AI & ML Technology Updates

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Checklist for Choosing a Platform

This short guide and accompanying checklist will help you when choosing the...
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How to Improve Quality

Download this short complimentary guide to improve your data labeling quali...
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NeurIPS 2019 Review - Insider's Guide

In this episode, Alegion’s Chief Data Scientist, Cheryl Martin, and Directo...
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How To Measure Quality Data Labeling

This short guide will walk you through the four core metrics to measure you...
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Data Science for Business

No BiAS is on the Top 10 AI Podcasts & Radio You Must Follow in 2019! Check...
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How To Define Quality Data Labeling

This short guide will help you establish an unambiguous set of rules that d...
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How to Achieve Quality Data Annotation

Alegion's Data Science Team put together a whitepaper on annotation guideli...
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CV & ML - Visual Understanding Beyond Object Recognition

CV is everywhere! From Snapchat filters to YouTube video buffering to medic...
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Trends & Innovations in ML

Alegion Mentioned In Gartner's 2019 Hype Cycle
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Alegion ranked #1 place to work

We are excited and honored to be named the #1 place to work among small com...
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New Use Cases & Highlights from ICCV 2019

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

Annotated videos hold the future for training computer vision models. Learn...
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Deep Learning for Object Detection Part II

Introduction to a more in depth piece about Fast R-CNN and the innovations ...
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Episode 4: Bias in ML

In this podcast episode, we discuss helpful mathematical bias and examples ...
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5 Key takeaways from Trade show season

Trade show season has begun and these conferences continually demonstrate t...
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Machine Learning for the Enterprise

This emerging world of AI runs on data. Learn how to properly prepare your ...
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Deep Learning for Object Detection Part I

Introducing a new series on state-of-the-art object detection techniques an...
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New Episode: Supervised vs Unsupervised learning

In this episode we break down the strengths and weaknesses of each approach...
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NLP Part II: Understanding the challenges of NLP through Wittgenstein

Philosopher Ludwig Wittgenstein's insights into human communication can hel...
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NLP Part I: Communication is Key

As difficult as it can be to successfully communicate with another person, ...
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Is data the new oil?

In the latest episode of our podcast, No BiaS, Melody, Nikhil, and Saurabh ...
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Just the Cliffnotes - Supervised vs unsupervised learning

New executive summary - “Machine Learning” — Gives “computers the ability t...
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Alegion in WSJ & Forbes!

The Wall Street Journal and Forbes take notice that manually labeling data ...
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Announcing our new podcast - No BiaS

Check out out first episode of No BiaS, where we discuss the emerging and e...
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Agriculture is deep into machine learning

ML is revolutionizing agriculture. The benefit to growers is faster, more p...
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Survey Says: Outsource Your Data Labeling

Global survey of data scientists shows that organizations that outsource th...
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Supervised vs Unsupervised Learning

What we learned attending 5 AI/ML conferences in June! And a new “how to” ...
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CV: what does it mean to "see"?

Aristotle observed the link between our desire for knowledge and our deligh...
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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...
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New survey shows ai and ml are still nascent

Breaking news: A global survey shows AI is still in its infancy and poor da...
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We're in the news!

Dimensional Research has just published a fascinating survey showing that m...
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The Primacy of Flexibility

To address both volume and complexity, a computer vision labeling and annot...
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ODSC East 2019

The AI space is maturing and training data is feeding the growth.
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Data Engineering, Prep, and Labeling for AI 2019 - They’re not wrong

Report delineating the requirements and hurdles of data preparation, as wel...
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What does Alegion do?

