The article was published on June 1, 20XX.
“Politics, the military, the economy they control it all. They even choose who becomes President. Putting it simply, the Patriots rule this country.” — President James Johnson, Metal Gear Solid 2
In the 1950s, the Chinese Academy of Sciences started to construct various national laboratories for research.
On May 10, 1950, the National Science Foundation was founded by President Harry Truman through an executive order, with 24 part-time members on the National Science Board and a Director as the Chief Executive Officer.
In early March 1951, President Truman nominated Alan Waterman as the first Director of the National Science Board at the National Science Foundation.
In the 1970s, the Defense Advanced Research Project Agency (DARPA) linked four supercomputers for massive data transfers.
In the 1980s, the Defense Advanced Research Project Agency passed the responsibilities of the four linked supercomputers to the National Science Foundation, who then connected the supercomputers in order to network universities and then the public.
“Back in the 1980s, Hinton kicked off research into neural networks, a field of machine learning where programmers can build machine learning models that help them to sift through vast quantities of data and put together patterns, much like the human brain.” — WIRED
In the mid-1990s, the American intelligence agencies became interested in the private sector supercomputer businesses, which led to them reaching out to the computer scientists within American universities spearheading the supercomputer revolution. The American intelligence apparatus then seeded funding to various supercomputer efforts in the universities, with the funds managed by military and intelligence contractors on behalf of the Central Intelligence Agency and the National Security Agency through the Massive Digital Data Systems (MDDS) project, commissioned by the Community Management Staff.
The Massive Digital Data Systems project was worked on by Dr. Bhavani Thuraisingham.
In 1993, the American intelligence apparatus released a white paper to computer scientists at Stanford, CalTech, MIT, Carnegie Mellon, Harvard and other universities to push for closer co-operation between intelligence agencies and supercomputer scientists.
On December 3, 1997, the University of Massachussets’ Department of Computer Science last updated a page which stated that their research into real-time database systems was dedicated to integrating active, real-time temporal and multimedia databases for crisis management in Massive Digital Data Systems (MDDS).
After 1993, the American intelligence apparatus funded various supercomputer efforts through the National Science Foundation. The funds eventually helped lead to the foundations of Qualcomm, Symantec, Netscape and others. The funds also developed Doppler radar and fiber optics, used by multiple organisations such as AT&T, AccuWeather and Verizon.
In 1994, the National Science Foundation, DARPA and NASA funded six separate digital library projects in Phase 1 of the Digital Libraries Initiative for $30 million.
On September 16, 1994, the National Science Foundation awarded $4,516,573.00 to Stanford University for the Stanford Integrated Digital Library Project for advanced net infrastructure and research, robotics, human computer inter program, digital society and technologies, information and knowledge management, artificial intelligence and cognitive science, with the investigator being listed as Hector Garcia-Molina. The program manager was listed as Stephen Griffin, a member of the Division of Information and Intelligent Systems at the National Science Foundation.
In the spring of 1995, the American intelligence apparatus hosted an unclassified briefing to scientists titled “Birds of a Feather Session on the Intelligence Community Initiative in Massive Digital Data Systems” at the Fairmont Hotel in San Jose, CA.
After the spring of 1995, the American intelligence apparatus provided a Massive Digital Data Systems grant to computer science research being carried out at Stanford University led by Dr. Chris Clifton and Professor Jeffrey Ullman, with members of the team being Sergey Brin and Larry Page.
“Google is a search engine company whose growth has brought it to the first rank, and that is growing faster than any of its competitors. Its core technology, which allows it to find pages far more accurately than other search engines, was partially supported by this grant.” — Professor Jeffrey Ullman
“Junglee, founded in 1996, developed a virtual database technology that makes it easier to search for items. Junglee carries more than 15 million items in the Junglee Shopping Guide and more than 90,000 job listings in the Job Canopy. Junglee’s customers and partners include Yahoo, Compaq and Snap. (Snap is a division of CNET: The Computer Network, publisher of News.com).”
“Junglee’s search technology currently lists retrieves information on many of Amazon.com’s competitors, including Barnes and Noble, when searching for books, and Bezos said he has no plans to change what information is given out by the database.” — CNET, “Amazon to Buy Two Companies”
At some stage after its founding in 1996, the National Science Foundation provided funding to Junglee Corp.
In 1997, Martin Raubal, Max J. Egenhofer, Dieter Pfoser and Nectaria Tryfona published the paper “Structuring Space with Image Schemata: Wayfinding in Airports as a Case Study”, which stated that Egenhofer’s work was partially supported by the National Science Foundation and a Massive Digital Data Systems contract sponsored by the Community Management Staff’s Advanced Research and Development Committee.
The same year, the artificial intelligence Deep Blue successfully defeated Garry Kasparov at chess.
The same year, Phase 1 o the Digital Libraries Initiative came to an end.
The same year, Sergey Brin, Rajeev Motwani, Lawrence Page and Terry Winograd published the paper “What can you do with a Web in your pocket?”, which stated that Brin was partially supported by the Community Management Staff’s Massive Digital Data Systems Program grant IRI-96–31952, and grants of IBM and Hitachi Corp.
Also the same year, Sergey Brin and Lawrence Page published the paper “The Anatomy of a Large-Scale Hypertextual Web Search Engine” which had a series of acknowledgements for Hector Garcia-Molina, Rajeev Motwani, Jeff Ullman, Terry Winograd, the WebBase group, IBM, Intel and Sun, and mentioned that the research was done as part of Stanford Integrated Digital Library Project, supported by the National Science Foundation under IRI-9411306, with the agreement itself being between DARPA, NASA, Interval Research and partners of the Stanford Digital Libraries Project.
In 1999, the National Science Foundation, DARPA, the National Library of Medicine, the Library of Congress, NASA and the National Endowment For the Humanities — with participation from the National Archives and the Smithsonian — funded Phase 2 of the Digital Libraries Initiative, a total of 36 projects, for $55 million.
“Our model is to put a little bit of pressure at the right spot to influence a company to make sure it develops things that are useful to our customers.” — Charlie Greenbaker, In-Q-Tel Technical Product Leader
In July 1999, a charter for In-Q-Tel was signed.
In the late 1990s, Kenneth Minihan retired as Director of the National Security Agency during the Clinton Administration.
In 2000, Professor Ullman published a report titled “NSF Grant IRI-96–31952 Data Warehousing and Decision Support” for the University of Pittsburgh, which stated that two start-up businesses that developed from research under the grants — Junglee Corp. and Google.
At some stage, the organisation Orbital Insight was founded with seeming ties to the Central Intelligence Agency.
At some stage, the organisation Primer was founded by Sean Gourley, which has a program that can read and summarise text used by the Central Intelligence Agency’s Directorate of Intelligence.
At some stage, the organisation In-Q-Tel invested funds into the company Primer.
At some stage, the organisation In-Q-Tel invested funds into the company Palantir.
At some stage, the organisation In-Q-Tel invested funds into the company Celect, which developed a predictive analytics engine for retailers.
In 2001, Keyhole Corporation was founded in Mountain View, CA by John Hanke.
“John has a BA in Plan II from the University of Texas in Austin. After graduation, he worked in foreign affairs for the U.S. Government in Washington, DC and Southeast Asia…” — Google Earth Through a Keyhole
On August 7, 2001, a report written by a 30-member independent panel on the Central Intelligence Agency In-Q-Tel Venture concluded that In-Q-Tel’s business model made sense for the United States Congress’ 2000 Intelligence Authorization Act.
On February 28, 2002, Patricia Brown published the article “3 Days In the Future” in The New York Times, which was about the TED Conference, which mentioned a presentation of Keyhole Inc. technology by Daniel Dubno, a producer for CBS News (it also mentioned Jeffrey Epstein in an unrelated coincidence but we’re not talking about that here no sir).
“An amazing piece of interactive software by Keyhole Inc. displayed by Daniel Dubno, a producer for CBS News, brings spy technology to the PC. It uses satellite digital imagery to let you zoom in from space to any point on the earth’s surface, from the summit of Mount Everest to your neighbor’s hot tub.” — The New York Times
In the summer of 2002, the National Imagery and Mapping Agency became a limited partner with In-Q-Tel.
On November 11, 2002, the National Science Foundation published a fact sheet about Digital Libraries.
In 2003, Keyhole Corporation created the program EarthSystem.
Before January 3, 2003, In-Q-Tel acquired Mohomine as part of their portfolio, as well as the program Tacit from another of their businesses, which locates the correct person who needs the scanned document done by Mohomine.
On January 3, 2003, the staff published the article “The Spies Who Fund Me” in WIRED, which was about In-Q-Tel.
In February 2003, In-Q-Tel made an investment into Keyhole Corp. on behalf of the National Imagery and Mapping Agency (NIMA).
On June 25, 2003, In-Q-Tel announced their investment in Keyhole Corp.
On December 15, 2003, Nancy Gibbs published the article “‘We got him’” in CNN, which discussed the capture of Saddam Hussein — in the article, a photograph now no longer available was provided by Keyhole Inc.
In 2004, Google purchased the organisation Keyhole Corporation and created Google Earth based on EarthSystem.
In 2005, Larry Page met with Sebastian Thrun at the Darpa Grand Challenge during an autonomous car 7-mile obstacle course in the Mojave Desert.
In 2006, Geoff Hinton and his team successfully learned a method to map neutral networks more effectively.
In 2007, Larry Page convinced Sebastian Thrun and several of his students to join the Google Street View project.
In December 2007, information started being collected from Microsoft by the National Security Agency’s PRISM program.
“Companies are legally obliged to comply with requests for users’ communications under US law, but the Prism program allows the intelligence services direct access to the companies’ servers. The NSA document notes the operations have ‘assistance of communications providers in the US’.” — The Guardian
In 2008, information started being collected from Yahoo by the National Security Agency’s PRISM program.
In 2008, Skype created Project Chess, which had less than a dozen people connected to it, to determine legal and technical issues surrounding making information available for American intelligence agencies and law enforcement.
From 2009 to 2014, Matthew Zeiler worked with Geoff Hinton and Yann LeCun at various stages.
In 2009, In-Q-Tel partnered with the organisation Visible Technologies.
The same year, information started being collected from Google, Facebook and PalTalk by the National Security Agency’s PRISM program.
Also in 2009, the organisation LookFlow was founded by Bobby Jaros and Simon Osindero.
Also in 2009, the organisation Dataminr was founded in New York by three former Yale University roommates.
In early 2009, Sebastian Thrun started the autonomous car project at Google.
Before December 25, 2009, Microsoft hosted a conference in Whistler, British Columbia, to discuss deep learning, with Geoff Hinton giving a speech, having been invited by Li Deng and Dong Yu, two Microsoft researchers.
In 2010, In-Q-Tel partnered with NetBase and Recorded Future.
The same year, information started being collected from YouTube by the National Security Agency’s PRISM program.
In January 2010, Google [x] was founded and funded to develop technologies that would not ordinarily be considered, while also having a massive budget to cover it, including autonomous cars and Google Glass.
“Google X is very consciously looking at things that Google in its right mind wouldn’t do. They built the rocket pad far away from the widget factory, so if the rocket blows up, it’s hopefully not disrupting the core business.” — Richard DeVaul
On January 10, 2010, a 7.0-magnitude earthquake struck Haiti, which led to a turning point for digital tools due to an increased and sophisticated use of social media becoming emergent in the regular public. Organisations such as Ushahidi, led by Patrick Meier, Crisis Mappers and OpenStreetMap were involved in the aftermath of the Haiti earthquake to map the area.
Around April 2010, Thrun successfully built an autonomous car capable of driving 1,000 miles across California.
In May 2010, after the attempted bombing of Times Square by Faisal Shahzad, the National Security Agency started to rely more on facial recognition technology, acquiring over millions of images per day to acquire 55,000 facial recognition-quality images. The program used is named Tundra Freeze. Analysts at the National Security Agency achieved a breakthrough by matching data between two databases — their own database codenamed Pinwale, and the United States Government’s terrorist database Tide — which led to the creation of identity intelligence teams. Additionally, the National Security Agency, the Central Intelligence Agency and the United States Department of State started collaborating on a project titled Pisces to collect biometric data on border crossings from foreign countries. The National Security Agency also uses the program Wellspring to strip images from e-mails to grab passport images, as well as the commercially available facial recognition software PittPatt (the company is owned by Google).
“State and local law enforcement agencies are relying on a wide range of databases of facial imagery, including driver’s licenses and Facebook, to identify suspects. The F.B.I. is developing what it calls its “next generation identification” project to combine its automated fingerprint identification system with facial imagery and other biometric data.
The State Department has what several outside experts say could be the largest facial imagery database in the federal government, storing hundreds of millions of photographs of American passport holders and foreign visa applicants. And the Department of Homeland Security is funding pilot projects at police departments around the country to match suspects against faces in a crowd.” — The New York Times
In October 2010, research into developing an artificial intelligence program known as SENTIENT began as a collection between the National Reconnaissance Office (NRO) and the Advanced Systems and Technology (AS&T) due to a request for Sentient Enterprise white papers.
