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Under the Hood of LLaMA 2: A Deep Dive into Reward Modeling and RLHF
Under the Hood of LLaMA 2: A Deep Dive into Reward Modeling and RLHF
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 27
Customizing CoTracker3: How to Train the Model on Your Own Dataset
Customizing CoTracker3: How to Train the Model on Your Own Dataset
Learn how to fine-tune and further train CoTracker3 using your own dataset with step-by-step instructions and code examples.
Malyaj Mishra
Oct 26
Contrastive Language-Image Pre-Training (CLIP): A Comprehensive Overview📐
Contrastive Language-Image Pre-Training (CLIP): A Comprehensive Overview📐
In machine learning, Contrastive Language-Image Pre-Training (CLIP) has gotten a lot of interest because of its capacity to connect…
Asad iqbal
Oct 25
CoTracker3: The Latest AI Model for Superior Point Tracking
CoTracker3: The Latest AI Model for Superior Point Tracking
CoTracker3 model: Powerful pseudo-labelling, and simplifying the complexities of point tracking in videos
Malyaj Mishra
Oct 25
Setting Up CoTracker3: A Step-by-Step Guide for Installation, Demo, and Inference
Setting Up CoTracker3: A Step-by-Step Guide for Installation, Demo, and Inference
Learn how to install CoTracker3, run demos, and perform inference with basic code examples and pre-trained models.
Malyaj Mishra
Oct 25
A Complete Guide to NLP Techniques for Data Science Beginners
A Complete Guide to NLP Techniques for Data Science Beginners
My Personal Journey into the World of Language
Harsh Chourasia
Oct 24
AI APIs: Democratizing the Future of Artificial Intelligence
AI APIs: Democratizing the Future of Artificial Intelligence
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 22
How AutoMQ Reduces Nearly 100% of Kafka Cross-Zone Data Transfer Cost
How AutoMQ Reduces Nearly 100% of Kafka Cross-Zone Data Transfer Cost
Producing data with the broker in the same availability zone with S3 WAL, self-balancing, and leveraging Kafka rack-awareness
Vu Trinh
Oct 22
NVIDIA Unleashes Llama-3.1-Nemotron-70B-Instruct: Reshaping the Future of AI
NVIDIA Unleashes Llama-3.1-Nemotron-70B-Instruct: Reshaping the Future of AI
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 20
BitNet is Here: Run you AI Models on CPUs
BitNet is Here: Run you AI Models on CPUs
All the discussion about scaling and using LLMs is around GPUs. And everyone is focusing on how to built data centers around that purpose…
Vassilios Karakoidas
Oct 20
The Power of Time Series Analysis
The Power of Time Series Analysis
Adapting to Change and Learning from Patterns
Eric Francis Kariri
Oct 20
30 Must-Know Git Command-Line Tips for Developers
30 Must-Know Git Command-Line Tips for Developers
When I first started using Git, I quickly realized it was much more than just a version control tool.
Kiran Maan
Oct 19
The Evolution of a Neural Network: A Case Study in Optimization
The Evolution of a Neural Network: A Case Study in Optimization
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 19
From Spark to Flame: A History of Artificial Neural Networks
From Spark to Flame: A History of Artificial Neural Networks
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 19
The Rise of the Machines: AI-Native Development in the Cloud-Native Ecosystem
The Rise of the Machines: AI-Native Development in the Cloud-Native Ecosystem
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 17
Heart Disease Prediction Using Machine Learning
Heart Disease Prediction Using Machine Learning
Hey there! Today we’re diving into a topic that’s literally life or death — heart disease prediction. Now, before you get overwhelmed…
Ayomitan Adesua
Oct 17
Decoding the Language of Machines: Perplexity and the Rise of Perplexity AI
Decoding the Language of Machines: Perplexity and the Rise of Perplexity AI
Frank Morales Aguilera, BEng, MEng, SMIEEE
Frank Morales Aguilera
Oct 16
Astute RAG: The Future of Knowledge Retrieval
Astute RAG: The Future of Knowledge Retrieval
In the fast-changing world of artificial intelligence, getting accurate and reliable information has always been a big challenge. A…
Vansh Jatana
Oct 15
GSM8K and the Limitations of LLMs
GSM8K and the Limitations of LLMs
Recently, I bumped into the following paper by Apple engineers, titled:
Vassilios Karakoidas
Oct 15
Data Science: Is it relevant in Patient Care?
Data Science: Is it relevant in Patient Care?
Healthcare and technology have intertwined for years, affecting patient care both positively and negatively. As a caregiver, I’ve witnessed…
Taeja Williams
Oct 15
Can We Really Change an LLM's Memory? Key Insights from Recent Research
Can We Really Change an LLM's Memory? Key Insights from Recent Research
Brian Niccol became the CEO of Starbucks in August this year. Unfortunately, our LLMs were trained much before this, so they might still…
Nikhil Anand
Oct 14
Airflow: Life in Intervals
Airflow: Life in Intervals
In this article, I will discuss cases related to the Airflow DAG’s schedule.
Pavel Pustoshnyi
Oct 13
More on Loss Functions (Classification)
More on Loss Functions (Classification)
In my last post, I wrote about loss, what it is and some of the fundamental loss functions that are used for regression. In this post, we…
Francesco Franco
Oct 13
From Physics to AI: How Nobel Laureates Hopfield and Hinton Ignited the Neural Network Revolution
From Physics to AI: How Nobel Laureates Hopfield and Hinton Ignited the Neural Network Revolution
Machine learning capabilities enabled by artificial neural networks
Vipin
Oct 11
Building a voice-enabled Python FastAPI app using OpenAI’s Realtime API
Building a voice-enabled Python FastAPI app using OpenAI’s Realtime API
Learnings from my experience using the OpenAI Realtime API in my FastAPI websockets app with function calling.
Jayesh
Oct 11
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