We released our Freebits white paper: http://shivakintali.org/freebits.pdf In this white paper, we explain why there is an urgent need for a decentralized, permissionless and uncensorable global public square. A quick overview of freebits is at https://freebits.app/about
I am very excited to announce Freebits ( http://freebits.app ), a decentralized, permissionless, immutable and uncensorable social network built on top of EulerChain.
Our mission is to enable journalists and influencers to speak freely to everyone globally, connect with their fans and get tips (in crypto) without any censorship or de-platforming.
Please sign up and join the future of social media 👉 https://freebits.app/
What is freebits ? 👉 https://freebits.app/about
FAQ 👉 https://freebits.app/faq/
My profile on freebits 👉 https://freebits.app/shiva/
Cryptics is my upcoming adventure novel, aimed at teaching cryptography, blockchain and mathematical concepts (to students from middle school & above) in a fun, exciting & a memorable way.
Read more details & Chapter 0 on my medium blog post.
Chapter 1 and the details of our crowdfunding campaign (taking pre-orders) are coming soon.
After almost two years of development of our Blockchain-powered data integrity platform, our consumer facing app is now available on the iOS app store. It is called True Dat. Watch the above video for a quick overview of True Dat app and download the app from the iOS app store.
What is True Dat app ?
True Dat app lets you create and share tamper-proof videos, photos and audio recordings. It prevents tampering by securely storing the cryptographic hashes of your content (and related metadata) on a Blockchain. The app and the platform consist of more than fifty different security checks to keep track of provenance of this data and verify their authenticity.
Why do you need True Dat app ?
With the upcoming elections in the US, ongoing protests in India and Hong Kong, wildfires in Australia, climate change everywhere, ongoing international tensions, etc…. there is a lot of misinformation, selectively edited videos, fake videos, fake audio and fake photos on the internet. They often go viral on the social media (facebook, twitter, whatsapp, instagram etc). Some people claim fake content as real and some people claim real content as fake. These claims are often based on their limited knowledge or based on their social / economic / political biases. Common people (with limited time and short attention span) have no idea what’s real and what’s fake. They quickly jump into conclusions, randomly taking one side or the other. Based on their random conclusions some people resort to online trolling or extreme violence. Their actions in turn go viral on social media and thus creating more socio-economic and political chaos. It’s a vicious snowball effect leading us to a potential post-truth dystopia.
True Dat app prevents misinformation by giving everyone a truth machine. It allows anyone, anywhere to create and share tamper-proof videos, photos and audio recordings. One way, it prevents tampering is by securely storing the cryptographic hashes of your content (and related metadata) on a Blockchain. The app uses several proprietary techniques to make sure that the content is genuinely created by the author at a particular time and at a particular location and it hasn’t been modified in any way or form since its creation. The author can prove the authenticity of his/her content to anyone by providing the content and the associated blockchain timestamps and tamper-evident metadata files securely created by the True Dat app.
Tamper-proof videos, photos and audio recordings are particularly useful in the following cases:
Journalists, Media companies, Political campaign groups and Government agencies: To create and share tamper-proof videos, photos and audio recordings of major news events, politicians’ speeches, major local and global political events. This helps them prevent and detect selective editing and deepfakes and eliminate misinformation. Here are some real-life examples:
- Recently ABC News mistakenly aired a video from Kentucky military show as Syria bombing footage. The content created using True Dat app prevents such mistakes by securely storing the metadata (including the location and time of creation) on a Blockchain.
- Manipulated videos of Nancy Pelosi edited to falsely depict her as drunk spread on social media.
- Video Edited to Falsely Suggest Joe Biden Made Racist Remark
Citizen journalism and Photo Journalism: As mentioned earlier, there is lot of misinformation, fake photos, videos about violence in protests across the world. Here are some scary examples of misinformation about the recent protests in India:
- An old video from 2018 showing a group of people burning images of Hindu gods is now being shared on social media with a false claim that the incident took place during the recent anti-CAA protests.
- An old photo from 2008, showing a Nepalese policeman pull the t-shirt of a female Tibetan protester is being shared on social media with a false claim that the Indian Army is manhandling a woman in Assam during CAA protests.
