We often talk about Artificial Intelligence's applications – meaning, what we use it for – but we often forget to talk about a more crucial question:
How do we use AI effectively?
Many people misuse AI. They think they can simply plug in a dataset, press a button, and poof! Magically, an edge appears.
Most commonly, people lack the infrastructure (or the data literacy) to properly handle even the most basic algorithms and operations. And even before that - they haven't even properly assessed whether AI is needed in their business. Remember, AI is a tool, not the goal.
Even though this is the golden age of AI ... we are just at the beginning. Awareness leads to focus, which leads to experimentation, which leads to finer distinctions, which leads to wisdom.
Do you remember Maslow's Hierarchy of Needs? Ultimately, self-actualization is the goal ... but before you can focus on that, you need food, water, shelter, etc.
In other words, you most likely have to crawl before you can walk, and you have to be able to survive before you can thrive.
Artificial Intelligence and Data Science follow a similar model. Here it is:

Monica Rogati via hackernoon
First, there's data collection. Do you have the right dataset? Is it complete?
Then, data flow. How is the data going to move through your systems?
Once your data is accessible and manageable you can begin to explore and transform it.
Exploring and transforming is a crucial stage that's often neglected.
One of the biggest challenges we had to overcome at Capitalogix was handling real-time market data.
The data stream from exchanges isn't perfect.
Consequently, using real-time market data as an input for AI is challenging. We have to identify, fix, and re-publish bad ticks or missing ticks as quickly as possible. Think of this like trying to drink muddy stream water (without a filtration process, it isn't always safe).
Once your data is clean, you can then define which metrics you care about, how they all rank in the grand scheme of things ... and then begin to train your data.
Compared to just plugging in a data set, there are a lot more steps; but, the results are worth it.
That's the foundation to allow you to start model creation and optimization.
The point is, ultimately, it's more efficient and effective to spend the time on the infrastructure and methodology of your project (rather than to rush the process and get poor results).
If you put garbage into a system, most likely you'll get garbage out.
Slower sometimes means faster.
Onwards.
The Rise of Remote Work
Remote work has been increasingly popular because of the pandemic ... but even as more people have vaccines, and some are even getting booster shots, the love for remote work stays.
But some industries are adopting it more than others.
I'll be honest ... when I first saw this, I was like, "Retail's that low? That can't be right". But then I realized... I never really go to stores. What would I know?
Seeing the rise of remote work in Media & Tech is unsurprising. But, I will be curious to see what percentage of these businesses stay remote as we move further away from the "worst" of Covid-19.
As I mentioned in this video, hybrid solutions are the answer. There's too much benefit to the culture of companies that spend real time together in person. While I believe productivity can remain high at home or in the office, the sense of camaraderie is hard to sustain if you rarely see each other in real life.
That being said, employees are reporting being happier and more productive at home. Consequently, I wouldn't bet on the move back to the office happening quickly. Meanwhile, companies also are suffering through the "great resignation." Clearly, the game has changed – and so must their strategies and tactics.
The culture of work is in a massive period of transformation. Regardless of where your specific company or industry ends up, all businesses will have to increase the amount of employee care they provide. Just as the heart of AI is still human, so is the heart of our businesses.
You shouldn't be forced to take care of your employees ... you should want to. This past year+ has been challenging for everyone, and it's important to keep that in mind as you make decisions.
Posted at 10:02 PM in Business, Current Affairs, Healthy Lifestyle, Market Commentary, Personal Development, Science, Web/Tech | Permalink | Comments (0)
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