Data Annotation, an “Engine” for Self-Driving Car

With the development of computer vision technology and the increasing intelligence of the travel eco-system, the typical application scenario is autonomous driving.

Semantic Segmentation

Self-driving cars are really coming

In 2018, the world’s first driverless taxi was on the roads. This is the first driverless taxi ride in Frisco, Texas, by Silicon Valley start-up Drive.ai.

In China, Baidu is the leader in the auto autonomous driving industry. On 30 Nov 2019, Baidu launched a trial operation of RoboTaxi in Guangzhou, the second biggest city in China.

Technical support behind self-driving cars

In the process of autonomous driving, the car itself needs to…


Data Labeling Industry Needs to Take the Lead in Reform as AI is Difficult to Break the Ground

AI landing has become a difficulty

Two years ago, the investment and financing enthusiasm of the artificial intelligence field has been greatly reduced, and a considerable number of AI enterprises have completely disappeared. “The cold wave of artificial intelligence has arrived” has even become the industry’s hot word in 2019.

Compared with the boom a few years ago when entrepreneurship and investment enthusiasm went forward together, the AI industry has suffered a lot recently.

The reason is that “AI landing has become a difficulty”.

From the age of automation to the age of AI, the value created by artificial intelligence is constantly increasing. Meanwhile, the refinement…


Four Customer Pain Points in Getting No Bias Training Data

With the commercialization of AI products, auto-driving, face recognition, security, and other fields have become popular scenarios, and AI companies begin to focus on scenario-based landing capability.

As the basis of the AI industry, high-quality training data is one of the decisive elements of the model launching.

Relevant statistics show that the amount of data generated in 2025 will be as high as 163ZB, 90% of which are unstructured data. These unstructured data can only be “awakened” by cleaning and labeling. The potential and large demands allow the data labeling service to keep booming and expanding.


Living in the Internet age, how occasionally have you come across the tricky CAPTCHA tests while entering a password or filling a form to prove that you’re fully human? For example, typing the letters and numbers of a warped image, rotating objects to certain angles, or moving puzzle pieces into position.

What is CAPTCHA and How Does It Work?

CAPTCHA is also known as the Completely Automated Public Turing Test to filter out the overwhelming armies of spambots. Researchers at Carnegie Mellon University developed CAPTCHA in the early 2000s. Initially, the program displayed some garbled, warped, or distorted text that a computer could not read, only a human…


The Animoji feature in the text message, of course!

Source:https://www.thurrott.com/microsoft/209813/microsoft-copied-the-iphones-animoji-and-made-it-more-accessible

Simply put, it is through face recognition technology, using the image provided by the system to record their own exclusive dynamic expression.

This amazing feature helps us express things that we don’t know how to express through words. In addition to emoticons, people can record sounds to express their mood, and they can copy the recorded emoticons and send them to social media.

How do these dynamic expressions, which you can’t stop playing, come into being?


Lipstick Effect

There is a famous “lipstick effect” in economic theory, which refers to an interesting economic phenomenon that lipstick is sold hot due to economic depression, also known as “ small luxury items preference “. For example, in 2008, during the global financial crisis, the cosmetics industry continued to be on rising.

Despite that the Covid-19 epidemic in 2019 disturbs routine life, it cannot disturb the admiration for beauty. Due to the limitation of physical conditions, the cosmetics industry constantly uses artificial intelligence to develop its business online.

Image Recognition Case

Brand search accuracy is one of the main directions of AI technology in…


Data Annotation Service — From the Backstage to the Front Stage

“Have you heard about the AI industry?”

9 out of 10 people will probably say yes.

“Do you know data-annotation?”

This time, 9 out of 10 people will probably shake their heads.

Unlike AI companies at the center of the spotlight, the data annotation industry has been in the gray area for a long time, in a low-profile status.

However, with the increasing of refined demands, the data annotation industry is undergoing rapid changes, moving from the background to the foreground.

Annotation service

Data annotation technique is used to make the objects recognizable and understandable for machine learning models. It is critical…


New Trends and Challenges in Data Annotation Industry

Data Annotation

Data annotation technique is used to make the objects recognizable and understandable for machine learning models. It is critical for the development of machine learning (ML) industries such as face recognition, autonomous driving, aerial drones, and many other AI and robotics applications.

Data Annotation Market Size

The global data annotation market was valued at US$ 695.5 million in 2019 and is projected to reach US$ 6.45 billion by 2027, according to Research And Markets’ report. Expected to grow at a CAGR of 32.54% from 2020 to 2027, the booming data annotation market is witnessing tremendous growth in the forthcoming future.

The data annotation industry…


The data annotation industry is driven by the increasing growth of the AI industry

Data Annotation Market Size

The global data annotation market was valued at US$ 695.5 million in 2019 and is projected to reach US$ 6.45 billion by 2027, according to Research And Markets’ report. Expected to grow at a CAGR of 32.54% from 2020 to 2027, the booming data annotation market is witnessing tremendous growth in the forthcoming future.

The data annotation industry is driven by the increasing growth of the AI industry.

At present, the commercialization of Artificial intelligence has reached a stage of basic maturity in terms of computing power and algorithm. …


How a Human-Powered Data Labeling Platform Accelerates AI industry’s Development During COVID-19

The covid-19 epidemic in 2019 disturbs routine life across the globe. Due to the limitation of physical conditions, traditional enterprises are enhancing their strategies for digital transformation and business automation.

Data Labeling is a Simple but Difficult Task

Labeled data is the core of the AI/ML industry. The quality and quantity of data determine the performance of the AI model.

It is showed that an in-house experienced team composed of 10 labelers and 3 QA inspectors is able to complete around 10,000 automatic driving lane image labeling in 8 days.

In fact, training a model needs tens of thousands or even millions of no bias data samples, which…

ByteBridge

A data labeling platform with robust tools for real-time workflow management, providing high-quality training data with efficiency. — http://bytebridge.io/#/

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