logo
How to Scale AI in Your Organization

According to WEKA's 2023 Global Trends in AI Report, 69% of organizations now have AI projects up and running, and 28% are using AI across their whole business. This shows a big move from just trying out AI to making it a key part of how companies operate and succeed. However, this is just the beginning as the major point is not to have only AI but to have it work to your benefit. Organizations have to address various challenges such as the collection of data, hiring the right skills, and fittin

Published: April 4, 2024
# AI / ML
# Computer Vision
# NLP
Top Computer Vision Opportunities and Challenges for 2024

Computer vision (CV) is a part of artificial intelligence that enables computers to analyze and understand visual information, both images and videos. It goes beyond plain “seeing” an image, but teaches computers to make decisions based on what they see. The AI-driven computer vision market is experiencing rapid growth, rising from $22 billion in 2023 to an expected $50 billion by 2030, with a 21.4% CAGR from 2024 to 2030. This technology imitates human vision but works faster using sophisticate

Published: March 8, 2024
# Computer Vision
# AI / ML
Top-5 NLP news of December by a CTO of Sciforce — Max Ved

We are excited to announce that we are launching a new section today at Sciforce — “Top AI news of the month.” We decided to create this column to keep our valued clients aware of the latest news and technologies in the AI world. So, here, we will share some interesting information with you about SciTech! Well, today we will discuss Top-5 NLP news in December:

Published: January 19, 2023
# NLP
Face Detection Explained: State-of-the-Art Methods and Best Tools

So many of us have used different Facebook applications to see us aging, turned into rock stars, or applied festive make-up. Such waves of facial transformations are usually accompanied by warnings not to share images of your faces — otherwise, they will be processed and misused. But how does AI use faces in reality? Let’s discuss state-of-the-art applications for face detection and recognition. First, detection and recognition are different tasks. _Face detection_ is the crucial part of face re

Published: June 17, 2021
# Computer Vision
# AI / ML
Brain-Computer Interfaces: Your Favorite Guide

At the beginning of April 2021, Neuralink’s new video featuring a monkey playing Pong with his mind hit the headlines. The company’s as-always-bold statements promise to give back the freedom of movement to people with disabilities. We decided to look beyond the hype and define what these brain-computer systems are capable of in reality. Let’s dive right into it. Brain-computer interfaces (BCIs)* or *Brain-machine interfaces (BMIs) capture a user’s brain activity and translate it into commands f

Published: May 20, 2021
# Computer Vision
# AI / ML
Text Preprocessing for NLP and Machine Learning Tasks

As soon as you start working on a data science task you realize the dependence of your results on the data quality. The initial step — data preparation — of any data science project sets the basis for the effective performance of any sophisticated algorithm. In textual data science tasks, this means that any raw text needs to be carefully preprocessed before the algorithm can digest it. In the most general terms, we take some predetermined body of text and perform upon it some basic analysis and

Published: May 5, 2020
# NLP
Memorability in Computer Vision

Among many things that define us as humans, there is our ability to remember things such as images in great detail, and sometimes after a single view. What is even more interesting, humans tend to remember and forget the same things, suggesting that there might be some general internal capability to encode and discard the same types of information. What makes certain images more memorable than others? Research suggests that pictures of people, salient actions and events are more memorable than n

Published: March 25, 2020
# Computer Vision
# AI / ML
Biggest Open Problems in Natural Language Processing

The NLP domain reports great advances to the extent that a number of problems, such as part-of-speech tagging, are considered to be fully solved. At the same time, such tasks as text summarization or machine dialog systems are notoriously hard to crack and remain open for the past decades. However, if we look deeper into such tasks we’ll see that the problems behind them are rather similar and fall into two groups:

Published: February 5, 2020
# NLP
Google’s BERT changing the NLP Landscape

We write a lot about open problems in Natural Language Processing. We complain a lot when working on NLP projects. We pick on inaccuracies and blatant errors of different models. But what we need to admit is that NLP has already changed and new models have solved the problems that may still linger in our memory. One of such drastic developments is the launch of Google’s Bidirectional Encoder Representations from Transformers, or BERT model — the model that is called the best NLP model ever based

Published: November 21, 2019
# NLP
NLP for Low-Resource Settings

Natural language processing (NLP) is a field of Artificial Intelligence that tries to establish human-like communication with computers. Although it can boast significant success, computers still struggle with comprehending many facets of language, such as pragmatics, that are difficult to characterize formally. Moreover, most of the success is achieved in popular languages like English or other languages that have text corpora of hundreds of millions of words. But we should understand that thes

Published: October 11, 2019
# NLP
# AI / ML