With all the terminology floating around the AI world, it’s easy to get caught up in terms and phrases and really not know what you’re talking about. We’re here to fix that. Machines (computers) have been able to “learn” from data and algorithms for 70+ years now but it really didn’t take off until the late 1990’s, spearheaded by IBM developing it’s Deep Blue Supercomputer. (Spoiler alert. The computer won. 🫣 ) It can seem like a complex topic but it’s everywhere in our daily lives so let’s break it down. We don’t want you to sound like a chump when you don your glasses at your partner’s company dinner.

What is machine learning, exactly? 🤓

Machine learning is artificial intelligence (AI) that enables computers to learn from experience without being explicitly programmed. It’s like teaching a child how to ride a bike – you provide guidance and support independently, and the child learns independently through trial and error, and a broken arm or two…

Machine learning uses algorithms, rules, or instructions to analyze vast amounts of data, identify patterns, and make predictions or decisions based on that information. The more data the computer processes, the better it becomes at making accurate predictions, just like how humans improve their skills through practice, except machines don’t need coffee breaks.

So Where is Machine Learning in our lives? 😵

Great question - everywhere really, but you wouldn’t know it. Let’s look at a few areas that will hit home:

Personalized Recommendations

You’re scrolling through Netflix right and the hits just keep on coming. Like, how do they know that I’m a sucker for the latest teeny-bop Romcom?!? You guessed it. Machine learning algorithms. They analyze your viewing history, compare it to others with similar preferences, and voila! Binge-worthy content as much as your heart desires.

Fraud Detection

Ever gotten a notification from your bank about suspicious activity? Banks use machine learning models to analyze transaction history to detect activity that’s not common among your spending habits so you can be alerted.

Voice Assistants

Alexa much? Yep. Her too. Machine learning. Who knew machines could be so helpful and chatty? She processes your spoken commands (yep they’re listening), understands your intent, and provides relevant information or processes the command on your behalf.

Traffic Predictions

Google Maps and other navigation apps use machine learning to analyze data from millions of users, historical traffic patterns, and real-time updates to estimate travel times and suggest the most efficient routes. Unfortunately, this won’t help you on the 405 in L.A.

Medicine and Medical Diagnoses

Advances in the medical field are making huge strides with machine learning. Patient monitoring, developing diagnostics (analyzing MRIs and X-rays), and reconstructing diseases are just a few of the ways that machine learning is enabling doctors and researchers to do their jobs better and more efficiently so we’re all healthy and wise

So - do you feel smarter? Did you learn something? Machine learning is an exciting and rapidly-evolving field shaping our lives and work. While the concept may seem complex, understanding the basics is essential in today’s digital age.

As machine learning advances, its applications will only grow, improving countless industries and aspects of daily life. By staying informed and understanding the technology’s potential, we can better adapt to these changes and make the most of the opportunities that arise, like having a robot butler.

Want to learn more? Read more here

🫡 AI Government Regulation

Congress has been holding sessions with founders of AI companies (most notably OpenAI founder Sam Altman) to talk about how to most effectively regulate and control AI for the safety of U.S. citizens and protection from bad actors. Just so you’re in the loop and know how this might affect you, there are 4 areas that seem to be open for government oversight:

1. Data Privacy and Protection Regulation

   1. Algorithms are data-hungry. The way this data is sourced, the nature of it, and how it is processed and stored is one of the biggest talking points surrounding AI regulations.

2. Development of an Ethical AI Framework

   1. AI companies preach “safe and ethical AI” - but who’s making the rules? Who decides what safe AI looks like? Something to watch.

3. Dedicated Regulatory Agency

   1. Yep. Another government agency is up for discussion.

4. Addressing Copyright and Intellectual Property Concerns

   1. AI-specific copyright laws are on the table. Algorithms are rich with copy-written material. How are the rights of original content creators safeguarded? We shall see.

😰Let AI Coordinate Your Family’s Chaos

We recently learned about Milo - an AI co-pilot for parents. (Get on the waitlist here.) Powered by ChatGPT, Milo promises to take all the chaotic communication within a family - texts, grocery lists, screenshots, late-night rambling memos - and Milo will sort it out and keep your family intact and on time.