Ah, 2023, the year when artificial intelligence (AI) took over the world. Everyone and their grandmothers are talking about it. If I have to read one more article about how there is a 5% chance that AI will go nuts and take over the world, I am going to throw my computer out the window.
Perhaps the biggest surprise of 2023 isn’t ChatGPT; rather, it’s the fact that a company that was only known in very specific circles suddenly took the world by storm and blindsided Google, Amazon, and every other tech giant. OpenAI didn’t just create a killer app, they literally released the fastest-growing app in history. It was an overnight success.
No one could have seen it coming, not even the people working at OpenAI, who suddenly got the message from upper management that they were going to create an app. It was a gamble, and it paid off. The massive popularity of LLM has taken over the tech industry, and investors have taken an interest in what OpenAI has planned for the future.
In parallel, their other model Dall-e has fallen behind competitors like Stable Diffusion and more—specifically Midjourney—but once again, image generation blindsided big tech. What were they doing?
How Companies Grow Stagnant
I’ve been in the software development game for quite a while, and I’ve noticed how big companies can become complacent in their success. They get comfortable on top of the hill they worked so hard to climb and forget about the dangers lurking below.
It’s like being at the beach and building an impressive sandcastle only to realize that, as high tide approaches, your castle will soon be nothing but grains of sand again. But instead of preparing for high tide by continuing to build and fortify their structure, some companies just kick back with a piña colada and assume everything will be hunky-dory.
But let me tell you something from experience: It won’t be okay. Success isn’t an excuse to sit still; it’s actually a reason to take more risks, try new things, and innovate even more! Otherwise, you’re essentially setting yourself up for failure.
Think of it this way: imagine you’re running a marathon. You’re in first place with only 1 mile left until the finish line. Do you slow down because you know no one is ahead? Hell no! That’s when you push even harder than before—because victory is right there!
Now apply this same mindset to business strategy—pushing boundaries rather than resting on laurels—and watch innovation happen like never before.
When you’re working within a behemoth corporation with bottom lines as deep as ocean trenches, embracing uncertain ventures can be daunting at best and downright detrimental at worst. But this aversion to risk can quickly become the kiss of death for these companies.
I remember when I signed on with a major software development company—one whose name you’d surely recognize if I divulged it—where innovation was treated like an abstract concept rather than a tangible goal. They were afraid to disrupt their established routines and instead spent most of their efforts playing catch-up with smaller competitors who had taken chances they hadn’t even considered.
What they didn’t realize is that avoiding risk-takers often results in stagnation. Standing idle while others move forward will lead nowhere but obscurity-ville.
How? By resisting change and advancements that could open new gates for progress or—dare I say it—disruption.
A company’s fear of failure is understandable—no one wants to lose their footing—but it can also be incredibly harmful if not managed properly. Embrace innovation and risk-taking; otherwise, the competition will do it instead and leave you running after them trying to keep up.
The Innovation Paradox: Why Big Companies Struggle to Innovate
Why is it that these big companies, with all their money and resources, can’t seem to innovate and evolve as the startups do? It’s like they’re stuck in some kind of time warp where everyone is still using flip phones and listening to CDs.
Here’s the thing: When a company gets too big, it’s more difficult to take risks. There are more people involved in decision-making, which means there are more opinions and egos at play. The fear of failure grows stronger as you climb up that corporate ladder. No one wants to be responsible for wasting millions on something that ends up being a flop.
Think about it. How will investors react to a call where the CEO says, “Hey, we are betting all our money on something that has been proven before”? There is a reason why Hollywood is so obsessed with movie remakes instead of building new brands.
But here’s where the paradox comes into play: Innovation requires both risk-taking and resources. You can’t create something truly groundbreaking if you’re not willing to put everything on the line. That’s why small startups tend to be so innovative—they have nothing to lose!
See where I’m going? The more resources you have, the more cautious you become; that’s prospect theory, one of the most widely regarded and respected theories in psychology and economics. So, companies that have a lot of resources tend to be risk-averse, while companies with fewer resources are bigger risk-takers.
It also doesn’t help that big companies tend to move slowly compared to their smaller counterparts. They have layers upon layers of bureaucracy that slow down any progress toward innovation or change.