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

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

We're hiring in all departments. Come join our fast growing team at Alegion...
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The State of AI Expertise

So what is the state of AI expertise? Early stages but growing fast. AI tea...
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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 ...
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AI in Austin, AI at SxSW

We participated in an AI event during last week’s South by Southwest Confer...
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We've integrated computer vision capabilities into our training data platform

In a press release this morning we announced new computer vision capabiliti...
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A blueprint for preparing your own ML training data

Considering DIY training data? We created a downloadable blueprint that lay...
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The Journey of a Machine Learning (and learning) Project

Alegion partners with clients to create training data for their machine lea...
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This Week in Austin: Machine Learning

The local Austin machine learning community will be busy this week. Machine...
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7 tips to being AI ready

7 tips to being AI ready. We produce quality training data for computer vis...
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The real promise is AI to AI to AI to AI

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

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

There’s this prevailing suggestion that AI is only beginning to emerge, but...
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See you at Texas AI Summit

We are excited to be a silver sponsor at Texas AI Summit that brings AI pra...
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What Experts had to say About AI in 2018

Analysts and researchers who have been following the emergence of AI contin...
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Lunch and Label Survival Guide

Lunch and Label is a popular tactic among the Training Data DIYers. Data Sc...
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Artificial Intelligence 2018 - A Year in Review

2018 saw stories in a huge cross section of publications. Technology standa...
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Security-in-the-Loop

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

If the images your algorithm is learning from were shot with a lens with a ...
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The Agile AI Way - part 2

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

Prejudicial bias is probably what most people think of when they hear the w...
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The Agile AI Way - part 1

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

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

Bias is generally coupled with variance, another algorithm property. Bias a...
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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...
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TRICK OR TREAT!

In honor of Halloween we're demystifying three really scary things that hap...
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We've just announced the Alegion Training Data Platform

We've just released significant enhancements to the Alegion Training Data P...
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Finding the ‘Right’ Data to Train your AI Is Getting Easier

Finding the ‘Right’ Data to Train your AI Is Getting Easier
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Gartner: Artificial Intelligence Demands That CIOs Foster a Data-Literate Society

Gartner: Artificial Intelligence Demands That CIOs Foster a Data-Literate S...
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Consider the Meaning of Deep Learning Before Beginning a Project

Consider the Meaning of Deep Learning Before Beginning a Project
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Define the Problem then Create the Solution

Define the Problem then Create the Solution
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How Artificial Intelligence Is Edging Its Way into Our Lives

How Artificial Intelligence Is Edging Its Way into Our Lives
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Venture Capital Firms Use Artificial Intelligence to Sift Through Investment Opportunities

Venture Capital Firms Use Artificial Intelligence to Sift Through Investmen...
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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...
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Sophisticated Training Data Leads to AI Program that Spots Wildlife Poachers

Sophisticated Training Data Leads to AI Program that Spots Wildlife Poacher...
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Study Suggests The Better the Data, the Better the AI

Study Suggests The Better the Data, the Better the AI
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Irish Tech News Interviews Alegion CEO Nathaniel Gates about Company’s Success

Irish Tech News Interviews Alegion CEO Nathaniel Gates about Company’s Succ...
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Alegion CEO Nathaniel Gates Invited to Speak at AI Conference

Alegion CEO Nathaniel Gates Invited to Speak at AI Conference
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The AI Movement Will Create Jobs, Not Kill Them

The AI Movement Will Create Jobs, Not Kill Them
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German Newspaper Highlights Alegion for Work with Crowd

German Newspaper Highlights Alegion for Work with Crowd
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Huffington Post Highlights Alegion

Huffington Post Highlights Alegion
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Alegion in Businessweek Magazine Feature on the Future of AI

Alegion in Businessweek Magazine Feature on the Future of AI
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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...
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AI Trends Features Alegion

AI Trends Features Alegion
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The Marketing Artificial Intelligence Institute Singles Out Alegion

The Marketing Artificial Intelligence Institute Singles Out Alegion
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Market Watch Announces Alegion’s Acceleration Plan

Market Watch Announces Alegion’s Acceleration Plan
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Seeking Alpha Features Alegion’s Unique Position in AI Field

Seeking Alpha Features Alegion’s Unique Position in AI Field
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Yahoo! Finance Features Alegion CEO

Yahoo! Finance Features Alegion CEO
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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
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ABJ Features Alegion’s New Jobs, New Focus

ABJ notes that “CEO Nathaniel Gates expects Alegion's headcount to nearly d...
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Artificial Intelligence Startup Alegion Raises $3.6 Million

Artificial Intelligence Startup Alegion Raises $3.6 Million
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Alegion Featured in Real-Time Insights

Alegion Featured in Real-Time Insights
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First Blog Post

First Blog Post