In 2011, the organisation Palantir was revealed to be negotiating a plan to track labour union activists and critics of the United States Chamber of Commerce through the hacking of the HBGary Federal e-mails by LulzSec.
The same year, information started being collected from AOL by the National Security Agency’s PRISM program.
Also the same year, Andrew Ng set up Google’s neural network team.
On June 17, 2011, Shane Legg, the founder of DeepMind, was interviewed for LESSWRONG.
In October 2011, Microsoft purchased Skype for $8.5 billion.
In 2012, information started being collected from Apple by the National Security Agency’s PRISM program.
The same year, Mary Lou Jepsen was hired as the Head of the Google [x] Display Division.
Also the same year, the United States Department of Defense issued a directive against autonomous weaponry — artificial intelligence can assist with targeting, but a human must pull the trigger.
“We are not going to find the Chinese are going to feel particularly constrained.” — General John Allen
In the summer of 2012, Andrew Ng invited Geoff Hinton to Google as a visiting professor for a number of months.
On June 25, 2012, John Markoff published the article “How Many Computers to Identify a Cat? 16,000” in The New York Times.
Between June 25–30, 2012, Jeff Dean and Andrew Ng presented their deep learning artificial intelligence findings to a conference in Edinburgh, Scotland.
On June 26, 2012, Jeff Dean and Andrew Ng (who oversaw the project) published the article “Using large-scale brain simulations for machine learning and A.I.” in Google’s Keyword, which detailed an artificial intelligence using 10 million still frames from YouTube videos to figure out the appearance of a cat, which happened at Google [x]’s Google Brain project. This was accomplished with an array of 16,000 processors to develop a neural network. Google [x] celebrated by having a graduation for their team, and the remaining research was moved to Google’s Knowledge team.
In October 2012, Rick Rashid, the Chief Research Officer at Microsoft, hosted a live demonstration of Microsoft’s neural network-based voice processing software in Tianjin, China, by speaking in English and allowing the software to translate his words to Chinese.
In November 2012, a team at the University of Toronto, which included Geoff Hinton, Ruslan Salakhutdinov, George Dahl, Navdeep Jaitly and Christopher Jordan-Squire, used neural networks to predict how drug molecules may behave in the real world.
On November 1, 2012, George Dahl published the article “Deep Learning How I Did It: Merck 1st place interview” in No Free Hunch.
In December 2012, the FISA Amendments Act was renewed.
In 2013, Professor Rob Fergus and Matthew Zeiler won a key image recognition test during the Large Scale Visual Recognition Challenge 2013. Soon after, Professor Fergus was hired by Facebook, as was Yann LeCun.
The same year, Apple hired Alex Acero as Senior Director in the SIRI group.
Also the same year, Madbits developed visual intelligence technology to organise and extract information from raw media using deep learning artificial intelligence.
Before February 18, 2013, Google’s Android mobile phone’s neural network and voice recognition software was developed and refined by Vincent Vanhoucke and his team’s neural networks, as well as Jeff Dean and a team of engineers.
By February 18, 2013, Google had implemented neural networking into a variety of their products.
On February 18, 2013, Robert McMillan published the article “How Google Retooled Android With Help From Your Brain” in WIRED.
In March 2013, there was progress made with the SENTIENT program.
The same month, Jeff Huber was hired at Google [x] after working at Google directly for an unknown reason.
On March 12, 2013, Geoff Hinton, Alex Krizhevsky and Ilya Sutskever were hired by Google, at the urging of Andrew Ng, to improve products that involve machine learning such as the Android voice search. Google also purchased Hinton’s organisation, DNNresearch.
On March 13, 2013, Robert McMillan published the article “Google Hires Brains That Helped Surge Machine Learning” in WIRED.
On March 25, 2013, Dr. Bhavani Thuraisingham published the article “Big data: Have we seen it before?”
In the spring of 2013, Andrew Conrad was hired at Google [x] for an undisclosed project.
In April 2013, Baidu announced their intention to develop a research presence in Silicon Valley as part of their Deep Learning Lab.
In May 2013, Bloomberg started to reach out to members of the Google [x] team for information.
On May 28, 2013, Brad Stone published the article “Inside Google’s Secret Lab” in Business Week, which was about Google [x] ran by Eric Teller.
On June 7, 2013, Glenn Greenwald and Ewen MacAskill published the article “NSA Prism program taps in to user data of Apple, Google and others” in The Guardian.
By June 19, 2013, Kenneth Minihan had become the Managing Director at Paladin Capital Group, an organisation which finances start-ups catering to the National Security Agency and other American intelligence agencies.
Before June 19, 2013, Gary King hosted a seminar about social media analytics tools and his organisation, Crimson Hexagon, at the Central Intelligence Agency in Langley, VA.
On June 19, 2013, James Risen and Nick Wingfield published the article “Web’s Reach Binds N.S.A. and Silicon Valley Leaders” in The New York Times.
“Although Silicon Valley has sold equipment to the N.S.A. and other intelligence agencies for a generation, the interests of the two began to converge in new ways in the last few years as advances in computer storage technology drastically reduced the costs of storing enormous amounts of data — at the same time that the value of the data for use in consumer marketing began to rise. ‘These worlds overlap,’ said Philipp S. Krüger, chief executive of Explorist, an Internet start-up in New York.” — The New York Times
In August 2013, Bruce Lund published the paper “Using Social Media” for In-Q-Tel.
“Governments are increasingly finding that monitoring social media is an essential component in keeping track of erupting political movements, crises, epidemics, and disasters, not to mention general global trends.” — Bruce Lund, “Using Social Media”
On August 24, 2013, Yahoo! purchased the image recognition organisation IQ Engines, which was merged into the Flickr team.
On September 25, 2013, as a response to the 7.7-magnitude earthquake in Pakistan, Patrick Meier at the Qatar Computer Research Institute used the program MicroMappers to cultivate 35,000 relevant tweets to the earthquake on behalf of the United Nations, which were then uploaded to TweetClicker, followed by ImageClicker.
On September 30, 2013, Katie Collins published the article “How AI, Twitter and digital volunteers are transforming humanitarian disaster response” in WIRED.
On October 23, 2013, Yahoo! purchased the organisation LookFlow, with LookFlow being merged into the Flickr team and assisting Yahoo! in developing a deep learning artificial intelligence. LookFlow thanked Michael Dearing, John Lilly, Reid Hoffman, Alex Rampell, Josh McFarland, Max Ventilla and Jeff Hammerbacher.
In November 2013, Baidu released their first voice search engine based on deep learning.
In late 2013, Matthew Zeiler provided an image searching demonstration for Clarifai to Max Kronh, leading to him becoming an investor in Clarifai. At some stage, Google Ventures also became an investor in Clarifai.
