| 15% | “15%” | Historically 15% of IT companies suffer catastrophic value loss yearly | Peter Fenton | Mar 18, 2016 | Supported |
| 70% | “70%” | Historically 15% of IT companies suffer catastrophic value loss yearly | Peter Fenton | Mar 18, 2016 | Supported |
| 5% | “five percent” | Historically 15% of IT companies suffer catastrophic value loss yearly | Peter Fenton | Mar 18, 2016 | Supported |
| 80% | “80%” | De la Torre: 80% of data has location component, only 10% use it | Javier de la Torre | Feb 21, 2016 | — |
| 10% | “10%” | De la Torre: 80% of data has location component, only 10% use it | Javier de la Torre | Feb 21, 2016 | — |
| 1M | “1014 thousand” | CartoDB analysis finds 114,000 daily commuters depend on NYC's L train | Javier de la Torre | Feb 21, 2016 | Supported |
| $1.5B | “half a billion dollars” | Neustar acquired MarketShare for $500 million in 2015 | Satya Ramachandran | Feb 21, 2016 | Partly supported |
| 4.5B | “4.5 billion” | MarketShare ran sub-second simulations on 4.5 billion data points in 2015 | Satya Ramachandran | Feb 21, 2016 | — |
| 600M | “six hundred million” | MarketShare ran sub-second simulations on 4.5 billion data points in 2015 | Satya Ramachandran | Feb 21, 2016 | — |
| $2M | “two million dollars” | Pluralsight's top author earned over $2M in royalties in 2015 | Aaron Skonnard | Feb 21, 2016 | — |
| 1B | “a billion” | Skonnard: Adaptive learning bet can grow Pluralsight to $10B-$20B | Aaron Skonnard | Feb 21, 2016 | Didn’t hold up |
| 20B | “twenty billion” | Skonnard: Adaptive learning bet can grow Pluralsight to $10B-$20B | Aaron Skonnard | Feb 21, 2016 | Didn’t hold up |
| 500M | “a four hundred million” | Scholnick: Trinity Ventures closed a $400M 12th fund | Dan Scholnick | Jan 25, 2016 | — |
| 80% | “80%” | Scholnick: Developer tool companies rely less on large enterprise customers | Dan Scholnick | Jan 25, 2016 | — |
| 20% | “20%” | Scholnick: Developer tool companies rely less on large enterprise customers | Dan Scholnick | Jan 25, 2016 | — |
| 100M | “a hundred million” | New Relic wouldn't have reached $100M without its early sales hires | Dan Scholnick | Jan 25, 2016 | — |
| 2.5T | “a half a trillion” | Google's Peter Norvig estimated strong AI is worth up to $2T annually | Gary Marcus | Jan 25, 2016 | — |
| $2T | “two trillion dollars” | Google's Peter Norvig estimated strong AI is worth up to $2T annually | Gary Marcus | Jan 25, 2016 | — |
| 1B | “a billion” | Marcus: Facebook M relies mostly on human operators rather than AI | Gary Marcus | Jan 25, 2016 | Supported |
| $2M | “Two million dollars” | Orad: VCs rejected Sisense, leading a founder's father to invest $2M | Amir Orad | Jan 25, 2016 | — |
| $1K | “a thousand dollars” | Orad: Sisense processed 10TB of data in 10s on a $1k server | Amir Orad | Jan 25, 2016 | Partly supported |
| $30B | “thirty billion dollars” | Orad: $30 billion per year is spent on business intelligence | Amir Orad | Jan 25, 2016 | Supported |
| 1K | “a thousand” | Orad: Sisense has over 1,000 customers including NASA, eBay, and Target | Amir Orad | Jan 25, 2016 | Partly supported |
| 10M | “ten million” | Turck: MapR raised a $110 million funding round from Google Capital | Matt Turck | Dec 17, 2015 | — |
| 1.5B | “a half billion” | Srivas: MapR powers a global email provider with 1.5 billion accounts | M.C. Srivas | Dec 17, 2015 | — |