- An old photo from Pakistan showing a girl injured due to a dog bite is being shared on social media with a false claim that the kid was beaten by Uttar Pradesh police during the CAA Protests.
- Fake messages with doctored videos are being circulated on social media to create panic.
- A video from 2016 of a protest rally in Amritsar is going viral on social media with a false claim that the crowd is protesting against NRC in Punjab.
- An old video from 2011 is being shared on social media with a misleading claim that Muslims are using fake turbans to pass off as Sikhs protesting against the Citizenship Amendment Act.
- Photo showing policemen protesting against CAA is photoshopped.
- On Nov 12 2019, a little girl was injured in a train accident in Bangladesh. Now her photo is being shared on social media that she is injured during CAA protests. Tamper-proof provenance of digital media (along with metadata) prevents such misinformation
There are thousands of such examples across the world in just the last six months. Online fake news is costing us $78 billion globally each year and creating chaos and killing people. True Dat app allows anyone to create verifiable photos and videos of global events and prove their authenticity instantaneously.
Dating apps and ride-sharing apps: True Dat app and our data integrity APIs allows users and enterprises to create verifiable photo selfies and video selfies and verify authentic users instantaneously and prevent fraudulent users. For example:
- Bumble dating app blocked Sharon Stone after users thought her profile was fake
- Glasgow tops ‘catfishing’ league with one in seven singletons turning up to find the other person is nothing like their online photo
- Uber loses London licence after TfL finds drivers faked identity. People unwittingly got into cars with drivers who were not the same as the drivers booked through the app.
Insurance companies: According to the FBI, The total cost of insurance fraud (non-health insurance) is estimated to be more than $40 billion per year in U.S. This fraud costs the average U.S. family $400-$700 per year in increased premiums. Sometimes people submit fake photos downloaded from the Internet as a part of their insurance claims. True Dat app lets users securely provide tamper-proof photo and video evidence (of their car and its components) before getting an insurance and during submitting their claims. For example, you can send photos of your car from all angles before taking car insurance (or) glass coverage. This evidence can be instantaneously verified by the insurance companies using our platform.
Sports Centers: True Dat allows high school and college sports centers to issue sports certificates along with a photo / video proof of the student’s achievements. This allows them to keep track of student progress in a series of tamper-proof photos and videos. For example, fake photos were submitted in the recently exposed college admissions scandal. Read my detailed blog post about ‘Preventing future college admissions scandals’.
Whistleblowers, Undercover operations, sting operators: to create evidence of fraud, corruption or misbehavior. For example:
- incidents involving illegal police brutality at a peaceful protest
- incidents involving looting by civilians during protests / natural disasters
- corrupt politicians or officials taking bribes
- illegal actions happening inside corporations / government offices
- whistleblowers/journalists getting bullied/blackmailed/threatened
- incidents of sexual harassment or bullying
- incidents involving domestic disturbance or domestic violence.
Politicians, Celebrities, CEOs: There is a lot of online misinformation and fake news about politicians and celebrities. True Dat app allows them to (i) record a tamper-proof video of them giving clear statements about their opinion about a global social / economic / political event (ii) create photographic / video evidence of their presence at a certain event. The True Dat videos are tamper-proof, so selective editing of these videos can be efficiently detected.
E-commerce companies: To create verifiable photos and videos of third-party products.
Non-profit organizations and NGOs: To prove that an orphanage is built or a non-profit event was held at a particular location.
Travel: Create authentic photos and videos for travel blogs. For example:
- Instagram influencer slammed for ‘fake traveling’ photos
- An Instagram travel star apologized after being called out for stealing other people’s photos — and it proves you can’t believe everything you see online.
Real Estate: To create photographic / video evidence of real estate property for selling (or) for insurance purposes.
Process servers: to create a photographic / video proof that they served the right person at the right place.
UPS, FedEx, Amazon delivery personnel: to share location of the delivered package along with a photo / video evidence.
Law enforcement agencies: to prove that a video evidence, photo evidence or bodycam footage is not tampered, since the time of its creation. With the rise of deepfakes, lawyers are questioning the photgraphic and video evidence to promote their client’s self-interests.
Scientists and travelers: To create photographic and video evidence of the effects of climate change at certain locations.
On a lighter note, you can use True Dat app to create video evidence that you can do a perfect backflip, juggle, tricks with basket ball or soccer ball a hula hoop 🙂
There are many many more applications.
Our mission is to simplify trust and truth in the digital world, prevent and detect data tampering, eliminate fraud and misinformation and save humanity from a potential dystopia.
May the truth be with you.
If you want to know what motivated me to create TrueShelf (an AI powered adaptive learning platform) and the future of learning, please read my interview on Edsurge.
As some of you know, I am now the Founder & CEO of TrueShelf Inc, an EdTech startup based in the Bay Area. TrueShelf is aimed at developing platform, content and products to aid intuitive, visual, social, adaptive and personalized learning. TrueShelf consists of two main components: TrueShelf Online Network and TrueShelf Apps. Read our FAQ for more details.
Today’s post is about TrueShelf apps, intuitive and visual learning apps that are carefully designed to help students learn specific concepts in a systematic and adaptive manner.
Recently we released our True Vocabulary app, our first adaptive learning app. The existing solutions to learn english vocabulary are either too hard-to-use and/or expensive and/or old-fashioned (e.g. flashcards). Our app is focused primarily on automatic personalization and ease-of-use. It has already received more than 25,000 downloads on the iOS app store. If you are preparing for GRE, SAT, GMAT, ACT, CAT or simply interested in improving your english vocabulary, True Vocabulary app provides an efficient and elegant step by step adaptive learning process. It is an intelligent personalized vocabulary tutor.
True Vocabulary uses an intelligent algorithm (based on the concepts of spaced repetition, Leitner system and lexical cohesion) to design adaptive multiple-choice vocabulary quizzes. Learning tasks are divided into small sets of multiple-choice quizzes designed to help you master the basic words before moving on to the advanced words. Words closely related to your hardest words are selected more frequently in the quizzes. For a fixed word, the correct and wrong answers are selected adaptively giving rise to hundreds of combinations. After each wrong answer, you receive a detailed feedback with the meaning and usage of the corresponding word. Coins, Gems and Levels are unlocked adaptively to motivate, evaluate and reward the learner.
This is just the beginning of our journey to make education elegant, efficient and painless for hundreds of thousands of students and teachers. In future posts, I will talk more about TrueShelf’s vision and roadmap. Stay tuned.
Today’s post is about the following paper, a joint work with Qiuyi Zhang, one of my advisees. Qiuyi Zhang is now a graduate student in the Mathematics department of Berkeley.
- Shiva Kintali, Qiuyi Zhang. Forbidden Directed Minors and Directed Pathwidth. (Preprint is available on my publications page)
Undirected graphs of pathwidth at most one are characterized by two forbidden minors i.e., (i) the complete graph on three vertices and (ii) the spider graph with three legs of length two each (see the following figure).
Directed pathwidth is a natural generalization of pathwidth to digraphs. We proved that digraphs of directed pathwidth at most one are characterized by a finite number of forbidden directed minors. In particular, we proved that the number of vertices in any forbidden directed minor is at most 8*160000+7. Ahem !!
This paper falls in the “directed minors” part of my research interests. In an earlier theorem, proved in April 2013 (see this earlier post), we proved that partial 1-DAGs are characterized by three forbidden directed minors. In a similar vein, I conjectured that the digraphs with directed pathwidth at most 1 are characterized by a finite number of forbidden directed minors. I assumed that the number of forbidden directed minors is number is around 100. So we started this project in May 2013 and started making a list of carefully constructed forbidden directed minors and tried to extend our techniques from partial 1-DAGs. Here is an initial list of minors we found.
All the forbidden minors we found, looked very cute and we assumed that a proof is nigh. Soon, we realized that the list is growing quickly and none of our earlier techniques are applicable. After almost an year of patient efforts and roller coaster rides, we proved our finiteness theorem in May 2014, two weeks before Qiuyi Zhang’s thesis defense. It took us 10 more months to get the paper to its current status. So this is a two year long adventure.
I am hoping to prove more theorems in the “directed minors” area in the coming years. The current paper taught me that patience and focus are big factors to make consistent progress. There should be a nice balance between `proving new theorems’ and `writing up the existing results’.