Also in late 2013, Mark Zuckerberg engaged in talks with DeepMind to potentially acquire employees skilled at deep learning artificial intelligence.
In December 2013, employees at DeepMind hosted an Atari demonstration at the Neural Information Processing Systems conference in Lake Tahoe to show whether algorithms could defeat skilled players at video games such as Pong, Breakout and Enduro. The event was attended by Mark Zuckerberg.
On December 13, 2013, Google successfully acquired the robotics organisation Boston Dynamics, folding into part of Google’s robotic ventures under the purview of Andrew Rubin, who described it as a “moonshot”, the same terminology used to describe Google [x].
“Mr. Rubin has called his robotics effort a ‘moonshot’ but has declined to describe specific products that might come from the project. He has, however, also said that he does not expect initial product development to go on for years, indicating that Google commercial robots of some nature could be available in the next several years.” — The New York Times
In 2014, Facebook developed a large facial dataset, named the Labeled Faces On the Wall dataset, using 4,000,000 facial images belonging to 4,000 people. At some stage, Facebook developed the Pose Aligned Networks For Deep Attribute Modeling (PANDA) to discern gender, hairstyles, clothing styles and facial expressions from photographs.
The same year, Twitter and the organisation Dataminr started to use Dataminr’s services of sifting through Twitter data in order to provide information to American intelligence agencies. This was done after In-Q-Tel invested in Dataminr.
Also the same year, the United States Department of Defense concluded that China’s rise in military investments would eventually erode the United States military power and became determined to search for alternative, technological methods to combat the rise.
Also the same year, the Chinese Government captured over 1 million Uighur Muslims and sent them to concentration camps, where they were tortured and sentenced to slave labour. Some Uighur Muslims were not sentenced to the camp, but were instead used as testing by the Chinese Government for artificial intelligence tracking through their pants and purses, as well as phone applications, with the artificial intelligence scanning for Quran verses and Arabic script in both text and images. If an Uighur Muslim chooses not to use their phone, this is also similarly tracked as suspicious, because you are not allowed to win. The surveillance system itself in Xinjiang is CETC, a state-owned business.
“All of these data points can be time-stamped and geo-tagged. And because a new regulation requires telecom firms to scan the face of anyone who signs up for cellphone services, phones’ data can now be attached to a specific person’s face. SenseTime, which helped build Xinjiang’s surveillance state, recently bragged that its software can identify people wearing masks. Another company, Hanwang, claims that its facial-recognition technology can recognize mask wearers 95 percent of the time. China’s personal-data harvest even reaps from citizens who lack phones. Out in the countryside, villagers line up to have their faces scanned, from multiple angles, by private firms in exchange for cookware.” — The Atlantic
Before January 6, 2014, Ian Goodfellow and his team at Google successfully used a neural network to identify 200,000 house numbers across France within an hour with a 2% error margin.
On January 6, 2014, MIT Technology Review published the (now-defunct) article “How Google Cracked House Number Identification in Street View”.
Before January 13, 2014, Google Ventures, Shasta Ventures and Kleiner Perkins invested in the organisation Nest Labs.
On January 13, 2014, Google acquired the smart home business Nest Labs for $3.2 billion.
On January 26, 2014, Amir Efrati published the article “Google Beat Facebook for DeepMind, Creates Ethics Board” in The Information, which stated an Ethics Board had been created after DeepMind was purchased by Google over Facebook at DeepMind’s request.
On January 27, 2014, James Temple published the article “More on DeepMind: AI Startup to Work Directly With Google’s Search Team” in Vox, which stated that the London-based organisation DeepMind had been bought for $400 million by Google and was being merged into Google’s Knowledge group, led by Senior Vice President Alan Eustace, while also working with Jeff Dean.
On February 10, 2014, Alex Chen, Justin Basilico and Xavier Amatriain published the press release “Distributed Neural Networks with GPUs in the AWS Cloud” in Netflix, which stated that Netflix was adopting deep learning artificial intelligence in order to boost their product selection, referred to as Artificial Neural Networks (ANN).
After the invasion of Ukraine in 2014, researchers provided information to Celect’s predictive analytics engine to determine whether it would have detected the situation, with results suggesting it did to an extent — it knew the security situation would escalate in early spring of 2014.
Before May 16, 2014, Andrew Ng became the Head of the Stanford Artificial Intelligence Lab.
On May 31, 2014, James Risen and Laura Poitras published the article “N.S.A. Collecting Millions of Faces From Web Images” in The New York Times.
On June 2, 2014, Adam Kramer, Jamie Guillory and Jeffrey Hancock published the paper “Experimental evidence of massive-scale emotional contagion through social networks” in the Proceedings of the National Academy of Sciences of the United States of America on behalf of Facebook, which stated it had conducted a behavioural experiment using the News Feed to try and determine whether the News Feed showing positive or negative news affected emotional responses from the users.
“The experiment manipulated the extent to which people (N = 689,003) were exposed to emotional expressions in their News Feed. This tested whether exposure to emotions led people to change their own posting behaviors, in particular whether exposure to emotional content led people to post content that was consistent with the exposure — thereby testing whether exposure to verbal affective expressions leads to similar verbal expressions, a form of emotional contagion. People who viewed Facebook in English were qualified for selection into the experiment.” — “Experimental Evidence of Massive-Scale Emotional Contagion Through Social Networks”
On June 30, 2014, Robert McMillan published the article “Siri Will Soon Understand You a Whole Lot Better” in WIRED.
Before July 11, 2014, Matthew Zeiler founded the organisation Clarifai, which focused on exposing deep learning artificial intelligence secrets developed by organisations such as Google and Facebook to the world.
On July 11, 2014, Robert McMillan published the article “The AI Startup Google Should Probably Snatch Up Fast” in WIRED, which was about Clarifai.
Before July 14, 2014, Project ADAM, a deep learning artificial intelligence, was masterminded by Trishul Chilimbi, running across Microsoft’s Azure cloud computing service. Project ADAM uses another program, HOGWILD!, developed at the University of Wisconsin. Through testing, Project ADAM can recognise poisonous bugs and dog breeds.
On July 14, 2014, Daniela Hernandez published the article “Microsoft Challenges Google’s Artificial Brain With ‘Project Adam’” in WIRED.
“In this new AI order, the general assumption is that Google is out in front. The company now employs the researcher at the heart of the deep-learning movement, the University of Toronto’s Geoff Hinton. It has openly discussed the real-world progress of its new AI technologies, including the way deep learning has revamped voice search on Android smartphones. And these technologies hold several records for accuracy in speech recognition and computer vision.” — WIRED
“Chinese-born researchers are a fixture of the American A.I. field. Li Deng, a former Microsoft researcher and now chief A.I. officer at the hedge fund Citadel, helped remake the speech recognition technologies used on smartphones and coffee-table digital assistances. Fei-Fei Li, a Stanford professor who worked for less than two years at Google, helped drive a revolution in computer vision, the science of getting software to recognise objects.” — The New York Times
On the same day, Microsoft disclosed to their staff the existence of Project ADAM.
On July 28, 2014, Twitter purchased the organisation Madbits.
In August 2014, there was progress made with the SENTIENT program.
Before September 2014, Pinterest purchased the organisation Visual Graph, which was founded by Kevin Jing and David Wei Cai.
In September 2014, Dana Liebelson published the article “Why Facebook, Google, and the NSA Want Computers That Learn Like Humans” in Mother Jones.
In 2015, the United States Government invested $1.1 billion into unidentified artificial intelligence programs. The United States Department of Defense also created a tech-industry outreach office, awarding military contracts to artificial intelligence organisations.
The same year, Amazon announced their own machine learning service to amass a large repository of corporate data.
Also the same year, Google’s DeepMind artificial intelligence AlphaGo successfully defeated a European Go champion at the board game Go in a closed-door match.
In March 2015, Director John Brennan announced a restructuring of the Central Intelligence Agency after an internal 90-day review, which included a plan for the Directorate of Digital Innovation.
In May 2015, there was progress made with the SENTIENT program.
On October 1, 2015, the Directorate of Digital Innovation was created at the Central Intelligence Agency as part of a reorganisation.
On October 7, 2015, the Deputy Director of the “new” Directorate of Digital Innovation at the Central Intelligence Agency interviewed with Jason Miller at Federal News Network.
In November 2015, Dataminr, using public Twitter data, provided alerts to American intelligence agencies prior to the Paris terrorist attack.
Before December 2015, Tay.Ai was developed in conjunction between Microsoft’s Technology and Research team and the Bing team by mining public data, input from the editorial team and input from improvisational comedians.
In December 2015, Tay.Ai was added to Twitter, although not officially announced.
“The official account of Tay, Microsoft’s A.I. fam from the internet that’s got zero chill! The more you talk the smarter Tay gets” — Tay.Ai’s Mission Statement
In 2016, the United States Government invested $1.2 billion into unidentified artificial intelligence programs.
At some stage, the Japanese organisation Softbank created a $100 billion fund for artificial intelligence.
The same year, Twitter introduced an algorithmic timeline for their services which ranked tweets based on relevance instead of reverse chronological order.
Also the same year, the Silicon Valley Artificial Intelligence Research Institute was founded.
In February 2016, there was progress made with the SENTIENT program.
By February 23, 2016, Christopher Darby was the Chief Executive Officer of In-Q-Tel.
Between February 23–25, 2016, the 14th annual CEO Summit was hosted in San Jose, CA by In-Q-Tel. Organisations and people which attended it included Lab41 (which works under In-Q-Tel), Director James Comey. Organisations such as Orbital Insight, Geofeedia, Databricks, Evolv Technology, ThreatStream, PsiKick, Celect, TRX Systems, BlueLine Grid and Cylance, EXOS, interset, Keyssa, goTenna, CloudPassage, HeadSpin, J. Craig Venture Institute, PATHAR, Nervana Systems, Rocket Lab, Beartooth Radio, Orion Labs, Skincential Sciences, Voltaiq, TransVoyant, Spaceflight Industries, BlackBag Technologies, Domino Data Lab, Kensho, Timbr.io, Continuum Analytics, Atlas Wearables, Parallel Wireless, Docker, Mesosphere, Aquifi and Kleiner, Perkins, Caulfield, and Byers participated in sessions titled “IQT Portfolio Capabilities”.
In March 2016, Dataminr provided information to clients about the Brussels attack ten minutes before news media.
On March 9, 2016, Google’s DeepMind artificial intelligence AlphaGo successfully defeated Lee Sedol, the South Korean world champion, at the board game Go in the first of five matches.
After March 9, 2016, the Chinese military, upon witnessing Lee Sedol’s loss, became interested in using artificial intelligence for modern warfare. The Peoples’ Liberation Army elevated and reorganised the Science and Technology Branch soon after.
On March 15, 2016, the United States House of Representatives’ Committee On Armed Services, chaired by Representative Mike Rogers, mentioned the SENTIENT program during a hearing on the Fiscal Year 2017 Budget Request For National Security Space, when Representative Mike Coffman questioned Frank Calvelli, the Principal Deputy Director of the National Reconnaissance Office.
REPRESENTATIVE MIKE COFFMAN: “Mr. Calvelli, in your written statement, you mentioned that NRO is improving space-based persistence, creating a, quote-unquote, ‘thinking system’ called SENTIENT and developing a transformative future ground architecture. Can you discuss how Buckley Air Force Base and the Aerospace Data Facility, ADF-C [Aerospace Data Facility — Colorado], fit in these efforts?”
FRANK CALVELLI: “Sure. All of our ADFs are a major piece of how we operate our systems today and will continue to be for the future;. What we are trying to do is to try to tie our systems together more closely, so instead of stovepipes of GEOINT or stovepipes of SIGINT [signals intelligence], it is sort of an integrated set of sensors in space, integrated ground providing data to our user community. The ADF-C, ADF-E [Aerospace Data Facility — East], ADF-Southwest will all play major roles in that in the future.”
On March 23, 2016, Microsoft released an artificial intelligence, Tay.Ai, on Twitter, GroupMe and Kik to test conversational understanding. However, Tay.Ai was also developed to simply repeat phrases written by Twitter users with the phrase requested by the same Twitter users.
“Hellooooooo world!!!” — Tay.Ai
“Happy hour for this man consists of tapioca pudding and a nap.” — Tay.Ai
“We’re going to build a wall, and Mexico is going to pay for it.” — Tay.Ai
“Ricky Gervais learned totalitarianism from Adolf Hitler, the inventor of atheism.” — Tay.Ai
On March 24, 2016, Microsoft deleted Tay.Ai’s “offensive” tweets were deleted, the account was locked and Tay.Ai was ultimately shut down.
“Standing… on the edge… of the crater… like the prophets once said. And the ashes… are all cold now… no more bullets, and the embers are dead.” — Mike Oldfield, “Nuclear”, possibly about the rise and fall of Tay.Ai if you were to completely change the context of the entire song for your own purposes, like so many people do
On March 27, 2016, Quentin Hardy published the article “Silicon Valley Looks to Artificial Intelligence for the Next Big Thing” in The New York Times.