These companies must remember what made them successful in the first place: experimentation! Back when things were just starting out, failure was an expected part of growth; nowadays, it seems many industries have become less tolerant of instances where initial discoveries lead to weeks or months of setbacks in efficiency and innovation. They need to go back to that mindset of taking risks, experimenting with new ideas, and trusting their team’s expertise.
Answering the Call: Google Bard and Amazon Bedrock
Of course, big tech wasn’t going to sit still. Once again, perception is everything in terms of marketing and attracting investors. In a matter of days, both Google and Amazon were showing their own version of language models: Google, in the context of search engines, and Amazon—we’ll get to them in a little bit.
Bard’s first demo was a disaster, replying with erroneous information during a makeshift presentation. Now, we know that these models aren’t perfect. In fact, they are quite prone to mistakes, but this isn’t some rando asking why the sky is blue. This is a multimillion-dollar company sending a message to its investors that they have everything under control and that they too, can do whatever is trending now.
How do we know that it was makeshift? Just look at the quality of the presentation of the now-dead Stadia vs. that first Bard demo—it’s as if we were watching two completely different companies.
And yes, that whole fiasco had consequences, with Alphabet losing $100 million in market value overnight.
Now, I have been playing around with Bard, and while it’s not as powerful as ChatGPT and not as elaborate as Bing, it’s actually a really good implementation. It’s pretty experimental, but if Google sticks by its side, they have a very good product on their hands. Unfortunately, that first demo was enough to turn Bard into a meme.
Amazon, on the other hand, took another route. Instead of presenting an LLM, they instead unleashed what we can basically call a Foundational Model as a Service. Amazon Bedrock is a suite of software solutions for companies big and small to leverage the power of AI by making it easy to fine-tune models for specific needs.
Now, that’s thinking big—except for one little detail: the product does not exist, at least not to the public at large. As of the time of this article, Bedrock is being previewed by a select group of clients. In other words, while Amazon is actually trying to gain some ground by providing Bedrock as an AWS solution, right now, it’s but a promise.
Personally, I can’t wait for Bedrock. I am an AWS fan, and I’m sure that whatever Amazon releases is going to be a lot better than OpenAIs current API (and overwhelmed models that keep throwing errors because they are working at capacity).
It’s obvious that OpenAI took the lead, and the giants were not ready for the impact LLMs were going to have in society. AI is nothing new, but if my Twitter interactions are anything to go by, people are going crazy over what can be accomplished with ChatGPT and offerings like Adobe’s new AI.
From trailblazers to chasers, big tech is now chasing the white rabbit. What they have in their favor is resources—massive amounts of resources—to throw at their products and hope that something marketable comes out of the other side. But if leaks are to be believed, it doesn’t seem like they are going to get ahead in the race anytime soon.
Having said that, the fact that they have been able to garner their troops and refocus their efforts in such a short amount of time is quite impressive. And there is a lesson to be learned there: No matter how huge you are, the world will throw you curveballs, and you have to find a way to adapt as quickly as possible.
The Role of Data and Analytics in Adapting to Disruption
Alright folks, it’s time to talk about the big “D” word—disruption. Yes, I said it! It’s happened to all of us at some point in our lives. You know when everything is going great and then—BOOM!—the unexpected hits you like a ton of bricks. What was once considered a lucrative business model becomes outdated overnight, and you’re left scratching your head, wondering what’s next. However, fear not, my friends, because there’s good news on how businesses can adapt to these changes.
Enter data and analytics—two words that have been popping up endlessly in the world of tech for years now but are more relevant than ever before when it comes to adapting to disruption.
As software developers, we thrive using dialects such as Python or Javascript; designing various AI and machine learning algorithms is what gets us pumped every day. But let me tell you something—these same concepts translate seamlessly into helping big companies adapt quickly during times of change.
Let me paint you a picture by sharing an anecdote from one of my favorite Netflix shows—Narcos. Remember those Colombian drug lords who would use informants’ details in order to evade police capture? Well, same principle here, we use data to make educated guesses (what we like to call predictions) to keep companies on the lookout for potential problems—of course, we are not talking about anything illegal here.
Metaphors aside, folks, implementing analytics has allowed companies to focus on agility rather than stability, which ultimately gives their profit margin substantial protection against any sudden downswings within volatile markets. Now isn’t that exactly what we need during difficult times?