| 100M | “a hundred million” | Srivas: A single Apache HDFS cluster handles roughly 100 million files | M.C. Srivas | Dec 17, 2015 | Supported |
| 1.5M | “a half million” | Srivas: Aadhaar will take 2.5 years to achieve full enrollment in India | M.C. Srivas | Dec 17, 2015 | Partly held up |
| 1K | “a thousand” | Srivas: MapR has reached 1,000 customers in four years | M.C. Srivas | Dec 17, 2015 | — |
| 30M | “thirty million” | Srivas: India's Aadhaar biometric system has registered 930 million people | M.C. Srivas | Dec 17, 2015 | Supported |
| 1M | “a million” | Mashable crawls about a million pieces of content daily | Haile Wusu | Nov 23, 2015 | — |
| 75% | “75%” | Mashable's Velocity engine reaches 75% content prediction accuracy within five minutes | Haile Owusu | Nov 23, 2015 | — |
| 1M | “a million” | Bloom: Netflix couldn't deploy its $1M prize algorithm due to complexity | Josh Bloom | Nov 23, 2015 | Supported |
| 95% | “95%” | Bloom: 95% of production machine learning code is just glue code | Josh Bloom | Nov 23, 2015 | Supported |
| 20% | “20%” | Wise.io's ML automatically resolves 5% to 20% of support tickets | Josh Bloom | Nov 23, 2015 | — |
| 20% | “20%” | Birchbox's catalog recommendation algorithm boosted full-size product conversions by 20% | Liz Crawford | Oct 21, 2015 | — |
| 4M | “four million” | PlayStation 4 launch generated four million pieces of content on Livefyre | Ramana Rao | Oct 21, 2015 | — |
| 5× | “five times” | Disney saw repeat visits increase fivefold after integrating Livefyre social elements | Ramana Rao | Oct 21, 2015 | — |
| 128K | “128 thousand” | Fox's breaking news coverage topped 200,000 concurrent interactive users via Livefyre | Ramana Rao | Oct 21, 2015 | — |
| 350M | “three hundred fifty million” | Livefyre reaches 350 million unique visitors and 3 billion page views | Ramana Rao | Oct 21, 2015 | — |
| 3B | “three billion” | Livefyre reaches 350 million unique visitors and 3 billion page views | Ramana Rao | Oct 21, 2015 | — |
| 100M | “a hundred million” | Livefyre reaches 350 million unique visitors and 3 billion page views | Ramana Rao | Oct 21, 2015 | — |
| 1M | “a million” | Livefyre regularly hits one million concurrent live users across its network | Ramana Rao | Oct 21, 2015 | — |
| 4M | “four million” | Livefyre processes four million requests per minute across its live widgets | Ramana Rao | Oct 21, 2015 | — |
| 66K | “66 thousand” | Livefyre processes four million requests per minute across its live widgets | Ramana Rao | Oct 21, 2015 | — |
| 3× | “three times” | Livefyre processed 12 million requests per minute during 2015 CNN debate | Ramana Rao | Oct 21, 2015 | — |
| 80B | “eighty billion” | Rao predicts Livefyre will process over 80 billion events per month | Ramana Rao | Oct 21, 2015 | — |
| 97% | “97%” | Falkowitz: 97% of all cyberattacks begin with phishing | Oren Falkowitz | Oct 21, 2015 | Partly supported |
| 90% | “90%” | Ten phishing emails yield a 90 percent success probability within 90 seconds | Oren Falkowitz | Oct 21, 2015 | Partly supported |
| 50% | “50%” | Falkowitz: Verizon report shows 50% phishing success by third message | Oren Falkowitz | Oct 21, 2015 | Contradicted |
| 1M | “one million” | Area 1 Data: Top spam filters miss 9 targeted phishing emails per million | Oren Falkowitz | Oct 21, 2015 | — |