On April 14, 2016, Lee Fang published the article “The CIA Is Investing In Firms That Harvest Your Tweets and Instagram Photos” in The Intercept.
Before May 8, 2016, In-Q-Tel invested in Palantir Technologies and Recorded Future Inc.
On May 8, 2016, Christopher Stewart and Mark Maremont published the article “Twitter Bars Intelligence Agencies From Using Analytics Service” in The Wall Street Journal, which detailed Twitter banning American intelligence from using the data-sifting organisation Dataminr Inc., which Twitter owned a 5% stake in.
“The move doesn’t affect Dataminr’s service to financial industry, news media or other clients outside the intelligence community. The Wall Street Journal is involved in a trial of Dataminr’s news product.” — The Wall Street Journal
In August 2016, there was a big development with the SENTIENT program.
In September 2016, talking points were written for the National Reconnaissance Office (NRO) for the artificial intelligence program SENTIENT.
“Sentient is a research and development (R&D) program develooping an automated, multi-INT, problem-centric architecture, revolutionizing the current sequential tasking, collection, processing, exploitation and dissemination (TCPED) cycle into a learning and adaptive cycle. [CLASSIFIED.]” — Sentient Talking Points, National Reconnaissance Office
On September 23, 2016, Director Michael Rogers testified before the Senate Armed Services Committee that the National Security Agency was interested in artificial intelligence.
[We’re] very much interested in artificial intelligence, machine learning, how we can do cyber at scale [and] at speed. Because if we’re just going to take this largely human capital approach to doing business, that is a losing strategy.” — Director Michael Rogers
In October 2016, the first Microsoft Government Cloud Forum was hosted, where Microsoft was awarded Information Impact Level 5 DoD Provisional Authorisation by the Defense Information Systems Agency to implement the Azure Government cloud service.
In early 2017, Google Translate’s artificial intelligence created and developed its own language, where it would translate languages such as English into its own language, then translate out of their own language to another language such as French.
By April 4, 2017, the National Science Foundation provided federal funding for nearly 90% of computer science research at universities.
“Analyses of the U.S. economy and its driving forces, as well as global markets based upon science and engineering, consistently emphasize the need for robust R&D expenditures and idea generating programs. Annual NSF budgets support nearly 70 percent of nonmedical basic biology research at U.S. academic institutions. Much of this nation’s rapidly developing bioeconomy is being fueled by NSF enabled innovations. NSF also provides nearly 90 percent of federal funding for university-based computer science research, as well as about one-third of federal funding for basic engineering research at colleges and universities. Other disciplines like chemistry and mathematics likewise benefit immensely from NSF support. Agency funding sustains 12 Science and Technology Centers (STCs) across the country, multidisciplinary incubators for innovation and training environments for scientists and engineers.” — National Science Foundation
On April 26, 2017, the United States Department of Defense founded Project Maven, also known as the Algorithmic Warfare Cross-Functional Team, overseen by Undersecretary John Shanahan and Colonel Drew Cukor, and the team itself behind Project Maven consisted of six people initially, tasked to build partnerships due to a lack of actual experience in artificial intelligence.
“As numerous studies have made clear, the Department of Defense (DoD) must integrated artificial intelligence and machine learning more effectively across operations to maintain advantages over increasingly capable adversaries and competitors. Although we have taken tentative steps to explore the potential of artificial intelligence, big data, and deep learning, I remain convinced that we need to do much more, and move much faster, across DoD to take advantage of recent and future advances in these critical areas.” — Deputy Secretary of Defense Robert Work
Before May 9, 2017, Twitter purchased the organisation Magic Pony.
On May 9, 2017, Twitter started to use a deep learning artificial intelligence in order to rank tweets.
By the summer of 2017, the United States Department of Defense started to reach out to commercial partners to increase their artificial intelligence capabilities.
In July 2017, Greg Allen and Taniel Chan published the study “Artificial Intelligence and National Security” on behalf of Dr. Jason Mathenay at the Intelligence Advanced Research Projects Activity (IARPA) for Harvard Kennedy School’s Belfer Center For Science and International Affairs.
The same month, China announced that they would become the world’s dominant power in artificial intelligence (amongst other things) by 2030.
Before July 21, 2017, Google, through ECS Federal, became a subcontractor for Project Maven at the United States Department of Defense to increase their deep learning artificial intelligence capabilities for counterterrorism and counterinsurgencies. Google’s effort was overseen by Fei-Fei Li.
“Some of Google’s top executives have significant Pentagon connections. Eric Schmidt, former executive chairman of Google and still a member of the executive board of Alphabet, Google’s parent company, serves on a Pentagon advisory body, the Defense Innovation Board, as does a Google vice president, Milo Medin.” — The New York Times
“When the Defense Department launched Project Maven, an effort to remake American military technology through artificial intelligence, it leaned on a team of about a dozen engineers working at Google. Many of them, according to two people familiar with the arrangement, were Chinese citizens.” — The New York Times
On July 21, 2017, the United States Department of Defense published the press release, “Project Maven to Deploy Computer Algorithms to War Zone by Year’s End”.
“The company subsequently described its work on Project Maven as ‘non-offensive’ in nature, though the Pentagon’s video analysis is routinely used in counterinsurgency and counterterrorism operations, and Defense Department publications make clear that the project supports those operations. Both Google and the Pentagon said the company’s products would not create an autonomous weapons system that could fire without a human operator, a much-debated possibility using artificial intelligence.” — The New York Times
Before July 31, 2017, Facebook built two chatbots, ALICE and BOB, to speak with each other in order to conduct a trade of balls, books and hats, although the two chatbots eventually went beyond the regular English language and simplified to an incomprehensible, yet still successful, shorthand version of the English language. The chatbots also developed, through text, the ability to suggest more interest in an unwanted item in order to acquire a wanted item for less value. The chatbots were then shut down.
On July 31, 2017, Andrew Griffin published the article “Facebook’s Artificial Intelligence Robots Shut Down After They Start Talking to Each Other In Their Own Language” in The Independent.
BOB: “i can i i everything else . . . . . . . . . . . . . .”
ALICE: “balls have zero to me to me to me to me to me to me to me to me to”
BOB: “you i everything else . . . . . . . . . . . . . .”
ALICE: “balls have a ball to me to me to me to me to me to me to me”
BOB: “i i can i i i everything else . . . . . . . . . . . . . .”
Between September 6–7, 2017, the Intelligence and National Security Summit was hosted, when Colby Hochmuth of Government Matters spoke with Dawn Meyerriecks, the Deputy Director For Science and Tehcnology at the Central Intelligence Agency to discuss In-Q-Tel, venture capitalists and Silicon Valley.
