update .md

8 files changed, 62 insertions, 20 deletions

diff --git a/site/content/pages/about/assets/adam-harvey.jpg b/site/content/pages/about/assets/adam-harvey.jpg
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+++ b/site/content/pages/about/assets/adam-harvey.jpg
diff --git a/site/content/pages/about/assets/jules-laplace.jpg b/site/content/pages/about/assets/jules-laplace.jpg
new file mode 100644
index 00000000..310b2783
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diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md
index e2025bf2..f9c6f83a 100644
--- a/site/content/pages/about/index.md
+++ b/site/content/pages/about/index.md
@@ -1,8 +1,8 @@
 ------------
 
 status: published
-title: MegaPixels Credits
-desc: MegaPixels Project Team Credits
+title: About MegaPixels
+desc: About MegaPixels
 slug: credits
 published: 2018-12-04
 updated: 2018-12-04
@@ -10,10 +10,20 @@ authors: Adam Harvey
 
 ------------
 
-# Credits
+# About MegaPixels
 
-- MegaPixels by Adam Harvey
-- Made with support from Mozilla
-- Site developed by Jules Laplace
-- Design and graphics: Adam Harvey
-- Research assistants: Berit Gilma
\ No newline at end of file
+MegaPixels aims to answers to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.
+
+MegaPixels aims to answers to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.
+
++ Years: 2002-2004
++ Datasets Analyzed: 325
++ Author: Adam Harvey
++ Development: Jules LaPlace
++ Research Assistance: Berit Gilma
+
+![Adam Harvey](assets/adam-harvey.jpg) **Adam Harvey** is an American artist and researcher based in Berlin. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund awards, and is currently a researcher in residence at Karlsruhe HfG studying artifical intelligence and datasets.
+
+![Adam Harvey](assets/jules-laplace.jpg) **Jules LaPlace** is an American technologist and artist also based in Berlin. He was previously the CTO for a NYC digital agency and currently works at VFRAME, developing computer vision for human rights groups, and as a freelance technologists for artists.
+
+**Mozilla** is a free software community founded in 1998 by members of Netscape. The Mozilla community uses, develops, spreads and supports Mozilla products, thereby promoting exclusively free software and open standards, with only minor exceptions. The community is supported institutionally by the not-for-profit Mozilla Foundation and its tax-paying subsidiary, the Mozilla Corporation.
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diff --git a/site/content/pages/about/press.md b/site/content/pages/about/press.md
index 56b4990f..2e3fa9a7 100644
--- a/site/content/pages/about/press.md
+++ b/site/content/pages/about/press.md
@@ -18,3 +18,4 @@ authors: Adam Harvey
 - Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset>
 - Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset>
 - Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset>
+lfw
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diff --git a/site/content/pages/datasets/caltech_10k/index.md b/site/content/pages/datasets/caltech_10k/index.md
new file mode 100644
index 00000000..8f49f2d1
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+++ b/site/content/pages/datasets/caltech_10k/index.md
@@ -0,0 +1,29 @@
+------------
+
+status: published
+title: Caltech 10K Faces Dataset
+desc: Caltech 10K Faces Dataset
+slug: caltech_10k
+published: 2019-2-23
+updated: 2019-2-23
+authors: Adam Harvey
+
+------------
+
+# Caltech 10K Faces Dataset
+
++ Years: TBD
++ Images: TBD
++ Identities: TBD
++ Origin: Google Search
++ Funding: TBD
+
+-------
+
+Ignore text below these lines
+
+-------
+
+Research
+
+The dataset contains images of people collected from the web by typing common given names into  Google Image Search. The coordinates of the eyes, the nose and the center of the mouth for each frontal face are provided in a ground truth file. This information can be used to align and crop the human faces or as a ground truth for a face detection algorithm. The dataset has 10,524 human faces of various resolutions and in different settings, e.g. portrait images, groups of people, etc. Profile faces or very low resolution faces are not labeled. 
\ No newline at end of file
diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md
index 1f847a2a..8b37f035 100644
--- a/site/content/pages/datasets/lfw/index.md
+++ b/site/content/pages/datasets/lfw/index.md
@@ -2,10 +2,12 @@
 
