No! :)
*we do continue to label data though and will probably have a large "AI Trainer" staff in place for any NEW skill we want Amy to have in the future.
At x.ai, we are building an artificial intelligence powered personal assistant. The software will schedule meetings for our customers automatically without subjecting them to the typical back and forth over email negotiating when and where to meet someone. We are looking for a smart, self-motivated, and enthusiastic individual to join us on the journey in building the artificial intelligence of the future. You’ll get to work side by side with a small team of serial entrepreneurs moving at breakneck speed.
A Backend Engineer will:
- Build, evolve and scale out infrastructure to ingest, process and extract meaning out of free form text
- Jump between architecture, implementation, infrastructure management, and firefighting
- Design and build a system that enables seamless human-machine interactions
- Solve various optimization and constraint problems related to coordinating people’s schedules and preferences
- Integrate with various external APIs
- Constantly improve our development processes and tools to reduce friction from idea to deployment
Ideal Candidate:
- Build maintainable, well tested and scalable code
- Experience with building big data processing system
- Data modeling and architectural skills
- BS or MS in Computer Science (or related field)
- Intellectually curious, collaborative, self-motivated, fast learner that is comfortable with uncertainties
- Want to be part of a passionate and collaborative team, looking to make a mark in the world
- Our backend is built in Scala so direct experience will be preferred
- Bonus: Experience with AWS, MongoDB and EMR/Hadoop
At x.ai, we are building an artificial intelligence powered personal assistant. The software will schedule meetings for our customers automatically without subjecting them to the typical back and forth over email negotiating when and where to meet someone. We are looking for a smart, self-motivated, and enthusiastic individual to join us on the journey in building the artificial intelligence of the future. You’ll get to work side by side with a small team of serial entrepreneurs moving at breakneck speed.
A Data Engineer will:
- Build, evolve and scale out infrastructure to ingest, process and extract meaning out of free form text
- Jump between architecture, implementation, infrastructure management, and firefighting
- Design, implement and evolve Natural Language Processing software modules
- Solve various optimization and constraint problems related to coordinating people’s schedules and preferences
- Constantly improve our development processes and tools to reduce friction from idea to deployment
Ideal Candidate:
- Build maintainable, well tested and scalable code
- Experience with building big data processing system
- Strong statistic background, ideally experience Natural Language Processing techniques
- Data modeling and architectural skills
- BS or MS in Computer Science (or related field)
- Intellectually curious, collaborative, self-motivated, fast learner that is comfortable with uncertainties
- Want to be part of a passionate and collaborative team, looking to make a mark in the world
- Bonus: Experience with Scala, AWS, MongoDB and EMR/Hadoop
At x.ai, we are building an artificial intelligence powered personal assistant. The software will schedule meetings for our customers automatically without subjecting them to the typical back and forth over email negotiating when and where to meet someone. We are looking for a smart, self-motivated, and enthusiastic individual to join us on the journey in building the artificial intelligence of the future. You’ll get to work side by side with a small team of serial entrepreneurs moving at breakneck speed.
A Data Scientist will:
- Design, develop and implement statistical models to carry out various novel aspects of classification and information extraction from unstructured text, such as emails or email threads
- Using a combination of judgement and experience, create hypotheses to confront complex Natural Language Processing problems
- Be capable of designing stringent tests of these hypothesis and use results to guide further development towards performance optimization
- Familiar with or eager to learn various advanced statistical techniques to solve different optimization and constraint problems related to automating the coordination of people’s schedules and derivation of implicit and explicit preferences from email-related data
- Be capable of visualizing and communicating data science concepts to other team members, and seek meaningful feedback from them
Ideal Candidate:
- Quantitative degree and/or relevant experience
- Strong statistics background, ideally experience with Natural Language Processing techniques; loves building mathematical and probabilistic models and algorithms
- Code experience in a production environment; familiar with data structures, parallelism and concurrency
- Intellectually curious, collaborative, self-motivated, fast learner that comfortable working in a dynamic environment tackling challenging problems
- Bonus: Experience with Scala, Python, AWS, and MongoDB; implementation experience with supervised and unsupervised machine learning algorithms
Well, I cc'ed Eric, Ken and Taylor, and Amy worked with them individually to find the best time. Upon conclusion, she sent the invite AND out came a $check. ;)
It's not supposed to be exciting; 87 US knowledge workers schedule a little bit above 10 billion meetings a year. I just want to help them do that (no more, no less). Users couldn't care less how it is done and I would be very hesitant to market this under any "AI"/STAT/ML/NLP moniker. So back to my starting point - we just schedule meetings.
I am not sure I would be offended if somebody called a service "Dennis" (probably the opposite). That aside, use Andrew Ingram instead, or name her yourself and move her to your domain (the most obvious premium product we have in mind).
I agree and I could easily see myself use something like that. However, I want something (naively perhaps) which my Mom can use. My worst nightmare is one where early users inadvertently create some sort of "syntax" which my mom use to discard this as a service for her. Like she discarded the idea of twitter, because people created a RT, MT $bla #bla etc. "syntax".
Absolutely agree. We must understand the social dynamics that are inherently built into every meeting - and this is one 4 major challenges we are working on going forward.
But our early beta users should not be to shy to cue in Amy:
- Amy, set something up with Lerer in Soho
- Amy, can you arrange breakfast with Matt and FirstMark please. They can pick a place.
- Amy, setup a data science / whiteboard chat for Prateek and I *
* My default meeting location is 48 Wall (Amy knows that, and simply assume I want this location used for a new candidate interview)
Building a conversation model which can negotiate with multiple guests on behalf of the host in plain english is not easy (for us). This includes simple social concepts such as "compromise" - say, when to push for one location over another. The information extraction problem alone is a major challenge.
No buzzwords needed, we are just trying to do some good work, and if we succeed, we think many people would like it: https://twitter.com/search?q=xdotai
My bad, let me rephrase, near 100%.
Super naive perhaps, but we feel it is worth a shot. Hell, we might die trying, but we'll certainly come out a whole lot wiser on the other side.
It is very hard to do an asynchronous negotiation with another human in an APP like setting. It is also hard (perhaps impossible) to create a UX experience which anticipates all potential future requests.
- Hi Amy, can we push the meeting tomorrow 20 min ?
- Hi Amy, let’s do the meeting when John is back from holidays (Friday, yes?)
- Hi Amy, Let’s do the meeting end of next week, preferably Thursday
- Hi Amy, Have John call my Skype (if he's got an account) instead of Cell, and add Linda to the invite please.
- Hi Amy, set something up with Jordy from Softbank next week, heck, I'll do something outside my scheduling hours as long as it is next week.
I scheduled 1019 meetings myself as startup founder in 2012 [0] and this is all I want, which obviously does not equal us being able to pull it off.
The human part is a data annotation part, something which helps us move towards full automation. There is obviously no way a human operation will ever get to the end of those ~10 Billion formal meetings being scheduled in the US every year. Heck, we might die trying to fully automate this and we are certainly not finished yet, but I think we are off to a good start and we are fighting for that 100% Automation goal every single day. Feel free to email me if you want to join 24 other propellerheads on that mission :)
Amy (The AI Assistant) remember all the meetings she set up for you (and she'll remind you if needed) - so even if you did not have a calendar, she would avoid conflicts (unless you hide things from her).
We have this fantasy (delusion perhaps) of us becoming arbiters of time. You don't need a calendar, because Amy will help manage your time. One step at a time though and the problem is hard enough as is, before we print "Arbiter of Time" t-shirts.