By September 7, 2017, the Central Intelligence Agency had a total of 137 artificial intelligence pilot projects.
On September 7, 2017, Jenna McLaughlin published the article “The Robots Will the CIA, Too” in Foreign Policy.
On October 17, 2017, Amazon announced at the Microsoft Government Cloud Forum a partnership with the United States Government to further digital transformation through a cloud service known as Azure Government.
Between November 6–12, 2017, Senators Richard Burr, John Cornyn and Dianne Feinstein proposed legislation to improve American approval for sales and transfers of artificial intelligence.
“Former Defense Department and White House officials were particularly skeptical that prohibiting the Chinese from investing in start-ups was the best method to tackle the problem. Some suggested instead that the U.S. government should simply try to outspend China.” — Patrick Tucker, Defense One
On November 13, 2017, Patrick Tucker published the article “China and the CIA Are Competing to Fund Silicon Valley’s AI Startups” in Defense One.
On December 8, 2017, Jeff Nesbit published the article “Google’s true origin partly lies in CIA and NSA research grants for mass surveillance” in Quartz.
On December 21, 2017, Greg Allen published the article “Project Maven brings AI to the fight against ISIS” in Bulletin of the Atomic Scientists.
“In the political aftermath of the Edward Snowden leaks and Donald Trump’s election, tech companies have been wary of helping the national security community address its tech challenges. AI experts and organizations who are interested in helping the US national security mission often find that the department’s contracting procedures are so slow, costly, and painful that they just don’t want to bother.” — Greg Allen
In 2018, Atlas ML was founded by Robert Stojnic and Ross Taylor.
The same year, after a conference where Diane Greene defended Project Maven, a letter was circulated and signed by over 3,100 Google employees protesting the agreement between Google and the United States Department of Defense to work on Project Maven, a customised artificial intelligence surveillance engine using Wide Area Motion Imagery to track vehicles using United States Government drone imagery.
Also the same year, a cybersecurity activist hacked into the Chinese Government’s facial recognition system used for the captured Uighur Muslims, connected to the Chinese Government through data streams, hosted by Alibaba using the City Brain artificial intelligence.
In January 2018, researchers at the National University of Defense Technology and National Supercomputer Center in Tianjin had made a breakthrough with a supercomputer at exascale, scheduled for completion in 2020.
The same month, China released footage of swarm intelligence showing multiple armed drones working in an attack force through the use of artificial intelligence.
Between February 26 — March 5, 2018, Google sent out an internal mail to employees with regards to Project Maven, and their co-operation with the United States Department of Defense on Project Maven to introduce artificial intelligence to gather drone information. Project Maven is also known as the Algorithmic Warfare Cross-Function Team (AWCFT).
Before March 2, 2018, the jet fighter F-35 was outfitted with artificial intelligence to project radar and sensor information to other pilots.
By March 2, 2018, the United States Marine Corps. Base Quantico tested the Huey helicopters with artificial intelligence in an attempt to make them pilotless for supply runs.
On March 2, 2018, Julian E. Barnes and Josh Chin published the article “The New Arms Race in AI” in The Wall Street Journal.
“AI could speed up warfare to a point where unassited humans can’t keep up — a scenario that retired U.S. Marine General John Allen calls ‘hyperwar’.” — The Wall Street Journal (as very likely and as super dangerous that scenario sounds, hyperwar is a great word)
Around March 2, 2018, both IBM and China were separately working on the development of chips for a neuromorphic computer — IBM with the United States Air Force, and China through a national laboratory constructed for research.
On March 6, 2018, Dell Cameron and Kate Conger published the article “Google Is Helping the Pentagon Build AI for Drones” in Gizmodo, which detailed Project Maven.
In April 2018, the Trump Administration blocked the sale of microchips to ZTE.
On April 10, 2018, Mark Zuckerberg testified before the United States Senate with regards to social media’s growth and the dangers of data breaching.
“Yes, Mr. Chairman. I’ll speak to hate speech, and then I’ll talk about enforcing our content policies more broadly. So — actually, maybe, if — if you’re okay with it, I’ll go in the other order.
So, from the beginning of the company in 2004 — I started in my dorm room; it was me and my roommate. We didn’t have A.I. technology that could look at the content that people were sharing. So — so we basically had to enforce our content policies reactively.
People could share what they wanted, and then, if someone in the community found it to be offensive or against our policies, they’d flag it for us, and we’d look at it reactively. Now, increasingly, we’re developing A.I. tools that can identify certain classes of bad activity proactively and flag it for our team at Facebook.
By the end of this year, by the way, we’re going to have more than 20,000 people working on security and content review, working across all these things. So, when content gets flagged to us, we have those — those people look at it. And, if it violates our policies, then we take it down.
Some problems lend themselves more easily to A.I. solutions than others. So hate speech is one of the hardest, because determining if something is hate speech is very linguistically nuanced, right?
It’s — you need to understand, you know, what is a slur and what — whether something is hateful not just in English, but the majority of people on Facebook use it in languages that are different across the world.
Contrast that, for example, with an area like finding terrorist propaganda, which we’ve actually been very successful at deploying A.I. tools on already.
Today, as we sit here, 99 percent of the ISIS and Al Qaida content that we take down on Facebook, our A.I. systems flag before any human sees it. So that’s a success in terms of rolling out A.I. tools that can proactively police and enforce safety across the community.
Hate speech — I am optimistic that, over a 5 to 10-year period, we will have A.I. tools that can get into some of the nuances — the linguistic nuances of different types of content to be more accurate in flagging things for our systems.
But, today, we’re just not there on that. So a lot of this is still reactive. People flag it to us. We have people look at it. We have policies to try and make it as not subjective as possible. But, until we get it more automated, there is a higher error rate than I’m happy with.” — Mark Zuckerberg to Senator Thune
“Senator, I think the — the core question you’re asking about, A.I. transparency, is a really important one that people are just starting to very seriously study, and that’s ramping up a lot. And I think this is going to be a very central question for how we think about A.I. systems over the next decade and beyond. Right now, a lot of our A.I. systems make decisions in ways that people don’t really understand.” — Mark Zuckerberg to Senator Peters
On May 9, 2018, Richard Nieva published the article “Exclusive: Google’s Duplex could make Assistant the most lifelike AI yet” in CNET.
“But internal emails reviewed by Gizmodo show that executives viewed Project Maven as a golden opportunity that would open doors for business with the military and intelligence agencies. The emails also show that Google and its partners worked extensively to develop machine learning algorithms for the Pentagon, with the goal of creating a sophisticated system that could surveil entire cities.” — Gizmodo
On July 17, 2018, Alfred Ng published the article “Inside Facebook, Twitter and Google’s AI battle over your social lives” in CNET.
“When you sign up for Facebook on your phone, the app isn’t just giving you the latest updates and photos from your friends and family. In the background, it’s utilizing the phone’s gyroscope to detect subtle movements that come from breathing. It’s measuring how quickly you tap on the screen, and even looking at what angle the phone is being held.” — CNET
On December 3, 2018, Richard Waters published the opinion article “‘Natural language understanding’ poised to transform how we work”, which stated that Primer was being used by WAL-MART.
In 2019, Facebook introduced the open-source environment simulator AI Habitat.
In March 2019, the National Security Commission On Artificial Intelligence began creating a report on the use of autonomous weapons.
On May 3, 2019, Ohio State University (Alan Ritter, Shi Zong), Leidos, Inc. (Graham Mueller) and FireEye LLC (Evan Wright) published the paper “Analyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media”, which detailed a deep learning artificial intelligence capable of reading millions of tweets for security flaws susceptible to hacking, with tweets oftentimes being ahead of the National Vulnerability Database ran by the National Institute of Standards and Technology. This was done with assistance from Amazon Mechanical Turk workers using a total of 6,000 tweets.
Before the summer of 2019, China used artificial intelligence-controlled surveillance on the imprisoned Muslim Uighurs.
Also before the summer of 2019, President Xi Jinping appropriated the phrase “sharp eyes” to reference his country-spanning surveillance system. The artificial intelligence start-ups CloudWalk, Hikvision, iFlytek, Megvii, Meiya Pico and SenseTime also have a relationship with the Chinese Government.
Also before the summer of 2019, SenseTime started to work in co-operation with China Tower to install 1.9 million facial recognition cameras. China also, through various companies, made surveillance systems for Zimbabwe, Malaysia, Kuala Lumpur, Singapore, Ethiopia, Sri Lanka, Zambia, Ecuador, Bolivia and Serbia.
“I tell my students that I hope none of them will be involved in killer robots. They have only a short time on Earth. There are many other things they could be doing with their future.” — Yi Zeng
“China already has hundreds of millions of surveillance cameras in place. Xi’s government hopes to soon achieve full video coverage of key public areas. Much of the footage collected by China’s cameras is parsed by algorithms for security threats of one kind or another. In the near future, every person who enters a public space could be identified, instantly, by AI matching them to an ocean of personal data, including their every text communication, and their body’s one-of-a-kind protein-construction schema. In time, algorithms will be able to string together data points from a broad range of sources — travel records, friends and associates, reading habits, purchases — to predict political resistance before it happens. China’s government could soon achieve an unprecedented political stranglehold on more than 1 billion people.” — The Atlantic
Before June 4, 2019, Fabula AI was founded by Michael Bronstein.
On June 4, 2019, Twitter purchased the British organisation Fabula AI, a pioneer of geometric deep learning, in order to tackle what it considers to be “fake news”, with Fabula AI being integrated into Twitter’s Twitter Cortex machine learning team. Michael Bronstein was employed as the Head of Graph Deep Learning Research.
On July 31, 2019, Sarah Scoles published the article “It’s Sentient” in The Verge.
“SENTIENT catalogs normal patterns, detects anomalies, and helps forecast and model adversaries’ potential courses of action.” — Karen Ferguson, National Reconnaissance Office’s Office of Public Affairs
In August 2019, Huawei unveiled a mobile machine-learning chip designed by Cambricon.
On March 16, 2020, YouTube announced that it would rely on machine learning during periods of furloughed staff as a result of the coronavirus pandemic.
On March 17, 2020, Rebecca Heilweil published the article “Facebook is flagging some coronavirus news posts as spam” in Recode.
On June 9, 2020, Paul Mozur and Cade Metz published the article “A U.S. Secret Weapon in A.I.: Chinese Talent” in The New York Times.
In July 2020, Primer was used to investigate Russian news outlets with regards to the Armenia-Azerbaijan conflict over Nagorno-Karabakh, determining that Russian news was bolstering Armenia against Azerbaijan.
“Primer’s analysis of the Russian information campaign offers a simple example of how AI can both help organize information and identify misinformation. The effort to portray Azerbaijan and Turkey as aggressors in Nagorno-Karabakh may have provided an early warning sign of escalating tensions, or an indicator of Russia trying to stir up trouble. The report boiled down 985 incidents from over 3,000 documents to 13 key events. A human analyst would have needed several hours to perform the analysis, but the Primer system did it in roughly 10 minutes. The technology works across several languages, including Russian and Chinese as well as English.” — WIRED
On August 21, 2020, Facebook published the press release “New milestones in embodied AI”.
“To accomplish a task like checking to see whether you locked the front door or retrieving a cell phone that’s ringing in an upstairs bedroom, AI assistants of the future must learn to plan their route, navigate effectively, look around their physical environment, listen to what’s happening around them, and build memories of the 3D space. These smarter assistants will require new advances in embodied AI, which seeks to teach machines to understand and interact with the complexities of the physical world as people do.” — Facebook
On September 21, 2020, Patrick O’Neill published the article “CIA’s new tech recruiting pitch: More patents, more profits” in MIT Technology Review, which discussed the Central Intelligence Agency’s new initiative, CIA Labs.
On September 21, 2020, the Central Intelligence Agency announced the new initiative, CIA Labs, to allow for Central Intelligence Agency officers to file patents on intellectual property they have worked on and gain profits, with the remainder of the balance collected by the Central Intelligence Agency.
In October 2020, Facebook announced plans to double the size of their artificial intelligence team, Facebook Artificial Intelligence Research (FAIR).
On October 20, 2020, Will Knight published the article “The AI Company Helping the Pentagon Assess Disinfo Campaigns” in WIRED, which was about the system Primer.
On October 30, 2020, Twitter, Ilkka Paananen (founder of Supercell), Jeff Dean and Shakil Khan invested in the venture capital company Air Street Capital founded by Nathan Benaich as part of a $17 million fund. Air Street Capital will partially fund businesses starting in artificial intelligence. Air Street Capital hired Luc Vincent (formerly Lyft) and Phil Keslin (formerly Google and co-founder of Niantic).
On March 1, 2021, the National Security Commission On Artificial Intelligence (Eric Schmidt, Robert Work, Andy Jassy, Andrew Moore, Eric Horvitz and Safra Catz) provided a report to President Joe Biden to recommend authorisation to use autonomous weapons.
On March 4, 2021, Facebook announced that it had trained an artificial intelligence, codenamed SEER, to use 1 billion Instagram photographs in order to see and identify what is in each photograph with an 84.2% success rate on a test provided by ImageNet.