Tag Archives: openai

Gemini vs. ChatGPT: Will Either Become Our New Habit?

Two tall skyscrapers with digital data patterns glowing on their surfaces at dusk in a cityscape

Back 20 years ago when I spoke about search, I used to talk a lot about the “Google Habit.”  In the remarkably short time from its debut to the early 2000s, Google had become our defacto search choice. In fact, it was so dominant, we didn’t even consider its competitors. We didn’t think at all…we just Googled. That is how a habit works. We do things without thinking about them.

Fast forward 20 years. Google still dominates the information retrieval space. When we talk about worldwide search, Google delivers the results on 9 out of every 10 searches launched. It’s monolithic presence in the online landscape hasn’t really changed. But the way we navigate that landscape is beginning to. For the first time in a long time, Google has a real competitor when it comes to the way we look for our answers.

Another favorite topic of mine, following hard on the heels of the “Googe Habit,” was talking about the “usefulness of search.” I argued that while Google did a good job of retrieving information, it feel well short of the goal of making that information immediately useful to us. Today, with agentic A.I., the tantalizing promise of usefulness has finally arrived. The question is, what tools will we use to mine that usefulness?

The battle seems to be between Google’s Gemini, deeply embedded in the entire Google ecosystem, and OpenAI’s ChatGPT, a standalone app. Anthropic’s Claude is currently focused on the enterprise AI market.

Back two decades ago, I envisioned search gradually disappearing “under the hood” of various apps that made our lives easier. The act of actually retrieving information would be one step removed from us. What we would interact with would be a distillation of that information, formed into something we could use to do the things we wanted to do. What I didn’t anticipate was the emergence of the Large Language Model that currently powers ChatGPT and other AI models.

But as it currently stands, the act of retrieving information that we can use and the act of processing huge reams of text to predict useful responses are quickly converging. For an ever-increasing number of queries (currently about 50%) Google’s Gemini AI answers are now predominately displayed in the prime real estate of the search results page, straddling the very top of the “Golden Triangle.”  And ChatGPT is increasingly asked to retrieve specific information as users interact with its chatbot. Both Google and OpenAI realize that the future lies in a hybrid of the two.

The battle now is for either Google or OpenAI to dominate the various user interfaces in our personal technologies. And in this regard, it will be hard to beat Google. This January, Google and Apple inked a deal that would make Gemini the foundational AI platform for a future version of Siri. It’s already embedded in all Android devices. OpenAI’s early mover advantage over Google in terms of consumer AI usage is rapidly disappearing, with the two currently running almost neck and neck (36.6% for ChatGPT vs 27.4% for Gemini, according to a recent Emarketer forecast).

Brian X. Chen, lead consumer technology writer for the New York Times, indicated in a recent article that Emarketer’s numbers could be understating the competitiveness of OpenAI’s rival.  Google said at their recent Google I/O conference that in one year, the number of people using the Gemini chatbot more than doubled to 900 million. That puts it in a dead heat with ChatGPT and, if current growth rates continue, moving well past it in the next year.

Chen points out another massive advantage for Google’s Gemini over OpenAI’s ChatGPT. While OpenAI’s numbers are not public, they likely lost between $8 and $9 billion last year. Even the most optimistic forecasts don’t put OpenAI in a profitable position til 2029.

Google, thanks to its dominance in the online ad space, made a profit of $112 billion in 2025 on revenue of $386 billion. It will be relatively easy for Google to fold Gemini into that vast advertising supported ecosystem, moving to a cash positive position almost immediately. Because of the enormous development costs of AI, it’s hard to argue with the logic that player with the deepest pockets will be the ultimate winner.

OpenAI’s Q* – Why Should We Care?

OpenAI founder Sam Altman’s ouster and reinstatement has rolled through the typical news cycle and we’re now back to blissful ignorance. But I think this will be one of the sea-change moments; a tipping point that we’ll look back on in the future when AI has changed everything we thought we knew and we wonder, “how the hell did we let that happen?”

Sometimes I think that tech companies use acronyms and cryptic names for new technologies to allow them to sneak game changers in without setting off the alarm bells. Take OpenAI for example. How scary does Q-Star sound? It’s just one more vague label for something we really don’t understand.

 If I’m right, we do have to ask the question, “Who is keeping an eye on these things?”

This week I decided to dig into the whole Sam Altman firing/hiring episode a little more closely so I could understand if there’s anything I should be paying attention to. Granted, I know almost nothing about AI, so what follows if very much at the layperson level, but I think that’s probably true for the vast majority of us. I don’t run into AI engineers that often in my life.

So, should we care about what happened a few weeks ago at OpenAI? In a word – YES.

First of all, a little bit about the dynamics of what led to Altman’s original dismissal. OpenAI started with the best of altruistic intentions, to “to ensure that artificial general intelligence benefits all of humanity.”  That was an ideal – many would say a naïve ideal – that Altman and OpenAI’s founders imposed on themselves. As Google discovered with its “Don’t Be Evil” mantra, it’s really hard to be successful and idealistic at the same time. In our world, success is determined by profits, and idealism and profitability almost never play in the same sandbox. Google quietly watered the “Don’t be Evil” motto until it virtually disappeared in 2018.

OpenAI’s non-profit board was set up as a kind of Internal “kill switch” to prevent the development of technologies that could be dangerous to the human race. That theoretical structure was put to the test when the board received a letter this year from some senior researchers at the company warning of a new artificial intelligence discovery that might take AI past the threshold where it could be harmful to humans. The board then did was it was set up to do, firing Altman and board chairman Greg Brockman and putting the brakes on the potentially dangerous technology. Then, Big Brother Microsoft (who has invested $13 billion in OpenAI) stepped in and suddenly Altman was back. (Note – for a far more thorough and fascinating look at OpenAI’s unique structure and the endemic problems with it, read through Alberto Romero’s series of thoughtful posts.)

There were probably two things behind Altman’s ouster: the potential capabilities of a new development called Q-Star and a fear that it would follow OpenAI’s previous path of throwing it out there to the world, without considering potential consequences. So, why is Q-Star so troubling?

Q-Star could be a major step closer to AI which can rationalize and plan. This moves us closer to the overall goal of artificial general Intelligence (AGI), the holy grail for every AI developer, including OpenAI. Artificial general intelligence, as per OpenAI’s own definition, are “AI systems that are generally smarter than humans.” Q-Star, through its ability to tackle grade school math problems, showed the promise of being artificial intelligence that could plan and reason. And that is an important tipping point, because something that can rationalize and plan pushes us forever past the boundary of a tool under human control. It’s technology that thinks for itself.

Why should this worry us? It should worry us because of Herbert Simon’s concept of “bounded rationality”, which explains that we humans are incapable of pure rationality. At some point we stop thinking endlessly about a question and come up with an answer that’s “good enough”. And we do this because of limited processing power. Emotions take over and make the decision for us.

But AGI throws those limits away. It can process exponentially more data at a rate we can’t possibly match. If we’re looking at AI through Sam Altman’s rose-colored glasses, that should be a benefit. Wouldn’t it be better to have decisions made rationally, rather than emotionally? Shouldn’t that be a benefit to mankind?

But here’s the rub. Compassion is an emotion. Empathy is an emotion. Love is also an emotion. What kind of decisions do we come to if we strip that out of the algorithm, along with any type of human check and balance?

Here’s an example. Let’s say that at some point in the future an AGI superbrain is asked the question, “Is the presence of humans beneficial to the general well-being of the earth?”

I think you know what the rational answer to that is.