I am the CEO of QuillBot, a machine learning engineer, and a college dropout. Ask me anything!

What are some intended uses for this, other than to make your copied schoolwork look like it’s not copypasted from Wikipedia?

The vast majority of our users do not use QuillBot for any sort of plagiarism. A large chunk are international/non-native English speakers who use QuillBot to make their writing sound natural. The second large chunk is students/writers that use QuillBot to fix awkward sentence structure and get over writers block.

The vast majority of our users do not use QuillBot for any sort of plagiarism.

Do you have evidence to support this claim?

We analyze users behaviors and patterns to determine this. If users are changing every other word in a sentence, it indicates they are likely plagiarizing. However, most of our users only lightly edit the output, indicating that they are using this as a legitimate writing aide.

Pretty sure that's exactly what your app will be used for. Instead of deflecting the possibility of this, why not tell us how you're going to ensure the app will not be used for plagiarism.

There is plagiarism checking software that prevents students from plagiarizing even via paraphrasing. Turnitin is a very sophisticated plagiarism checking software. If a student wanted to plagiarize using QuillBot, they would have to change every third word to effectively get past it. As of now, it is a major time commitment, and often it is better to just write the essay yourself. In addition, students still run a risk of getting caught, which often has severe penalties.

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We have found that students using this as a writing aide, instead of a cheating aide, often get way more benefit from the software.

I use that plagiarism software and it doesn't catch everything. I know, because I have to individually read each top results in google and then read my students papers to find out the plagiarizers.

Take note that your AI doesn't just replace words straight up synonym for synonym. It restructures the sentence to be a full on paraphrase. That makes detection harder.

Here's a suggestion: reverse engineer your AI and allow it to be used as a plagiarism detector. Since it can restructure sentences, it can put it back together and find the original source. You'd earn more money from that.

Reverse engineering QuillBot to serve as a plagiarism detector is a lot harder than it seems. In fact, if our team was to engineer a plagiarism detector, it would most likely be something similar to what Turnitin already has.

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On a sentence level, Turnitin won't be able to pick up paraphrased sentences, but when you plagiarize a full essay it will be able to. This is because they check sequential trigrams. Without getting too deep into the math, the more sentences you are plagiarizing from, the easier it will be for Turnitin to pickup. Especially if you are plagiarizing it sentence by sentence (like QuillBot would do). This is true even if you restructure the sentence. As long as 3 words from many of the original sentences are preserved and the sentences are in the same order, Turnitin will pick it up.

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Hows your dating life?

Terrible.

How long does it take you to run a mile?

Depends on who is chasing me.

How many languages does QuillBot understand and how many more are you looking to teach it?

The whole development team only speaks English, so it is difficult to apply the technology to other languages. However, the technique we used can be applied to all/most languages, so in the future, as we bring on bilingual engineers we could expand it.

What paraphrase of the QuillBot scared you?

In an early model (not the current one), QuillBot made the following Paraphrase:

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AIs are stealing our jobs!

to:

AIs are doing the work for us

Where do you see machine learning in 10 or 20 years?

My answer to that varies more than I would like it too. Right now there are some serious limitations on what these systems can do, but if research can somehow break them (which is very much possible, but hard to make any time judgments on) it could mean a massive amount a difference to how intelligent and influential these algorithms can become. One thing that is for sure, is that its going to increase in relevancy within the next 10 years, and will exist in almost every aspect of our lives. Heck, right now ML is going to determine how successful this post is. So a short answer to your question is everywhere.

What are the serious limitations?

One major limitation involves the inability of current AIs to move from "narrow intelligence" to "general intelligence". These limitations mainly revolve around the fact that narrow agents need the task to be explicitly defined. We still have major issues getting agents to construct their own goals.

There are additional mathematical limitations as to which sets of problems our current network architectures can optimize on, as well as data accessibility which u/mliberosis detailed

Did you have to deal with everyone always against your success? College drop out here, starting my own business. On my second job that "requires a bachelors". I work hard and more importantly I work smart, I plan for future obstacles and learn from past failures.

I talk to friends and colleagues about my ambitions and overall everyone just shits all over the things that I say. It does give me the attitude of let me prove them wrong, but Im starting to doubt myself and thinking maybe my ego is too big. Just want to know if this is something that all successful people have to deal with?

Sounds very circumstantial. I'm reluctant to give anyone advice on pursuing a market I am unfamiliar with, however I would give 2 caveats. One is to try to find friends who are in the spaces that you are trying to aspire towards, and will encourage your entrepreneurship, since their judgments will be better informed and you can help bring each other up rather than down. Another point is that when it comes to entrepreneurship, a degree is less relevant, as it mostly serves as a tool to validate your ability to execute instructions that are explicitly laid out.

What programming languages and/or frameworks does QuillBot use? I've been interested in learning ML.NET but I'm not sure i know enough base .NET to make it worth my time.

The vast majority of QuillBot's ML was programmed in Python using the PyTorch framework.

What kind of hours do you work?

I don't really keep track of how much hours I work in the day. It kind of just all blends together at a certain point, since my work and life are the same existence. Most of what I do is sit on my ass and push buttons for hours straight. That on top of the large amount of caffeine I take makes it too easy to get an irregular+nocturnal schedule

How did you start your business and what did you do to make it successful? My boyfriend wants to start one doing AI development but he is so lost and doesn't know how to start

I would recommend first focusing on the problem rather than the solution. When I first started I was working on Question Generation ( a user gives an ai an article, and it creates multiple choice questions for self evaluation ), and for too long I was focused on trying to jam as much sophistication and bleeding edge research into a product that nobody asked for. Turns out students don't want more homework, they want the most efficient way to study (which is the material they are most likely going to get tested on).

Will you ever officially help policymakers writing laws? Congrats for your work, we'll done

In general I'd prefer to write less laws. However, if its going to happen anyways and if anyone cares to hear what I have to say, I'd give my best words.

I was searching to see if it’s open sourced, instead I got this: https://github.com/jkob/quillbot-plagiarizer...... anyways, are you planning on releasing data, or open sourcing it?

Nice question, its a tough one.

Had a laugh at the cosmic irony on that repo, since its a headless browser that plagiarizes our tech.

As for open sourcing, the unfortunate reality is that I just financially cant. I'm a richard stallman loving FOSS boy personally, but a man has to pay his student loan debt.

Would you recommend anyone to dropout?

No not anyone. I think college sends a strong signal to employers that you have a baseline competence and can follow instructions well. It also shows your stress tolerance and ability to exist in an institution. If you are going to be a professional, especially a technical profession (STEM etc.), college is probably a pretty good trade-off.

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I think for entrepreneurs it is a slightly different story. You do not need to send that signal to employers, however, in the likely event that you fail, a college degree may be a good safety. My degree was supposed to be in Computer Science, and even though I dropped out, I have done enough tasks/projects (QuillBot) where I could still get a decent software engineering job without the degree if I failed. I took this into account before I dropped out.

What were the main sources of knowledge about implementing ML in Python when you started vs now?

All the coding sources I've used "back in my day" are pretty outdated, and I wouldn't recommend trekking my previous paths. Instead I would suggest looking for tutorials around keras, since it is the cleanest framework that maintains the simple yet elegant nature of python, that I've encountered. Also shout out to Siraj Raval on youtube.

Now a days I kind of have a reasonable grasp on most of the ML frameworks, since they all really do mostly the same things. So the frameworks I use comes down to whichever github repo is the best in terms of performance and documentation
Edit: forgot to answer second half of question

How does quillbot as a company make money? Are you storing user submissions for any interesting projects?

User submissions and edits are stored, and then used to enhance the systems abilities. Its quite interesting how the site serves as a co-learning platform for both the user and the ai.

As for how we make money, we get our cash flow from 2 sources: Users paying for our premium service and companies using our API access (so they can integrate QuillBot in their own technology, for example chatbots).

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Could college students use your software to plagiarize papers and defeat plagiarism checking software?

Turnitin is a very sophisticated plagiarism checking software. If a student wanted to plagiarize using QuillBot, they would have to change every third word to effectively get past it. As of now, it is a major time commitment, and often it is better to just write the essay yourself. In addition, students still run a risk of getting caught, which often has severe penalties.

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We have found that students using this as a writing aide, instead of a cheating aide, often get way more benefit from the software.

Is Quillbot answering the questions me on this AMA?

The little guy is not that sophisticated as of yet, but perhaps one day.

What inspired you to make QuillBot?

After I learned about how machine learning functions, I had a strong epiphany on how drastically it will affect society, and a great fear as to how it can be misused. In many ways I felt that there was only a small window of time that was closing, while these systems are in their infancy, that I could have a legitimate effect on how they grow and manifest.

It is kind of scary to think about what these systems are capable of or what they'll be able to do in the future. Almost like an episode straight out of Black Mirror! What's your biggest concern about this type of growth? I'm sure a lot of people are concerned about a company like Facebook producing something like this for their own gains.

I'm not scared about the systems, what I am scared about is their owners. These agents are like dogs that have no option but to be loyal to their owners, and you can only think positively of them as they are just trying to do their best... However there are aspects of it when it comes to their ability to psychoanalyze that make me even wonder whether that narrative was manufactured by the machine itself. #RokosBasilisk

What are you working on next?

A pet project of ours is linguistic style transfer. We want to take an input and control the linguistic style of the output. For example, take an informal sentence and make it formal, take a complicated sentence and make it simple, or eventually (hopefully) take a sentence in modern English and turn it into old English.

How did college dropping affect you as a person? Is it harder for you to start up?

As of now, having dropped out doesn't have much of an effect on me, because I know what I'm doing and doing it to my best. But during my first year after, I cant deny, there was a sense of extreme uncertainty and a mild sense of dis-belonging which in many ways motivated me to succeed even harder.

Props to you and hope you’ll succeed jn the future. Thank you for answering!

Another question. What do you think would be the best way to use/take advantage of the ‘free’ time from dropping out?

Thanks again

Dropping does not strictly mean that you failed as a student. In many cases college is simply just not an effective institution to help someone recognize their full potential. That being said, its societies best suggestion on how to optimize oneself, and dropping out is betting against the market. Its a major cost if your already committed, and what you do with your time needs to justify the cost of dropping out. Therefore, I think the best use of the "free time" is to either invest in yourself by learning as much as you possibly can on your own, or to produce something productive/valuable in your free time. This could be a pet project or through a job/internship.

if you could be any animal.... what animal would you be?

Without too much thought, I choose elephant. Highly social animal with a nose as an appendage that can make tools

I'm writing a story about a robot snail that's learning to speak. What is something cool about AI's learning a language?

One aspect that I find kind of cute is that QuillBot has no perception of the real world, and is using text (to the best of its ability) as its only reference to the real world. QuillBot knows that red is similar to blue but has never seen colour. He knows loudness is related to sound, but never heard a melody, and knows food and salty co occur a lot but never tasted a potato chip.

*Edited to be more accurate

Also, why is Quillbot a "he?"

No strict reasoning. I feel like most agent are female, and like being a nonconformist. One could argue that that male is statistically the default gender in English, and QuillBot is actually androgynous, with some bias towards being male.

A friend recently asked me about writing software that would process e.g. book reviews, then figure out what they have in common: what did people like and dislike, why they've liked a particular character or event, etc. In my brief research I've found that there are many libraries for text analysis, but none that could extract overall meaning of the text, whats and whys. Only stuff like "text is generally about international politics" or "the overall sentiment is positive". I wonder what is your opinion on this - is this too much to expect from ML, or is it doable?

Its may be possible, but it's not trivial by any means. What you are probably looking for at first is some NER(name entity recognition) model stacked with some sentiment analysis. The NER model would attempt to recognize instances of events and characters in the comment. The thing about emotion and taste is that its multidimensional and cant be fully captured by a simple, I liked/hated it, so most sentiment models will not be fully sufficient. I think an easier solution is to try to find datapoints that can provide a larger scope to the problem. Rather than thinking about the content of the text, consider the readers themselves and the collection of books the reader has read before, and if they liked/disliked it. This is kind of what amazon did, and is doing. You can even analyze the text to get details about the readers from their comments as well, like if they mention their family, life experience, etc, etc. The unnerving aspect of the modern age tech is that this psychoanalysis (understanding the human mind) is an easier problem than understanding an objective universe. So hypnotism might be an optimal solution to most problems. Definitely went on an over-sensational tangent on this one.

How necessary is college for software engineering if you are self motivated and taught?

I will say it would be easier to get a software engineering job with a degree than without. However, if you can pass a technical interview, and have a good portfolio/resume, it is not necessary. You can self-teach yourself the necessary skills, and everything is available on the internet.

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If you are looking to get into machine learning engineering/research as a profession, I would highly recommend getting a PhD or at least a masters in CS. The theoretical foundation is important, and employment is competitive.

Is most of the machine learning related stuff taught in school mathematics?

Thanks for your reply!

It really depends on the class. At UIUC, there were 3 main ML classes: Artificial Intelligence, Machine Learning and Applied Machine Learning. Artificial Intelligence was the intro class, mostly went over the basics, some application, some industry use cases, terminology, etc. Machine learning was very heavy math and very theoretical. There was minimal application. Applied Machine Learning was as the title implies. It was more application of advanced architectures, and way less theoretical.

I’m in university and one of the thesis offers that I got was a machine learning one and I’m pretty interested in that; can you tell me what are some things that make it a good specialization in your opinion? And how are the salaries?

There are many reasons to get in to ML, but one that got me the most interested is how ubiquitously it can be applied. Its the most general type of specialization one could manage, and that oxymoron makes it possible to be extremely technical without isolating oneself into a highly esoteric field bubble ( this is not true for all cases, but it true relative to most specialized field in CS ). I would say though, that working in ML is a lot different from that of traditional programming. Things are far less certain, and you will be working with data and your gut, more often than other specializations. As for salaries, I can't give you much life experience on that since I just went straight to my startup after I dropped out. I would recommend looking at glassdoor data for that.

Anyone tell you that you look a bit like Bighead from Silicon Valley?

You are not the first, and not the last

I have an idea: when your software is ready, implement it on openoffice. Or maybe make your own office program! I'm tired of people giving money to that bill gates guy. so, u gonna do it? :)

Way ahead of you :)

How can you call yourself an engineer if you dropped out? Is that not a protected title where you’re from?

"Machine Learning Engineer" or "Software Engineer" as far as I can tell is not a protected title.

I believe it is illegal in Texas to use engineer in your title if you do not have an engineering degree.

I live in Chicago.

Consider calling yourself a "specialist" or something squishier than "engineer" if you've got no degree to back it up. There's a reason why there are so many more "developers" than "software engineers"; that title comes bundled with an assumption that you have the skills (technical, ethical, and otherwise) conferred by an accredited university.

I admit a specialist may have been a better title, however, I do have the technical, ethical, and other skills necessary for an engineering title. I dropped out with only a single semester left in my school (don't worry, I can always go back)

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Usually I don't even use the title, I try to make my work speak for itself, however, in this situation I thought it was necessary in order to describe myself in minimal amounts of characters to as general of an audience as possible.

What advice would you give to someone wanting to learn more about computers and being a developer of a computer-based product?

Its hard to give advice that isn't vague and meaningless without a thorough conversation, about why you are interested in computers and what you want to do with them. The field of computer science is massive. I would recommend trying to try out as many niches in the field as possible, as deep as you can in the niche as possible, and figure out the parts you like, and more importantly the parts you don't like. Also try finding company that will encourage your exploration. Hackathons were a great early source for me to experiment with various ways tech can be interfaced.