| 100% | “hundred percent” | Deighton: Vast majority of new startup data lives in cloud | Anthony Deighton | Sep 14, 2015 | — |
| 90% | “90%” | Increasing dataset accuracy from 90% to 95% repeatedly halves error rates | Lukas Biewald | Sep 14, 2015 | — |
| 95% | “95%” | Increasing dataset accuracy from 90% to 95% repeatedly halves error rates | Lukas Biewald | Sep 14, 2015 | — |
| 100% | “hundred percent” | Increasing dataset accuracy from 90% to 95% repeatedly halves error rates | Lukas Biewald | Sep 14, 2015 | — |
| 30% | “30%” | Thirty percent of CrowdFlower's crowdsourced workforce is based in the US | Lukas Biewald | Sep 14, 2015 | — |
| 20% | “20%” | CrowdFlower charges a platform fee plus up to a 20% take rate | Lukas Biewald | Sep 14, 2015 | — |
| 25% | “25%” | 25% of CB Insights data is investor-submitted, 75% programmatically extracted | Anand Sanwal | Sep 14, 2015 | — |
| 75% | “75%” | 25% of CB Insights data is investor-submitted, 75% programmatically extracted | Anand Sanwal | Sep 14, 2015 | — |
| 100× | “hundred times” | People speak 100 times more words than they write in email | Evan Macmillan | Sep 14, 2015 | — |
| 99% | “99%” | A 1952 Bell Labs voice system reached 97-99% accuracy | Evan Macmillan | Sep 14, 2015 | Supported |
| 1K | “a thousand” | Kimball: Google expanded its MySQL AdWords backend to 1,000 shards before replacement | Spencer Kimball | Jun 19, 2015 | — |
| 90% | “90%” | Simple recommendation algorithms deliver 80 to 90 percent of the total benefit | David Glueck | Jun 19, 2015 | — |
| 3× | “three times” | Native apps distract engineering teams by forcing them to build features thrice | David Glueck | Jun 19, 2015 | — |
| 30M | “thirty million” | Essas: OpenTable has 30 million reviews in its database | Joseph Essas | Jun 19, 2015 | — |
| 5% | “five percent” | Five percent of Crisis Text Line users consume 40% of counselor resources. | Jake Porway | May 28, 2015 | Partly supported |
| 40% | “40%” | Five percent of Crisis Text Line users consume 40% of counselor resources. | Jake Porway | May 28, 2015 | Partly supported |
| 42B | “forty-two billion” | 42 billion customer service calls are made annually | Sameer Maskey | May 28, 2015 | Contradicted |
| 1B | “one billion” | Brute-forcing a 10-word sentence requires one billion permutations | Sameer Maskey | May 28, 2015 | Contradicted |
| 80% | “80%” | Enterprise customers will not pay for 80% accurate machine learning | David Luan | May 28, 2015 | — |
| 100% | “100%” | Enterprise customers will not pay for 80% accurate machine learning | David Luan | May 28, 2015 | — |
| 1K | “a thousand” | Neo4j ran a social network graph query 1,000 times faster than MySQL | Emil Eifrem | Apr 20, 2015 | — |
| 1M | “a million” | Neo4j maintained 2ms query latency when scaled to 1,000,000 users | Emil Eifrem | Apr 20, 2015 | — |
| 25M | “twenty-five million” | Neo4j maintained 2ms query latency when scaled to 1,000,000 users | Emil Eifrem | Apr 20, 2015 | — |
| 99% | “99%” | Muglia: Cloud security can surpass 99% of on-premises systems | Bob Muglia | Apr 20, 2015 | — |
| 3M | “three million” | Crouch: San Antonio police system has 1.2M duplicate records out of 3M | Scott Crouch | Apr 20, 2015 | Not publicly verifiable |
| 1.2M | “1.2 million” | Crouch: San Antonio police system has 1.2M duplicate records out of 3M | Scott Crouch | Apr 20, 2015 | Not publicly verifiable |
