Jake McCuistion
Relentless. Creative. Perfectionist.
Meet Jake
I'm an accomplished full-stack engineer with extensive experience in Swift, Objective-C, Java, Python, Javascript (MEAN), PHP (LAMP), and high-performance SQL/NoSQL. Born in Southern California and raised in the Rocky Mountains of Colorado, I've been immersed in Computer Programming and Desktop Publishing since childhood.
At a very young age, my Dad (who was a software engineer at the time) taught me programming concepts in FoxBASE. I wrote my first full program at age nine in BASIC, more than 24 years ago. At 12, I created my first commercial website. In high school, at 16 years of age I rewrote and expanded a large billing, inventory, and CRM database system for a publishing house.
In only three years of college I earned two degrees, graduated with honors, completed several networking certifications, and started a business in web development. That company continues on today, ever-expanding and pushing the limits of technology: I was seventh in line for the first iPhone, worked on iPhone apps before the App Store existed, began working on iPad apps before the launch, and have worked on all aspects of the Apple ecosystem including iOS, watchOS, tvOS, and macOS.
My Portfolio
"Great to work with – professional, responsive, and talented." – Phil B.
"Did a fabulous job." – Stan S.
"Completely exceeded all my expectations." – Steve A.
Things I Like
Check out the things I love, use regularly, know a good deal about, or am nostalgic for:
- 1Password
- 4th Dimension
- Actionscript
- Airflow
- Algolia
- Angular 2
- AngularJS
- Applescript
- Aurelia
- Azure
- Babel
- bash
- Bokeh
- BrowserLabs
- conda
- DD-WRT
- Docker
- Evernote
- Flask
- FoxBASE
- FoxPro
- git
- Google Analytics
- Grunt
- Gulp
- HBase
- HDF5
- Hadoop
- HeyAnita
- iOS
- IoT/IoE
- JQuery
- JSON
- JavaScript
- Jupyter Hub
- Lambda
- Linux
- log4cxx
- macOS
- MySQL
- NFC/RFID
- Nginx
- Node.js
- Numba
- Objective-C
- OmniFocus
- PHP
- Pandas Numpy
- Parallels
- Perl
- Photoshop
- PostgresSQL
- Puppet
- PyPy
- Python
- RESTful
- React
- RedHat
- Redis
- rsync
- RxJS
- Salt
- Scikit Learn
- Slurm
- Spark
- StuffIt
- TED Talks
- Tornado
- Transmit
- TweetDeck
- TypeScript
- Ubuntu
- WebPack
- Windows Server
- Xcode
- ZeroMQ
Let's Talk
Phone
510.866.0660
hello <at> jakemccuistion.com
Google Plus
+Jake McCuistion
@jakemccuistion
Chat
Skype: jakemccuistion
Teleconference, Webinar, and In-Person Training
Jake is available for corporate seminars and one-on-one training in the areas of Mobile Strategy, Cloud Data Services, and Digital Publishing.
Too Much Information
The Blog:
A Computer Wrote This Blog Post
How would you know if a computer wrote this blog? Would you be able to tell? That was the idea behind Turing's test — could a machine one day imitate the intelligence of a human at a level that would be difficult or impossible for other humans to distinguish.
A single computer is better at some types of math than most humans because essentially a computer is a high-powered calculator. But how about making a machine think like a human? That requires lots of input for "learning" to take place, and new models for architecting software. One cannot simply write a logic program and expect the desired result. There are too many variations on input and output. If the input has to be structured, then you've lost the battle. If the output follows procedural instructions too closely it will be obvious to humans, as humans are pattern-seeking creatures.
In fact, up to this point computers have become indispensable tools in areas of rules enforcement. Accounting, invoicing, form letters, POS, these were the very first software applications. I think about this every time a manager must be called to override the computer with a key to process my purchase or return at a store. A new wave of applications are here for a computer that can learn including computer vision, fighting crime, and managing investments.
What we are really talking about here is Deep Learning. Similar to the confidence you have in the spelling of the word "California" versus the confidence you have that "Llanfairp wllgwyngyll goger ychwyr ndrobwllll antysil iogog ogoch" is spelled correctly (a Welsh place name). A human learns by exposure to input and learning from mistakes, and humans use those confidences built up over time to make predictions about new experiences. That's the idea behind deep learning. It takes an enormous amount of compute power, and more research, but one day a computer may be able to write this blog post better than I can.
Twitter: