When you think about the future of artificial intelligence (AI) technology, it’s likely that you don’t think of auto-completion. However, you probably should. In July 2020, OpenAI released a beta testing version of GPT-3, a new auto-completion program that could very likely define the next decade of AI programming.
A year after unveiling CoreML, Apple introduced CreateML. CreateML allows developers to train machine learning models on their Mac. We will stick with our previous example and build a simple machine learning model that can recognize images of dogs. Head over to https://github.com/RichardBlanch/Dog-Classifier/tree/Starter and download or clone the project.
“WHAT THE HECK?! HOW CAN I UNLOCK MY PHONE WITH MY FACE?!”
Those were the words that came out of my mouth in October of 2017, as I pored over the user manual for my new iPhone X. It wasn’t all hyperbole, either — I really wanted to know, and I ended up dedicating quite a bit of time to learning about the science behind Apple’s new facial recognition technology. In the end, the answer to my question boiled down to two words — machine learning.
Alternate Title: The Self-Driving ABCs
My boyfriend’s dad’s car was recently broken into. By itself, this would be a pretty low note to start a blog post with, but rest assured that nothing was stolen and only one window of the car had to be replaced. The situation was made 100 times better by the fact that he was lent a Tesla Model X while his own car was being serviced.
My goal for this post is to share how I answered a seemingly simple question — what should I learn in my free time?
While developing software in Silicon Valley is educationally rewarding on a daily basis, there is still so much more to learn. Tech news is constantly bombarding readers with new technologies like blockchain, machine learning, and autonomous-(insert vehicle type here). Staying ahead is exciting for me, but also critical to my career.
I considered a few ways figure out what is “hot”: