Factorize

Compared to previous neural field techniques, 3DIML achieves 14–24× faster training times for 3D instance segmentation from 2D photos.

Solving 3D Segmentation’s Biggest Bottleneck

Discover how Toto achieved state-of-the-art results in AI forecasting, surpassing leading zero-shot and full-shot models.

Toto AI Model Sets New Benchmark for Time Series Forecasting

Datadog’s Toto sets a new benchmark in time series forecasting with trillion-point training and domain-tuned observability insights.

The Time Series Optimized Transformer Setting New Standards in Observability

Learn how to compress images using Singular Value Decomposition (SVD) in TensorFlow with practical examples, low-rank approximations, and energy-based tuning.

How to Compress Images With SVD and TensorFlow Core APIs

Researchers demonstrate how QCNNs excel in cyclic feature extraction for bearing fault signals by leveraging autocorrelation and noise cancellation techniques. 

How Advanced Neural Networks Improve Signal Clarity and Fault Detection

In this section, we describe the generation and serving procedures of typical LLMs and the iteration-level scheduling used in LLM serving.

The Generation and Serving Procedures of Typical LLMs: A Quick Explanation

Explore unconventional monetary policies, focusing on persistence elimination, demand shocks, and the interplay between inflation and output smoothing

How Unconventional Monetary Policies Address Economic Shocks

Explore the anti-Taylor policy rule, its mathematical proof, and implications for monetary policy stability, equilibrium, and New Keynesian macroeconomics. 

When Does Monetary Policy Fail? Insights from Anti-Taylor Rules

Learn how algebraic geometry techniques, like schemes and rings, help identify when economic models break down or shift unexpectedly.

Detecting Instability in Economic Models Using Algebraic Geometry

This breakthrough garnered a lot of attention and paved the way for further research and development in the field.

DreamLLM: Additional Related Works to Look Out For

This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport problems, respectively.

Efficient Neural Network Approaches for Conditional Optimal Transport: Numerical Experiments

Exploring AGI's progress and limitations: from visual reasoning struggles to potential in automating front-end engineering and aiding scientific discovery.

How Far Are We From Human-level Intelligence in AI?

A program that maintain its correctness in a multi-threaded environment is said to be a Thread-Safe program.

Safeguarding Concurrent Programs in Java: Thread Safety from an Object Oriented Perspective

Sometimes simplicity is key to getting the best results. And that's what Lumiere by Google offers.

Google Unveils Its Most Promising Text-to-Video Model Yet: Lumiere

The concept of prime numbers serves as a method to delineate the number line without leaving any voids. 

Prime Numbers: The Unbreakable Building Blocks of Mathematics

This blog analyses various CNN and Transformer-based SWIN architecture for Image Classification 

Image Classification in 2022

Can software project estimation be as realistic as possible? This article will walk you through how we, at UpsilonIT, approach the estimating process. We will also share some hands-on techniques and useful tips on making it more accurate and robust.

Accurate Project Estimations: How To Make Them?

Here's a deep dive into the history of machine learning embeddings, common uses, and current infrastructure solutions, including the vector database. 

Embeddings in Machine Learning: Everything You Need to Know

Influencer marketing prospects really impress! This market has doubled for the last year and a half and currently amounts to over $2 billion. No wonder! Bloggers give brands access to a huge audience on social networks. Instagram bloggers lead by a wide margin: 69% of marketers promote products with their help. However, there are some obstacles to the growth of this market, because of which small business almost does not risk to use the services of Instagram stars. Their prices are crazy high, guarantees are not always provided, and the selection of relevant influencers is too complicated. Data scientist Arthur Suilin presents problems with the new marketing industry and their solutions. Editor and co-author Egor Perezhogin.

Targeting and fake followers: how can we solve the most acute problems of influencer marketing?

The International Conference on Learning Representations (ICLR) took place last week, and I had a pleasure to participate in it. ICLR is an event dedicated to research on all aspects of representation learning, commonly known as deep learning. This year the event was a bit different as it went virtual. However, the online format didn’t change the great atmosphere of the event. It was engaging and interactive and attracted 5600 attendees (twice as many as last year). If you’re interested in what organizers think about the unusual online arrangement of the conference, you can read about it here.

The Ten Must Read NLP/NLU Papers from the ICLR 2020 Conference

I've been writing code for over three years. I have always asked myself about the good practices and how I could make my code more readable, understandable, easy to maintain and to be handled by other developers.

Best Practice in CSS: Organisation and Naming Conventions

I started using Pytorch to train my models back in early 2018 with 0.3.1 release. I got hooked by the Pythonic feel, ease of use and flexibility.

Eight Leaders Explain Their Model Training Libraries For The PyTorch Ecosystem

To understand what PyTorch is, how it works, and its ability to catalyze technological advancements. It’s important first to understand the answer to the question, “What is PyTorch?”

Facebook’s PyTorch3D : A Catalyst for Deep Learning and 3D Objects

Behavior-Driven Development (BDD) is a really powerful tool that helps us build robust, value-based software. You can sometimes hear detractors say that it brings a lot of complexity and leads to long tests difficult to maintain. Let's take stock of what BDD really is, by determining anti-patterns and best practices.

Behavior-Driven Development From Scratch [101]

We’re building Verse™: a visual programming tool made for developers by developers

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Factorize's stories on HackerNoon

Solving 3D Segmentation’s Biggest Bottleneck

Toto AI Model Sets New Benchmark for Time Series Forecasting

The Time Series Optimized Transformer Setting New Standards in Observability

How to Compress Images With SVD and TensorFlow Core APIs

How Advanced Neural Networks Improve Signal Clarity and Fault Detection

The Generation and Serving Procedures of Typical LLMs: A Quick Explanation

How Unconventional Monetary Policies Address Economic Shocks

When Does Monetary Policy Fail? Insights from Anti-Taylor Rules

Detecting Instability in Economic Models Using Algebraic Geometry

DreamLLM: Additional Related Works to Look Out For

Efficient Neural Network Approaches for Conditional Optimal Transport: Numerical Experiments

How Far Are We From Human-level Intelligence in AI?

Safeguarding Concurrent Programs in Java: Thread Safety from an Object Oriented Perspective

Google Unveils Its Most Promising Text-to-Video Model Yet: Lumiere

Prime Numbers: The Unbreakable Building Blocks of Mathematics

Image Classification in 2022

Accurate Project Estimations: How To Make Them?

Embeddings in Machine Learning: Everything You Need to Know

Targeting and fake followers: how can we solve the most acute problems of influencer marketing?

The Ten Must Read NLP/NLU Papers from the ICLR 2020 Conference

Best Practice in CSS: Organisation and Naming Conventions

Eight Leaders Explain Their Model Training Libraries For The PyTorch Ecosystem

Facebook’s PyTorch3D : A Catalyst for Deep Learning and 3D Objects

Behavior-Driven Development From Scratch [101]

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