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Latest articles
Really? AI Revolution is Losing Steam?
Really? AI Revolution is Losing Steam?
Concerns of sustanability of current AI development and prediction of the future AI
Kelvin Lu
Jun 10
What I learned from creating an AI of myself
What I learned from creating an AI of myself
Have you ever wanted to clone yourself? I don’t mean physically, but rather technologically. Here’s how I did it!
Sarah Cordivano
Jun 10
History, AI, and Non-Consumption: Part II, The Innovation Paradox
History, AI, and Non-Consumption: Part II, The Innovation Paradox
In part I of this series, we delved into the history of AI, journeying through periods of both promise and stagnation known as “AI…
Adel Zaalouk
Jun 10
Revolutionizing AI with DeepSeekMoE: Fine-grained Expert, and Shared Expert isolation 🧞♂️
Revolutionizing AI with DeepSeekMoE: Fine-grained Expert, and Shared Expert isolation 🧞♂️
Optimizing MoE with Fine-Grained and shared expert isolation for enhanced precision and efficiency in Large Language models.
JAIGANESAN
Jun 10
How do I Evaluate LLM?
How do I Evaluate LLM?
Before the launch of Large Language Models, I have always used to test and get a concrete accuracy of how well my model works — be it…
Meenakshi Srinivasan
Jun 9
Phi-3 and Azure: PDF Data Extraction | ExtractThinker
Phi-3 and Azure: PDF Data Extraction | ExtractThinker
How to combine Azure Document Intelligence and Phi-3 to extract data from files
Júlio Almeida
Jun 9
Towards Identification of Breast Cancer in Mammogram Images using Deep Learning: Part 2
Malignant and Benign Classification
Aminul Huq
Jun 9
Hands-On Introduction to Open AI Function Calling
Hands-On Introduction to Open AI Function Calling
A few months ago, OpenAI introduced a new capability to its API, enhancing its most recent models to accept additional parameters for…
Youssef Hosni
Jun 9
Testing Prompt Engineering-Based LLM Applications
Testing Prompt Engineering-Based LLM Applications
Hands-On Prompt Engineering for LLMs Application Development
Youssef Hosni
Jun 9
MidJourney and Surrealism: A Match Made in Artistic Heaven
MidJourney and Surrealism: A Match Made in Artistic Heaven
This combination is the perfect match for creative minds. Learn how to create stunning, imaginative art.
PromptDervish
Jun 8
RNN: Basic Recursive Neural Network for sentiment analysis in PyTorch
RNN: Basic Recursive Neural Network for sentiment analysis in PyTorch
This is a quick example to demonstrate the use of RNN to classify a set of tweets into positive or negative feedback. The idea is to give a…
Greg Postalian-Yrausquin
Jun 7
As a Product Manager, here’s how I *actually* use ChatGPT at work
As a Product Manager, here’s how I *actually* use ChatGPT at work
Spoiler alert: no, I don’t use it to come up with new product features.
Joy Zhang
Jun 7
A Study of Llama 3’s Rotary Position Embeddings
A Study of Llama 3’s Rotary Position Embeddings
Exploring the Advanced Mechanism Behind LLaMA 3’s Superior Positional Encoding for Natural Language Processing
Lorentz Yeung
Jun 7
Top Data Validation Tools for Machine Learning
Top Data Validation Tools for Machine Learning
Discover Python tools that can catch any issues with your data!
Eryk Lewinson
Jun 7
Let’s Talk Auto-Encoders
Let’s Talk Auto-Encoders
and how to improve their performance
Aminul Huq
Jun 7
Understanding MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Understanding MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
the math and intuition behind a novel parameter-efficient fine-tuning method
Hesam Sheikh
Jun 7
LoRA Learns Less and Forgets Less
LoRA Learns Less and Forgets Less
We will go through LoRA (Low-Rank Adaptation of Large Language Models), and compare LoRA to Full Fine-Tuning.
Hesam Sheikh
Jun 6
Building AI Agents With Crew AI using Google Gemini, Groq, LLama3
Building AI Agents With Crew AI using Google Gemini, Groq, LLama3
Introduction
Suhaib Arshad
Jun 6
Top Important LLMs Papers for the Week from 27/05 to 02/06
Top Important LLMs Papers for the Week from 27/05 to 02/06
Stay Updated with Recent Large Language Models Research
Youssef Hosni
Jun 6
Automatic Trend Change Points Detection in Time Series Analysis
Automatic Trend Change Points Detection in Time Series Analysis
How to identify and model trend change point into linear regression
Daniel Pollak
Jun 6
Reduce Risks when Coding with AI, AI Consulting Opportunities, Mistral 7B Deep Dive #27
Reduce Risks when Coding with AI, AI Consulting Opportunities, Mistral 7B Deep Dive #27
AI Community Projects, Group Learning, New Apps, and more!
Towards AI Editorial Team
Jun 6
Top Important Computer Vision Papers for the Week from 27/05 to 02/06
Top Important Computer Vision Papers for the Week from 27/05 to 02/06
Stay Updated with Recent Computer Vision Research
Youssef Hosni
Jun 6
Artificial General Ignorance and AI bubble
Artificial General Ignorance and AI bubble
Overcome our own biases and start from ABC: a hard inevitable path.
Fabio Matricardi
Jun 6
Deepspeed ZeRO-DP: distributed training for large models
Deepspeed ZeRO-DP: distributed training for large models
Deepspeed’s ZeRO (Zero Redundancy Optimizer) is a distributed training framework with a number of optimizations to easily train large deep…
Amina Shabbeer
Jun 6
Feature Selection and Generalization using Regularization
Feature Selection and Generalization using Regularization
An Overview of L1 and L2 Regularization Techniques and a Case Study on Feature Selection Using Neural Networks
Shahriar Hossain
Jun 5
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