Case in point, while ChatGPT came out of nowhere, the signs were already there. For months people had been talking about generative AI, about image generation, and about text and language models. In hindsight, it was obvious after the debacle of crypto and the utter failure of the metaverse, something had to fill the void.
Of course, data analytics isn’t enough; it has to go hand in hand with a business culture based on evolution and adaptability.
Building a Culture of Agility and Flexibility in Large Organizations
As software development experts, we all know how critical it is to stay nimble and adaptable. Our industry moves at an insanely fast pace, and if you’re not flexible enough to keep up with the trends, then you are bound to fall behind.
But building a culture of agility and flexibility in large companies? Now THAT’S a challenge. As someone who has worked with many big players in the tech world, I can tell you that this is no easy feat. For starters, getting everyone on board can be incredibly tough.
When you have teams spread out around the world working on different projects with varying levels of urgency, it can be difficult to convince them that adopting an agile approach will benefit them in the long run. Some people might think, “Why should I change what I’m doing when my current system works just fine?”
Imagine your company is like an aircraft carrier navigating through stormy waters ahead. Using traditional methods would mean turning that giant vessel very slowly when facing obstacles because sudden turns would lead it straight onto dangerous ground. By encouraging employees at every level to adopt an Agile mindset, they’ll make sure their helm is always prepared for whatever comes next and steer clear from danger much quicker than conventional approaches ever could.
Another key factor here is transparency. Without having full visibility across all your teams, it’s really impossible to work toward establishing any type of corporate cultural shift. To get buy-in from everyone involved AND sustain momentum during the transition phase, we must foster a candid environment that encourages open communication among team members.
Case Study: Netflix’s Transformation from DVD Rental to Streaming Giant
Let’s dive into Netflix’s transformation from DVD rental to streaming giant. It all started with Reed Hastings, who realized that the future of home entertainment was online streaming rather than DVDs. He saw disruption coming and decided to be proactive about it.
But adapting wasn’t easy for Netflix either—they stumbled along the way before finding their footing. Remember when they tried separating their DVD and streaming services under two different names? That was a total disaster because customers hated having to manage two separate accounts—talk about shooting yourself in the foot!
However, Netflix learned from its mistakes and made bold moves like creating original content, which ultimately paid off big time (hello Stranger Things!). They also utilized data analytics to understand what types of shows people want to watch before even producing them.
Overall, Netflix’s adaptation is an excellent example of how companies can turn disruptive forces into opportunities for growth. They were able to anticipate change early on and make radical decisions instead of clinging stubbornly to outdated business models.
Conclusion: Breaking the Stagnation Cycle in Big Companies
Ah, the dreaded “stagnation cycle.” It’s like quicksand for big companies—once they get sucked in, it’s tough to break free.
But fear not, my fellow software development enthusiasts! There is hope.
From my experience working at various tech companies (both large and small), I’ve learned a thing or two about how to avoid getting stuck in this vicious cycle. And let me tell you—it all starts with having an open mind.
I know, I know—that sounds cheesy. But hear me out!
The thing is, when you’re part of a huge organization with long-established routines and processes, it can be easy to fall into the trap of thinking that “this is just how things are done here.” You might start feeling like anything new or different would disrupt the delicate balance and cause chaos.
And honestly? That kind of attitude is what leads to stagnation. When people stop questioning why things are done a certain way and exploring whether there could be better alternatives out there…well, that’s when progress screeches to a halt.
So if you want your company to break free from the stagnant swamp tradition, start by encouraging everyone on your team to challenge assumptions and brainstorm new ideas without fear of judgment or reprisal. Make sure everyone feels empowered not only to identify problems but also to suggest solutions—even if they seem unconventional at first glance.
Because ultimately? The most successful organizations aren’t ones that cling stubbornly to outdated practices in order to maintain the status quo; rather, they’re constantly evolving and adapting based on feedback from employees/customers/etc., always striving toward something better.
It won’t happen overnight (trust me on this one), but breaking free from stagnation requires perseverance and open-mindedness. If we can foster those qualities within ourselves and our teams…who knows where we’ll end up? Sky’s the limit.
