers think that high-speed testing using Deep Learning models can help us understand these effects better and speed up catalyst development. The way a catalyst’s surface is shaped matters for certain chemical reactions due to various properties of the catalyst, which we study in Surface Chemistry.

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Marktechpost

JULY 2, 2023

The exponentially expanding scale of deep learning models is a major force in advancing the state-of-the-art and a source of growing worry over the energy consumption, speed, and, therefore, feasibility of massive-scale deep learning. What happens if you run a Transformer model with an optical neural network?*

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Marktechpost

JANUARY 4, 2024

Qu Kun from the University of Science and Technology of the Chinese Academy of Sciences has created a solution called Spatial Architecture Characterization by Deep Learning (SPACEL). The post Meet SPACEL: A New Deep-Learning-based Analysis Toolkit for Spatial Transcriptomics appeared first on MarkTechPost.

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Marktechpost

OCTOBER 8, 2023

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. Join our AI Channel on Whatsapp.

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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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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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Marktechpost

DECEMBER 30, 2023

The remarkable potentials of Artificial Intelligence (AI) and Deep Learning have paved the way for a variety of fields ranging from computer vision and language modeling to healthcare, biology, and whatnot. SciML consists of three primary subfields, which include PDE solvers, PDE discovery, and operator learning.

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Marktechpost

MARCH 23, 2024

AI researchers are taking the game to a new level with geometric deep learning. DeepMind Researchers introduce TacticAI, an AI assistant designed to optimize one of football’s biggest set-piece weapons: the corner kick. All credit for this research goes to the researchers of this project.

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Marktechpost

NOVEMBER 8, 2023

Overconfidence is a prevalent issue, particularly in the context of deep neural networks. The team has shared the two primary features of Fortuna that greatly improve deep learning uncertainty quantification. Deep neural networks that are being trained from the start can be trained using these techniques.

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Marktechpost

DECEMBER 15, 2023

Several new innovations have been made possible because of the advancements in the field of Artificial intelligence and Deep Learning. Complex tasks like text or picture synthesis, segmentation, and classification are being successfully handled with the help of neural networks.

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Marktechpost

OCTOBER 18, 2023

One of the biggest challenges in Machine Learning has always been to train and use neural networks efficiently. In recent research, a team of researchers has introduced a deep learning compiler specifically made for neural network training.

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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. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter.

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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Marktechpost

NOVEMBER 25, 2023

Data augmentation is a critical technique in deep learning that involves creating new training data by modifying existing samples. Creating variations of existing samples prevents overfitting and helps the model learn more robust and adaptable features, which is crucial for accurate predictions in real-world scenarios.

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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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Marktechpost

NOVEMBER 30, 2023

The study finds variability in the status of these core elements by analyzing 32 papers that predict poverty/wealth, using survey data for ground truth, applying it to urban and rural settings, and involving deep neural networks. The goal is to enhance wider dissemination and acceptance within the development community.

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Marktechpost

DECEMBER 28, 2023

Purdue University’s researchers have developed a novel approach, Graph-Based Topological Data Analysis (GTDA), to simplify interpreting complex predictive models like deep neural networks. The method was also applied to study chest X-ray diagnostics and compare deep-learning frameworks, showcasing its versatility.

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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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Marktechpost

JANUARY 5, 2024

Existing methods based on deep learning tend to model boundaries as discrete, rasterized maps, needing more resilience and adaptability for varied image resolutions and aspect ratios. Recent advances in boundary detection have predominantly employed deep learning techniques focusing on discrete representations.

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Marktechpost

JULY 12, 2023

Artificial neural networks have advanced significantly over the past few decades, propelled by the notion that more network complexity results in better performance. Modern technology has amazing processing capacity, enabling neural networks to perform these jobs excellently and efficiently.

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Marktechpost

DECEMBER 11, 2023

A rising number of people are interested in data-driven, deep learning-based weather forecasting methods to overcome the problems with NWP models. Using historical data, like the ERA5 reanalysis dataset, deep neural networks are trained to forecast future weather conditions.

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Marktechpost

NOVEMBER 23, 2023

Researchers have introduced a novel approach using topological data analysis (TDA), to solve the issue. These models, including machine learning, neural networks, and AI models, have become standard tools in various scientific fields but are often difficult to interpret due to their extensive parameterization.

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