| 8M | “eight million” | Crouch: FBI's NCIC database receives around 8M daily law enforcement queries | Scott Crouch | Apr 20, 2015 | Partly supported |
| 5M | “five million” | Washington D.C. estimates 20% to 40% of police records are duplicates | EJ Bensing | Apr 20, 2015 | Not publicly verifiable |
| 40% | “40%” | Washington D.C. estimates 20% to 40% of police records are duplicates | EJ Bensing | Apr 20, 2015 | Not publicly verifiable |
| 87% | “87%” | Bensing: 87% of Americans are identifiable by birth date, gender, location | EJ Bensing | Apr 20, 2015 | Supported |
| 90% | “90%” | Howie Liu: 90% of spreadsheets are used as makeshift databases | Howie Liu | Apr 20, 2015 | — |
| $50M | “fifty million dollars” | Ryan Smith: Qualtrics hit $50M revenue and $30M cash flow before raising capital | Ryan Smith | Apr 2, 2015 | — |
| $30M | “thirty million dollars” | Ryan Smith: Qualtrics hit $50M revenue and $30M cash flow before raising capital | Ryan Smith | Apr 2, 2015 | — |
| 1M | “a million” | Ryan Smith: Qualtrics grew to one million academic users | Ryan Smith | Apr 2, 2015 | — |
| 1B | “a billion” | Medlock: SwiftKey is used on close to a billion devices worldwide | Ben Medlock | Apr 2, 2015 | Partly supported |
| 15T | “15 trillion” | SwiftKey saved users 15 trillion keystrokes out of 50 trillion typed characters | Ben Medlock | Apr 2, 2015 | — |
| $38M | “thirty eight million dollars” | Flatiron raised $138M from Google, its largest healthcare deal | Zach Weinberg | Feb 18, 2015 | Partly supported |
| 20% | “20%” | Flatiron Health software connects 20% of US cancer cases | Zach Weinberg | Feb 18, 2015 | — |
| 90% | “90%” | US oncology EHR adoption will reach 100% by 2017 | Zach Weinberg | Feb 18, 2015 | Didn’t hold up |
| 100% | “hundred percent” | US oncology EHR adoption will reach 100% by 2017 | Zach Weinberg | Feb 18, 2015 | Didn’t hold up |
| 90% | “90%” | Flatiron spends 90% of its time on single-player software value | Zach Weinberg | Feb 18, 2015 | — |
| 10% | “10%” | Flatiron captures EGFR mutation status in 99% of its dataset | Zach Weinberg | Feb 18, 2015 | — |
| 99% | “99%” | Flatiron captures EGFR mutation status in 99% of its dataset | Zach Weinberg | Feb 18, 2015 | — |
| 30M | “thirty million” | Flatiron Health spent over half its $130M Series B acquiring an EHR | Zach Weinberg | Feb 18, 2015 | — |
| 50% | “50%” | Flatiron Health spent over half its $130M Series B acquiring an EHR | Zach Weinberg | Feb 18, 2015 | — |
| 40% | “40%” | Oncology accounts for about 40% of pharma R&D spending | Zach Weinberg | Feb 18, 2015 | Partly supported |
| 60% | “60%” | Flatiron's business is 60% provider-focused and 40% life sciences | Zach Weinberg | Feb 18, 2015 | — |
| 40% | “40%” | Flatiron's business is 60% provider-focused and 40% life sciences | Zach Weinberg | Feb 18, 2015 | — |
| 5% | “five percent” | Flatiron targets data from the 95% of cancer patients outside trials | Zach Weinberg | Feb 18, 2015 | — |
| 95% | “95%” | Flatiron targets data from the 95% of cancer patients outside trials | Zach Weinberg | Feb 18, 2015 | — |
| $1K | “a thousand dollars” | Kaganovich: Human genome sequencing costs plummeted from $3 billion to $1,000 | Mark Kaganovich | Feb 18, 2015 | Partly supported |
| 3B | “three billion” | Kaganovich: Human genome sequencing costs plummeted from $3 billion to $1,000 | Mark Kaganovich | Feb 18, 2015 | Partly supported |
