If you’ve turned on the television at all in the last few years, you’ve no doubt encountered at least one show about forensics. However, one of the fields of forensics that is rarely depicted is the ever-growing field of digital forensics. In a world where we are more and more dependent on our technological devices, digital forensics is becoming ever more important.
Genetic algorithms (GA) are directed search algorithms based on the mechanics of biological evolution. They are powerful tools capable of generating solutions to complex optimization and search problems that would otherwise be extremely hard or time consuming to complete by human trial and error alone.
As website developers, automation can increase our capacity to do more, reduce the time and cost of our projects, and allow us to skip the boring parts of our job (let’s be honest!).
I began developing at a time when there were no helpful tools like frameworks, user interface (UI) kits, application programming interfaces (APIs), or software development kits (SDKs) to speed up our processes. Over time, I’ve seen innovations like these change the pace and possibilities in web development. And now, with the creation of cloud services, we can even do our work from the comfort of our homes rather than relying on dedicated server racks at the office.
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”: