AI and machine learning evolved significantly in the past year, which begs the question: What’s next? Where are these technologies going and how will they further impact our way of life in a time that has been anything but predictable?
Large health insurance companies are using technology that’s been more or less proven and established for about two years. But in that time, they’ve also realized that taking this technology to the customer is a considerable expense and it takes them quite a while just to create usable applications from it. What’s more, it’s very hard for them to predict which of these applications will flourish and where. This would seem to be an exceptional opportunity to develop and deploy machine learning and AI applications that can more comfortably make these predictions on behalf of the insurance companies, hopefully helping them to answer the question of “which technology should we bet on based on the odds that it will pay off?”
Separately, the next time you speak with your physician, ask them how often they’re using machine learning. You’ll probably get some hilarious responses and blank stares because they don’t know what you’re talking about. “Machine learning? What’s that?”
Yet, machine learning is creeping into the healthcare field because machine learning systems made for the industry are being “trained” at scale to perform. It might require millions of dollars to train them, but they can be deployed once the system is introduced. This process can provide a template for billions of subsequent systems to be developed, trained, and deployed in an environment. And guess what? The technology continues to improve over time. So much so that healthcare workers forget that there was ever an option before this one.
That’s the future that’s coming for healthcare and could arrive this year.
Yes, autonomous driving is here and more people are driving cars with Full Self-Driving (FSD) than ever. Including myself. I have a Tesla now and I can say that I’m not particularly comfortable with FSD. The car itself has certain quirks that make it a little bit of a, well, “control freak.” For example, if you’re driving for the street and there is a car in front of you going through a stoplight, that’s no problem if the light is green. It will follow the vehicle in front of you. However, if there is nobody in front of you as you approach a stoplight, the car will start flashing a message that says, “Stoplight Coming In 400 Feet.” To avoid the car from stopping, I need to press the acceleration to indicate to keep going. But why do I get a message about an upcoming stoplight now rather than consistently, regardless of whether or not a car is in front of me?
When I tell the car to take me home, I’ll enter a highway in which the lanes will inevitably change. Well, the car doesn’t start changing lanes on its own. I don’t know when it’s going to change and if I tell it to change lanes, sometimes it doesn’t go that fast. That’s not perfectly safe.
Finally, it’s a car that may be autonomous, but that also means it’s not going to voluntarily go over the speed limit. Safe, yes. But we all have needed to go just a little bit faster at some point or another, haven’t we?
All of this is to say that autonomous driving may take you from point A to point B, but there is still room for improvement in filling the human driving experience gaps where we have complete control. We need to change lanes at a moment’s notice, not wait for when it may or may not happen. We need to lean on the accelerator at times, even if it’s a few miles over the speed limit. And we need the consistency of knowing what conditions and signs are coming up on the road, no matter how many cars are around us.
These are things that we know to do in the moment, but the autonomous car as is doesn’t know to do 100% of the time. They’re safe but not always selecting the practical option based on the experience around the car. This year, the next step in AI and machine learning could help autonomous cars evaluate the environment and respond in a more realistic, instinctual, intelligent way that is ever closer to the human experience. This is the gap that, once bridged, could be a phenomenal leap forward for autonomous driving as we know it. Will we see this in the subsequent software releases this year? It’s entirely possible
Talman Advantage #1: Our Connections Run Deep
Why is it so critical that Roy Talman be the first recruiter you talk to? Before your resume is casually distributed to others, it’s important to understand how valuable it is to work with someone who brings a credible and highly reputable network of hiring managers. We’ve cultivated relationships with these managers for over 30 years – in fact, many of them were our candidates at one point. But if you distribute a resume before we can leverage such connections to identify the best firm and role for you, it may be very difficult for us to help you further. So before you send out a resume, Talk To Talman First!
The Inflection Point Is Coming
We are approaching a moment in time of the very things that computer scientist and futurist Ray Kurzweil predicted would happen ten years ago. We are on the singularity spectrum. There are fascinating stories from China about a company backed by Alibaba that has developed a chip that performs 2200 trillion operations per second (TOPS). Wow! To put that in perspective, two computer chips that go inside a Tesla are 36 TOPS.
What does that mean for us in 2022? Imagine if a chip with this massive processing power is integrated into our way of life on a larger scale. It could happen as soon as this year. When it is normalized to have chips that perform 2200 total operations per second in autonomous vehicles, it will not be unusual in several locations to see truck deliveries made by fully autonomous vehicles following a fixed route. Or an autonomous vehicle that delivers your groceries. Even to some degree, we may see increased drone delivery. All of this is coming. It’s just a matter of when it occurs – in 2022 or 2023. From there, how much might it change lives? Not overnight. It could take five years to truly “feel” a national shift to such advancements as autonomous driving and it’s probably never going to be 100% adoption. But could it realistically be 40-50% adoption? Absolutely. And that is huge.
In a world where everything can change with the development of a single chip, it’s good to know there’s a partner to help technology and high-frequency trading firms stay ahead of the curve with a pipeline to the most coveted talent available: Roy Talman & Associates. Don’t wait for the future to arrive to identify the next great leaders for your team. Talk To Talman First.