| 3B | “three billion” | Bisignano: Human genome sequencing costs fell from $3B to $1,000 | Alexander Bisignano | Feb 18, 2015 | Contradicted |
| 12B | “Twelve billion” | Bisignano: Major diagnostic companies Quest and LabCorp lack agile software teams | Alexander Bisignano | Feb 18, 2015 | — |
| 65% | “65%” | Bisignano: Recombine achieves over 65% patient opt-in rate for research | Alexander Bisignano | Feb 18, 2015 | — |
| 50% | “50%” | Gutman: Over 50% of patients do not take prescribed treatments or medications | Ron Gutman | Feb 18, 2015 | Partly supported |
| 2.6B | “2.6 billion” | HealthTap has served over 2.6 billion doctor answers | Ron Gutman | Feb 18, 2015 | — |
| 100% | “hundred percent” | Gutman: 100% of HealthTap content is doctor-created and peer-reviewed | Ron Gutman | Feb 18, 2015 | — |
| 74% | “74%” | Gutman: 74% of nighttime ER visits are unnecessary | Ron Gutman | Feb 18, 2015 | Contradicted |
| 50% | “50%” | US print advertising spend fell about 50% from 2008 to 2012 | Chris Wiggins | Jan 16, 2015 | Partly supported |
| 100M | “a hundred million” | IBM created a $100 million Watson investment fund | Michael Karasick | Jan 15, 2015 | — |
| 20% | “20%” | LeCun: AT&T's neural net read 20% of US checks in late 1990s | Yann LeCun | Dec 18, 2014 | Supported |
| $740M | “seven hundred forty million dollars” | Intel acquired an 18 percent equity stake in Cloudera for $740 million | Mike Olson | Dec 18, 2014 | Supported |
| 18% | “18%” | Intel acquired an 18 percent equity stake in Cloudera for $740 million | Mike Olson | Dec 18, 2014 | Supported |
| 70B | “seventy billion” | Annual spend on relational database tools is double the underlying platform spend | Mike Olson | Dec 18, 2014 | Partly supported |
| 300M | “three hundred million” | AppNexus has raised around $250 million in venture capital | Michael Rubenstein | Nov 20, 2014 | — |
| $250M | “two hundred fifty million dollars” | AppNexus has raised around $250 million in venture capital | Michael Rubenstein | Nov 20, 2014 | — |
| 30B | “thirty billion” | AppNexus processes 30 billion daily impressions on a 16-node Hadoop cluster | Catherine Williams | Nov 20, 2014 | — |
| 70% | “70%” | Jimenez: x.ai correctly identifies 70% of new meeting proposals | Marcos Jimenez | Nov 20, 2014 | — |
| 87M | “eighty-seven million” | Mortensen: 87 million US knowledge workers schedule 10 billion meetings annually | Dennis Mortensen | Nov 20, 2014 | — |
| 10B | “ten billion” | Mortensen: 87 million US knowledge workers schedule 10 billion meetings annually | Dennis Mortensen | Nov 20, 2014 | — |
| 1.3M | “1.3 million” | Clarifai automatically tagged 1.3 million stock images in a few minutes | Matthew Zeiler | Nov 20, 2014 | — |
| 10× | “10 times” | Clarifai's video recognition runs ten times faster than real time | Matthew Zeiler | Nov 20, 2014 | Not publicly verifiable |
| $80B | “eighty billion dollars” | The U.S. federal government spends about $80 billion annually on IT | Nick Sinai | Oct 16, 2014 | Supported |
| $40B | “forty billion dollars” | The U.S. federal government spends $140 billion annually on research and development | Nick Sinai | Oct 16, 2014 | Partly supported |
| 10% | “10%” | NOAA collects 20 terabytes of weather data daily but releases only 10% | Nick Sinai | Oct 16, 2014 | Supported |
| 3M | “three million” | The unmarketed IRS GetTranscript tool increased annual digital requests to 12 million | Nick Sinai | Oct 16, 2014 | Supported |
| 12M | “twelve million” | The unmarketed IRS GetTranscript tool increased annual digital requests to 12 million | Nick Sinai | Oct 16, 2014 | Supported |
| $2.5M | “2.5 million dollars” | A round-trip oil tanker voyage to Indonesia costs $2.5 million | Ami Daniel | Oct 16, 2014 | — |
| 2K | “two thousand” | Half of the $2.8 trillion global crude imports travel by sea | Ami Daniel | Oct 16, 2014 | Partly supported |
| $823B | “eight hundred twenty three billion dollars” | Half of the $2.8 trillion global crude imports travel by sea | Ami Daniel | Oct 16, 2014 | Partly supported |
| 50% | “50%” | Half of the $2.8 trillion global crude imports travel by sea | Ami Daniel | Oct 16, 2014 | Partly supported |
| 100M | “one hundred million” | Global AIS ship tracking relies entirely on an unverified honor system | Ami Daniel | Oct 16, 2014 | Supported |
| 1% | “One percent” | One percent of global ships transmit false identities | Ami Daniel | Oct 16, 2014 | Supported |
| 30% | “30%” | Maritime identity fraud increased 30% over two years | Ami Daniel | Oct 16, 2014 | Supported |
| 55% | “55%” | 55% of global ships misreport their actual destinations throughout their journeys | Ami Daniel | Oct 16, 2014 | Supported |
| 20M | “twenty million” | Global unstructured data generation will hit 20 million petabytes annually by 2016 | Vance Loiselle | Sep 22, 2014 | Didn’t hold up |
| 2B | “two billion” | One terabyte of log data equals roughly two billion events | Vance Loiselle | Sep 22, 2014 | — |
| 2B | “two billion” | Midsize enterprises generate over two billion log records daily | Vance Loiselle | Sep 22, 2014 | — |
| 15T | “15 trillion” | Sumo Logic processes over 800,000 daily queries across four petabytes | Vance Loiselle | Sep 22, 2014 | — |
| 70% | “70%” | Sumo Logic anomaly detection engine achieves 70% accuracy out of the box | Vance Loiselle | Sep 22, 2014 | — |
| 70% | “70%” | Sumo Logic's buyer split is 70% DevOps and 30% CISOs | Vance Loiselle | Sep 22, 2014 | — |
| 30% | “30%” | Sumo Logic's buyer split is 70% DevOps and 30% CISOs | Vance Loiselle | Sep 22, 2014 | — |
| $400M | “four hundred million dollars” | Vertica was acquired for approximately $400 million | Chris Lynch | Jun 26, 2014 | Partly supported |
| 4B | “a three billion” | Mega-fund VCs are just lottery ticket buyers lacking company-building skills | Chris Lynch | Jun 26, 2014 | — |
| 300M | “three hundred million” | Automated Insights generated more content than all media combined in 2013 | Robbie Allen | Jun 26, 2014 | — |
| $42B | “forty two billion dollars” | Stewart: Alipay amassed $42 billion in wallet assets in six months | Jeff Stewart | May 29, 2014 | Supported |
| 0.5% | “half percent” | Laplanche: Lending Club consumer rates average around 12.5 percent | Renaud Laplanche | May 29, 2014 | Supported |
| 50% | “50%” | Gutierrez: Credit Card Act slashed addressable credit card market to 17% | James Gutierrez | May 29, 2014 | Contradicted |
| 17% | “17%” | Gutierrez: Credit Card Act slashed addressable credit card market to 17% | James Gutierrez | May 29, 2014 | Contradicted |
| 300B | “three hundred billion” | Gutierrez: Post-2008 regulations dropped available revolving credit by over $900 billion | James Gutierrez | May 29, 2014 | Partly supported |
