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Pixel Tolerance vs. IOU - Which One Should You Use for Quality Training Data?

The purpose of data annotation for computer vision is to teach a model how ...

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Pixel Tolerance vs. IOU - Which One Should You Use for Quality Training Data?

The purpose of data annotation for computer vision is to teach a model how ...

Responsible AI: How to Mitigate Bias in Your Training Data

The more we use AI to power and automate crucial parts of our daily lives, ...

Alegion Teams with Malaysian Government Agency to Expand ML Workforce Opportunities

Alegion and Malaysian government agency Yayasan Peneraju collaborate to tra...

Welcome to The Keypoint

Welcome to The Keypoint - a newsletter from Alegion updating our customers ...

Investment Banking Veteran and Software Market Strategist Jonathan Price Joins Alegion’s Board of Directors

Investment Banking Veteran and Software Market Strategist Jonathan Price Jo...

Calling All Data Scientists - Survey for Alegion 2021 State of the Industry

Each year, Alegion releases our analysis of the AI / ML space. We call upon...

Dr. Carla Brodley Joins Alegion’s Board of Directors

Renowned Machine Learning Researcher and Inclusive Computing Leader Dr. Car...

A Step-by-Step Guide to Quality Training Data for Computer Vision

Alegion specializes in high-quality training data for computer vision. In t...

How Alegion Stacks Up Against the VA Competition

How will you know if you have the best video annotation solution on the mar...

Active Learning: What it is & How Alegion Does it

Active learning is a method used in machine learning that helps focus data ...

Part 3: Building a Video Annotation Platform

With the rise of video, Alegion has become the top vendor for video annotat...

Part 2: Building a Video Annotation Platform

With the rise of video, Alegion has become the top vendor for video annotat...

Part 1: Building a Video Annotation Platform by Chip Ray, CTO

Over the past year, Alegion has taken on the challenge of building the best...

Alegion Closes Record Year Naming New Executives to Key Leadership Roles

Alegion Inc., a leading training data provider, closes record year naming n...

Designing for Video Annotation

Alegion opens up its powerful data labeling platform for self-serve use wit...

Alegion Control - The New Self Serve Data Labeling Platform

Alegion opens up its powerful data labeling platform for self-serve use wit...

Alegion Welcomes A New CEO!

Alegion Inc., a leading training data provider, announces David Mather, a t...

Entity Groups - Purpose-Built Annotation Tooling

Entity Groups organizes all of the items to be annotated for a particular t...

Alegion Launches ML-assisted Annotation for high-definition, long-running video footage

Alegion Launches ML-assisted Annotation for high-definition, long-running v...

Managing Incident Response Like A Pro

Learn about our incident response best practices collected and implemented ...

CV Case Study: Complex Video Annotation For Loss Prevention

Learn how Alegion helps companies leverage high-precision video annotation ...

Data Labeling for AI & ML Experimentation

This post shows how more experiments & smaller volumes of data help high-pe...

SmartPoly - Empowering Annotators with ML

SmartPoly takes the extreme points of an object in image or video as input ...

How ML Improves Quality

Balancing ML innovations and human expertise to deliver the highest quality

CV Case Study: Subjective Scene Classification for Improved Search Experience

This CV case study shows how Alegion built a scalable data labeling pipelin...

A Platform Built for Quality

This short guide shows how Alegion's Platform can improve your data labelin...

ML Experimentation - Fail Fast, Learn Faster

In this episode, Saurabh and I talk to Alegion’s Chief Data Scientist, Cher...

Alegion Flex Launch

Alegion Flex is the first ML data labeling solution designed for ML experim...

How Alegion Guarantees Quality

This white paper shows how Alegion is able to guarantee quality through our...

CV Case Study: Tracking Attentiveness & Emotion

This case study shows how leveraging high-precision data annotation empower...

Faster R-CNN: Using Region Proposal Network for Object Detection

This article explores Faster R-CNN & how RPNs, fully convolutional networks...

Ai & ML in the 2010s - From Science Fiction to Reality

The 2010s was the decade that “machine intelligence” made the leap from sci...

The Expense of Poorly Labeled Data

We take a good data set conducive towards modeling and distort the data in ...

Cost Of Poorly Labeled Data

Download this complimentary white paper to learn what causes poor quality t...

Checklist for Choosing a Platform

This short guide and accompanying checklist will help you when choosing the...

How to Improve Quality

Download this short complimentary guide to improve your data labeling quali...

NeurIPS 2019 Review - Insider's Guide

In this episode, Alegion’s Chief Data Scientist, Cheryl Martin, and Directo...

How To Measure Quality Data Labeling

This short guide will walk you through the four core metrics to measure you...

Data Science for Business

No BiAS is on the Top 10 AI Podcasts & Radio You Must Follow in 2019! Check...

How To Define Quality Data Labeling

This short guide will help you establish an unambiguous set of rules that d...

How to Achieve Quality Data Annotation

Alegion's Data Science Team put together a whitepaper on annotation guideli...

CV & ML - Visual Understanding Beyond Object Recognition

CV is everywhere! From Snapchat filters to YouTube video buffering to medic...

Trends & Innovations in ML

Alegion Mentioned In Gartner's 2019 Hype Cycle

Alegion ranked #1 place to work

We are excited and honored to be named the #1 place to work among small com...

New Use Cases & Highlights from ICCV 2019

ICCV is a hotbed of innovative ideas and technology aimed at giving the gif...

Methods of Video Annotation

Annotated videos hold the future for training computer vision models. Learn...

Deep Learning for Object Detection Part II

Introduction to a more in depth piece about Fast R-CNN and the innovations ...

Episode 4: Bias in ML

In this podcast episode, we discuss helpful mathematical bias and examples ...

5 Key takeaways from Trade show season

Trade show season has begun and these conferences continually demonstrate t...

Machine Learning for the Enterprise

This emerging world of AI runs on data. Learn how to properly prepare your ...

Deep Learning for Object Detection Part I

Introducing a new series on state-of-the-art object detection techniques an...

New Episode: Supervised vs Unsupervised learning

In this episode we break down the strengths and weaknesses of each approach...

NLP Part II: Understanding the challenges of NLP through Wittgenstein

Philosopher Ludwig Wittgenstein's insights into human communication can hel...

NLP Part I: Communication is Key

As difficult as it can be to successfully communicate with another person, ...

Is data the new oil?

In the latest episode of our podcast, No BiaS, Melody, Nikhil, and Saurabh ...

Just the Cliffnotes - Supervised vs unsupervised learning

New executive summary - “Machine Learning” — Gives “computers the ability t...

Alegion in WSJ & Forbes!

The Wall Street Journal and Forbes take notice that manually labeling data ...

Announcing our new podcast - No Bias

Check out out first episode of No Bias, where we discuss the emerging and e...

Agriculture is deep into machine learning

ML is revolutionizing agriculture. The benefit to growers is faster, more p...

Survey Says: Outsource Your Data Labeling

Global survey of data scientists shows that organizations that outsource th...

Supervised vs Unsupervised Learning

What we learned attending 5 AI/ML conferences in June! And a new “how to” ...

CV: what does it mean to "see"?

Aristotle observed the link between our desire for knowledge and our deligh...

Survey says: model confidence is built on a lot of training data

New survey reveals a concrete definition of “huge” in reference to 72% rep...

New survey shows ai and ml are still nascent

Breaking news: A global survey shows AI is still in its infancy and poor da...

We're in the news!

Dimensional Research has just published a fascinating survey showing that m...

The Primacy of Flexibility

To address both volume and complexity, a computer vision labeling and annot...

ODSC East 2019

The AI space is maturing and training data is feeding the growth.

Data Engineering, Prep, and Labeling for AI 2019 - They’re not wrong

Report delineating the requirements and hurdles of data preparation, as wel...

What does Alegion do?

What does Alegion do? O'Reilly AI Conference this week. We prepare quality ...

We are making an impact

The rapid growth in enterprise ML projects has helped us to achieve our imp...

Moving on up...

We're hiring in all departments. Come join our fast growing team at Alegion...

The State of AI Expertise

So what is the state of AI expertise? Early stages but growing fast. AI tea...

Look for us at MLconf in New York

MLconf's New York event is on March 29th this year. It's a great event for ...

AI in Austin, AI at SxSW

We participated in an AI event during last week’s South by Southwest Confer...

We've integrated computer vision capabilities into our training data platform

In a press release this morning we announced new computer vision capabiliti...

A blueprint for preparing your own ML training data

Considering DIY training data? We created a downloadable blueprint that lay...

The Journey of a Machine Learning (and learning) Project

Alegion partners with clients to create training data for their machine lea...

This Week in Austin: Machine Learning

The local Austin machine learning community will be busy this week. Machine...

7 tips to being AI ready

7 tips to being AI ready. We produce quality training data for computer vis...

The real promise is AI to AI to AI to AI

There are irreplaceable human beings answering the phone line at 911 who ca...

Interview with Nathaniel Gates, CEO & Co-Founder at Alegion

There’s this prevailing suggestion that AI is only beginning to emerge, but...

See you at Texas AI Summit

We are excited to be a silver sponsor at Texas AI Summit that brings AI pra...

What Experts had to say About AI in 2018

Analysts and researchers who have been following the emergence of AI contin...

Lunch and Label Survival Guide

Lunch and Label is a popular tactic among the Training Data DIYers. Data Sc...

Artificial Intelligence 2018 - A Year in Review

2018 saw stories in a huge cross section of publications. Technology standa...

Security-in-the-Loop

“Human-in-the-loop” is an increasingly popular way of describing the applic...

Measurement bias

If the images your algorithm is learning from were shot with a lens with a ...

The Agile AI Way - part 2

Much like with traditional software development, as AI and ML initiatives t...

Prejudicial Bias

Prejudicial bias is probably what most people think of when they hear the w...

The Agile AI Way - part 1

In waterfall these interdependencies aren’t fully explored until the penult...

Sample Bias

With sample bias in machine learning in computer vision, natural language p...

Algorithm bias

Bias is generally coupled with variance, another algorithm property. Bias a...

AI Bias: Where it comes from and what to do about it

We’re going to dedicate a series of posts in this blog to the topic of bias...

TRICK OR TREAT!

In honor of Halloween we're demystifying three really scary things that hap...

We've just announced the Alegion Training Data Platform

We've just released significant enhancements to the Alegion Training Data P...

Finding the ‘Right’ Data to Train your AI Is Getting Easier

Finding the ‘Right’ Data to Train your AI Is Getting Easier

Gartner: Artificial Intelligence Demands That CIOs Foster a Data-Literate Society

Gartner: Artificial Intelligence Demands That CIOs Foster a Data-Literate S...

Consider the Meaning of Deep Learning Before Beginning a Project

Consider the Meaning of Deep Learning Before Beginning a Project

Define the Problem then Create the Solution

Define the Problem then Create the Solution

How Artificial Intelligence Is Edging Its Way into Our Lives

How Artificial Intelligence Is Edging Its Way into Our Lives

Venture Capital Firms Use Artificial Intelligence to Sift Through Investment Opportunities

Venture Capital Firms Use Artificial Intelligence to Sift Through Investmen...

Google’s Appetite for Growth in AI Is Revealed in Its Looming Battle with Amazon

Google’s Appetite for Growth in AI Is Revealed in Its Looming Battle with A...

Sophisticated Training Data Leads to AI Program that Spots Wildlife Poachers

Sophisticated Training Data Leads to AI Program that Spots Wildlife Poacher...

Study Suggests The Better the Data, the Better the AI

Study Suggests The Better the Data, the Better the AI

Irish Tech News Interviews Alegion CEO Nathaniel Gates about Company’s Success

Irish Tech News Interviews Alegion CEO Nathaniel Gates about Company’s Succ...

Alegion CEO Nathaniel Gates Invited to Speak at AI Conference

Alegion CEO Nathaniel Gates Invited to Speak at AI Conference

The AI Movement Will Create Jobs, Not Kill Them

The AI Movement Will Create Jobs, Not Kill Them

German Newspaper Highlights Alegion for Work with Crowd

German Newspaper Highlights Alegion for Work with Crowd

Huffington Post Highlights Alegion

Huffington Post Highlights Alegion

Alegion in Businessweek Magazine Feature on the Future of AI

Alegion in Businessweek Magazine Feature on the Future of AI

Navidar Singles Out Alegion in Report on Developments in AI and Machine Learning

Navidar Singles Out Alegion in Report on Developments in AI and Machine Lea...

AI Trends Features Alegion

AI Trends Features Alegion

The Marketing Artificial Intelligence Institute Singles Out Alegion

The Marketing Artificial Intelligence Institute Singles Out Alegion

Market Watch Announces Alegion’s Acceleration Plan

Market Watch Announces Alegion’s Acceleration Plan

Seeking Alpha Features Alegion’s Unique Position in AI Field

Seeking Alpha Features Alegion’s Unique Position in AI Field

Yahoo! Finance Features Alegion CEO

Yahoo! Finance Features Alegion CEO

Austin startup Alegion brings in $3.6 million to ramp up AI initiatives

Austin startup Alegion brings in $3.6 million to ramp up AI initiatives

ABJ Features Alegion’s New Jobs, New Focus

ABJ notes that “CEO Nathaniel Gates expects Alegion's headcount to nearly d...

Artificial Intelligence Startup Alegion Raises $3.6 Million

Artificial Intelligence Startup Alegion Raises $3.6 Million

Alegion Featured in Real-Time Insights

Alegion Featured in Real-Time Insights

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First Blog Post

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