Forward Networks

Introducing CulturaX: a 6.3 trillion-token multilingual dataset in 167 languages, meticulously cleaned and deduplicated for training high-performing LLMs.

CulturaX: A High-Quality, Multilingual Dataset for LLMs - Conclusion and References

Efficiently run large language models on devices with limited DRAM by optimizing flash memory use, reducing data transfer, and enhancing throughput.

Large Language Models on Memory-Constrained Devices Using Flash Memory: Optimized Data in DRAM

Explore the groundbreaking AI technology of Panoptic Scene Graph Generation with Transformers for a deeper understanding of visual scenes.

How An AI Understands Scenes: Panoptic Scene Graph Generation.

To succeed in providing an excellent user experience, website managers must know more than just which keywords people are entering.

What are the Types of Neural Networks and How Do They Work?

RNN is one of the popular neural networks that is commonly used to solve natural language processing tasks.

What is an RNN (Recurrent Neural Network) in Deep Learning?

What is a Recurrent Neural Network or RNN, how it works, where it can be used? This article tries to answer the above questions. It also shows a demo implementation of a RNN used for a specific purpose, but you would be able to generalise it for your needs.

RNN or Recurrent Neural Network for Noobs

<em>[epistemic status: I work in a lab dedicated to biologically plausible neural circuits, so I’m informed on the problem, but probably still biased. There’s probably going be a follow-up post to this once I get a bunch of rebuttals from people smarter than me.]</em>

Deep Learning isn’t the brain

Restormer’s transformer architecture powerfully restores HST images, combining deconvolution and denoising for JWST-level clarity using transfer learning.

Efficient Transformers for Astronomical Images: Deconvolution and Denoising Unleashed

Overview of Large Language Model (LLM) inference, its importance, challenges, and key problem formulation.

Primer on Large Language Model (LLM) Inference Optimizations: 1. Background and Problem Formulation

This paper surveys the evolution of generative AI, highlighting innovations in MoE, multimodality, and AGI while addressing ethical and research challenges.

Surveying the Evolution and Future Trajectory of Generative AI - Innovative Horizon of MOE

Simple explanation of the Transformer model from the revolutionary paper "Attention is All You Need" which is the basis of many advanced AI systems.

Transformers: Age of Attention

New AI model (Rate Card Transformer) analyzes package details (size, carrier etc.) to predict shipping costs more accurately. 

Unveiling the Power of Self-Attention for Shipping Cost Prediction: Experiment

This study considers a bivariate jump-diffusion model to describe Bitcoin price dynamics and the number of Google searches affecting the price.

Neural Network for valuing Bitcoin: References 

Creating a bot that, given a starting phrase, would generate its own lyrics, powered by a machine learning model that would have learned from existing songs.

Auto-Generating Lyrics With TensorFlow and Machine Learning: A How-To Guide

Speech-to-text (STT), also known as automated-speech-recognition (ASR), has a long history and has made amazing progress over the past decade. Currently, it is often believed that only large corporations like Google,  Facebook, or Baidu (or local state-backed monopolies for the Russian language) can provide deployable “in-the-wild” solutions.

Towards an ImageNet Moment for Speech-to-Text: A Deep Dive

High level frameworks and APIs make it a lot easy for us to implement such a complex architecture but may be implementing them from scratch gives us the ground truth intuition of how actually ConvNets work.

ConvNet from scratch: just lovely Numpy, Forward Pass |Part 1|

The biggest hurdle for blockchain adoption is scalability. Mobile and desktop applications spoiled consumer expectations for performance and responsiveness. The latency of 1994 is unacceptable in 2018. The slow grind towards production-ready scalability solutions kills the pace of development and embrace of decentralized applications (Dapps).

The Amazing Race For Scalable dApps

The challenging task of fabricating a pristine environment to nurture a growing, powerful learning entity capable of translating data into insights is one that cannot be avoided. It is necessary to realize that automation forces us to lose control and management over overwhelming amounts of data that A.I. mines. The source of the above relevant question is due to the volatility of data, as definitions of bias and corruption transform in accordance with circumstance and environmental conditions.

An Invincible A.I.: Enhancing Self-Learning Processes

Make sure to check out the other articles <a href="http://camron.xyz" target="_blank">here</a>.

TensorFlow in a Nutshell — Part Three: All the Models

This study uses Physics-Informed Neural Networks to model earthquakes and invert fault friction parameters, integrating data with physical constraints.

Integrating Physics-Informed Neural Networks for Earthquake Modeling: Physics-Informed Deep Learning

Looking at how blockchain validators exploited in billion-dollar security threat.

The Achilles' Heel of Blockchain: How Validators Became the Target of a Billion-Dollar Threat

ZPrize Competition. Over $2 million of cash prizes! The goal of ZPrize is to bring together the best teams at the intersection of cryptography research.

[Announcement] The ZPrize Competition For Zero Knowledge Cryptography by Aleo

“Web3 isn’t another buzzword or jargon which can be written off. It is the future of the internet. This is the new infrastructure layer which will power the next generation of computing innovation,” 

Web 3.0 – Our Future or Just Another Buzzword

Overview of How HTTP Routing Works in Azure Functions

Configuring HTTP Route Parameters in Azure Functions 2.x using Python

The software used to manage networks hasn’t kept up with the dramatic expansion of networks themselves

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CulturaX: A High-Quality, Multilingual Dataset for LLMs - Conclusion and References

Large Language Models on Memory-Constrained Devices Using Flash Memory: Optimized Data in DRAM

How An AI Understands Scenes: Panoptic Scene Graph Generation.

What are the Types of Neural Networks and How Do They Work?

What is an RNN (Recurrent Neural Network) in Deep Learning?

RNN or Recurrent Neural Network for Noobs

Deep Learning isn’t the brain

Efficient Transformers for Astronomical Images: Deconvolution and Denoising Unleashed

Primer on Large Language Model (LLM) Inference Optimizations: 1. Background and Problem Formulation

Surveying the Evolution and Future Trajectory of Generative AI - Innovative Horizon of MOE

Transformers: Age of Attention

Unveiling the Power of Self-Attention for Shipping Cost Prediction: Experiment

Neural Network for valuing Bitcoin: References

Auto-Generating Lyrics With TensorFlow and Machine Learning: A How-To Guide

Towards an ImageNet Moment for Speech-to-Text: A Deep Dive

ConvNet from scratch: just lovely Numpy, Forward Pass |Part 1|

The Amazing Race For Scalable dApps

An Invincible A.I.: Enhancing Self-Learning Processes

TensorFlow in a Nutshell — Part Three: All the Models

Integrating Physics-Informed Neural Networks for Earthquake Modeling: Physics-Informed Deep Learning

The Achilles' Heel of Blockchain: How Validators Became the Target of a Billion-Dollar Threat

[Announcement] The ZPrize Competition For Zero Knowledge Cryptography by Aleo

Web 3.0 – Our Future or Just Another Buzzword

Configuring HTTP Route Parameters in Azure Functions 2.x using Python

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