| 900B | “nine hundred billion” | Gutierrez: Post-2008 regulations dropped available revolving credit by over $900 billion | James Gutierrez | May 29, 2014 | Partly supported |
| $20B | “twenty billion dollars” | Gutierrez: Credit card availability to non-prime market dropped by $120B | James Gutierrez | May 29, 2014 | Supported |
| 1K | “a thousand” | Gutierrez: Lenders need roughly 1,000 defaulted loans to build a risk model | James Gutierrez | May 29, 2014 | — |
| 80% | “80%” | Gutierrez: Lenders need roughly 1,000 defaulted loans to build a risk model | James Gutierrez | May 29, 2014 | — |
| 10% | “10%” | Gutierrez: Lenders need roughly 1,000 defaulted loans to build a risk model | James Gutierrez | May 29, 2014 | — |
| 7% | “seven percent” | Laplanche: Lending Club's expense ratio is under 2% vs banks' 5-7% | Renaud Laplanche | May 29, 2014 | Supported |
| 2% | “two percent” | Laplanche: Lending Club's expense ratio is under 2% vs banks' 5-7% | Renaud Laplanche | May 29, 2014 | Supported |
| 17% | “17%” | Laplanche: US credit cards average 17% while savings yields near 0% | Renaud Laplanche | May 29, 2014 | Partly supported |
| 0.5% | “half percent” | Laplanche: Lending Club averages 12.5% borrower rates and 8% investor returns | Renaud Laplanche | May 29, 2014 | Partly supported |
| 8% | “eight percent” | Laplanche: Lending Club averages 12.5% borrower rates and 8% investor returns | Renaud Laplanche | May 29, 2014 | Partly supported |
| 150% | “150%” | Laplanche: Lending Club caps annual growth at 150% to manage risk | Renaud Laplanche | May 29, 2014 | — |
| $1B | “a billion dollars” | OnDeck has loaned over $1 billion to US small businesses | Noah Breslow | May 28, 2014 | Supported |
| $1.3T | “a quarter trillion dollars” | Breslow: US small business loan demand is roughly $250 billion | Noah Breslow | May 28, 2014 | — |
| 100B | “hundred billion” | Breslow estimates $100B in unmet US small business loan demand | Noah Breslow | May 28, 2014 | — |
| 8M | “eight million” | OnDeck tracks eight million US small businesses from creation to closure | Noah Breslow | May 28, 2014 | — |
| 60% | “60%” | Breslow: Small business online banking adoption rose from 60% to 95% | Noah Breslow | May 28, 2014 | Contradicted |
| 95% | “95%” | Breslow: Small business online banking adoption rose from 60% to 95% | Noah Breslow | May 28, 2014 | Contradicted |
| $1M | “a million dollars” | Breslow: OnDeck's typical customers average 10 years in business and $1M revenue | Noah Breslow | May 28, 2014 | — |
| 60% | “60%” | Mitra: OnDeck increased applicant scoring coverage from 60% to over 95% | Abhra Mitra | May 28, 2014 | — |
| 95% | “95%” | Mitra: OnDeck increased applicant scoring coverage from 60% to over 95% | Abhra Mitra | May 28, 2014 | — |
| 100M | “a hundred million” | Context Relevant ran a 120-server demo to automatically discover triangle area formulas | Stephen Purpura | May 27, 2014 | — |
| 90% | “90%” | Stephen Purpura argues 90-percent accurate predictive models suffice for commercial monetization | Stephen Purpura | May 27, 2014 | — |
| 70% | “70%” | Cloud storage and compute prices recently dropped 70% and 60% | Ashish Thusoo | May 27, 2014 | Partly supported |
| 60% | “60%” | Cloud storage and compute prices recently dropped 70% and 60% | Ashish Thusoo | May 27, 2014 | Partly supported |