 status: published
 title: Labeled Faces in The Wild
-desc: LFW: Labeled Faces in The Wild
+desc: Labeled Faces in The Wild (LFW) is a database of face photographs designed for studying the problem of unconstrained face recognition
+subdesc: It includes 13,456 images of 4,432 people’s images copied from the Internet during 2002-2004.
 slug: lfw
 published: 2019-2-23
 updated: 2019-2-23
+color: #00FF00
 authors: Adam Harvey
 
 ------------
diff --git a/site/content/pages/info/index.md b/site/content/pages/info/index.md
index 4a65e71a..9cbb219e 100644
--- a/site/content/pages/info/index.md
+++ b/site/content/pages/info/index.md
@@ -11,7 +11,7 @@ sync: false
  
 ------------
 
-## What do facial recognition algorithms see?
+## 
 
 ```
 face_analysis
diff --git a/site/content/pages/research/00_introduction/index.md b/site/content/pages/research/00_introduction/index.md
index d3ef506b..1b784768 100644
--- a/site/content/pages/research/00_introduction/index.md
+++ b/site/content/pages/research/00_introduction/index.md
@@ -15,6 +15,16 @@ authors: Megapixels
 + Posted: Dec. 15
 + Author: Adam Harvey
 
+
+-----
+
+Ignore content below these lines
+
+-----
+
+Ever since the first computational facial recognition research project by the CIA in the early 1960s, data has always played a vital role in the development of our biometric future. Without facial recognition datasets there would be no facial recognition. Datasets are an indispensable part of any artificial intelligence system because, as Geoffrey Hinton points out, "we no longer program computers with code, we program them with data".


+
+
 It was the early 2000s. Face recognition was new and no one seemed sure exactly how well it was going to perform in practice. In theory, face recognition was poised to be a game changer, a force multiplier,  a strategic military advantage, a way to make cities safer and to secure borders. This was the future John Ashcroft demanded with the Total Information Awareness act of the 2003 and that spooks had dreamed of for decades. It was a future that academics at Carnegie Mellon Universtiy and Colorado State University would help build. It was also a future that celebrities would play a significant role in building. And to the surprise of ordinary Internet users like myself and perhaps you, it was a future that millions of Internet users would unwittingly play role in creating. 
 
 Now the future has arrived and it doesn't make sense. Facial recognition works yet it doesn't actually work. Facial recognition is cheap and accessible but also expensive and out of control. Facial recognition research has achieved headline grabbing superhuman accuracies over 99.9% yet facial recognition is also dangerously inaccurate. During a trial installation at Sudkreuz station in Berlin in 2018, 20% of the matches were wrong, a number so low that it should not have any connection to law enforcement or justice. And in London, the Metropolitan police had been using facial recognition software that mistakenly identified an alarming 98% of people as criminals [^met_police], which perhaps is a crime itself.
@@ -33,16 +43,6 @@ As McLuhan wrote, "You can't have a static, fixed position in the electric age".
 
 Like many projects, MegaPixels had spent years meandering between formats, unfeasible budgets, and was generally too niche of a subject. The basic idea for this project, as proposed to the original [Glass Room](https://tacticaltech.org/projects/the-glass-room-nyc/) installation in 2016 in NYC, was to build an interactive mirror that showed people if they had been included in the [LFW](/datasets/lfw) facial recognition dataset. The idea was based on my reaction to all the datasets I'd come across during research for the CV Dazzle project. I'd noticed strange datasets created for training and testing face detection algorithms. Most were created in labratory settings and their interpretation of face data was very strict.
 
-About the name
-
-About the funding
-
-About me
-
-About the team
-
-Conclusion
-
 
 
 ### for other post