| $55B | “fifty-five billion dollars” | Tan: Google generates $55B annually due to its search data lead | Jason Tan | May 27, 2014 | Supported |
| 60% | “60%” | High-frequency algorithms execute over 60% of US equity trades | Sean Gourley | Mar 20, 2014 | Partly supported |
| $300M | “three hundred million dollars” | Firms spent $300M on fiber cables cutting NY-London latency by 5ms | Sean Gourley | Mar 20, 2014 | Supported |
| $1T | “a trillion dollars” | Gourley: Algorithms can briefly wipe $1 trillion from financial markets | Sean Gourley | Mar 20, 2014 | Supported |
| $40M | “forty million dollars” | Gourley: Knight Capital lost $440M in 45 minutes from a rogue algorithm | Sean Gourley | Mar 20, 2014 | Supported |
| $200B | “two hundred billion dollars” | A fake AP tweet about White House explosions wiped $200B | Sean Gourley | Mar 20, 2014 | Partly supported |
| 61% | “61%” | Sean Gourley: 61% of internet traffic is non-human | Sean Gourley | Mar 20, 2014 | Partly supported |
| 51% | “51%” | Sean Gourley: 61% of internet traffic is non-human | Sean Gourley | Mar 20, 2014 | Partly supported |
| 85% | “85%” | Gourley: Google includes Wikipedia on page one for 85% of common searches | Sean Gourley | Mar 20, 2014 | Partly supported |
| 4M | “four million” | Jesse St. Charles: Knewton served roughly 4 million students in 18 months | Jesse St. Charles | Mar 20, 2014 | — |
| 10× | “10 times” | AT&T Labs Drove 12 Morristown Routes 10 Times for Cell Training Data | Chris Volinsky | Mar 20, 2014 | — |
| 100% | “hundred percent” | Industry data scientists must aim for 80% perfection, unlike in academia | Jake Klamka | Mar 20, 2014 | — |
| 80% | “80%” | Industry data scientists must aim for 80% perfection, unlike in academia | Jake Klamka | Mar 20, 2014 | — |
| 10% | “10%” | Sisense handles 3,000 concurrent users on a single server | Amit Bendov | Mar 3, 2014 | — |
| 10K | “ten-thousand” | Sisense analyzed 10 terabytes in 10 seconds on a sub-$10k server | Amit Bendov | Mar 3, 2014 | Supported |
| 50% | “50%” | Data Driven NYC meetup turnout is sometimes 50% of registered attendees | Matt Turck | Mar 3, 2014 | — |
| 10B | “ten billion” | Steier: Adding 10 billion rows to a data warehouse takes a long time | Sandy Steier | Mar 3, 2014 | — |
| 100% | “100%” | Retail churn is fuzzy and non-deterministic compared to subscription businesses | Corey Pearson | Mar 3, 2014 | — |
| 80% | “80%” | Retailers lose 80% of customers who go inactive for 4-5 months | Corey Pearson | Mar 3, 2014 | — |
| 30% | “30%” | Subramanian: Sizing is only 30% of the online apparel fit problem | Vijay Subramanian | Mar 3, 2014 | — |
| $100M | “hundred million dollars” | Product-market fit requires an unmet need that can sustain $50M+ revenue | Tasso Argyros | Mar 3, 2014 | — |
| $18T | “18 trillion dollars” | $18 trillion worth of goods crosses global borders annually | Josh Green | Mar 3, 2014 | Supported |
| 1.5B | “half a billion” | Sailthru processes roughly half a billion events every day | Ian White | Mar 3, 2014 | — |
| 500M | “five hundred million” | White: Sailthru has 500 million users in its database | Ian White | Mar 3, 2014 | — |
| 90% | “90%” | White: 80 to 90 percent of Sailthru's infrastructure is databases | Ian White | Mar 3, 2014 | — |
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