Why Google’s BARD will beat ChatGPT

From a Machine Learning Perspective, Google has several advantages over Open AI and Microsoft.

Published in

Geek Culture

10 min readFeb 9, 2023

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The AI wars have hit the next level. Google has announced the release of Bard, their answer to ChatGPT. In their announcement post An important next step on our AI journey, the CEO of Google Sundar Pichai had the following to say-

Soon, you’ll see AI-powered features in Search that distill complex information and multiple perspectives into easy-to-digest formats, so you can quickly understand the big picture and learn more from the web: whether that’s seeking out additional perspectives, like blogs from people who play both piano and guitar, or going deeper on a related topic, like steps to get started as a beginner. These new AI features will begin rolling out on Google Search soon.

Several internet commentators have been commenting on whether this Google’s rollout of this model is too little too late. Now that Microsoft has started to integrate ChatGPT into their systems, can they bring an end to Google’s dominance in the search market? Presently, there is a lot of negative publicity around Bard, with a lot of internet intellectuals predicting that ChatGPT will come out on top because of its seniority. This has been compounded by the recent mistake made by Bard in its presentation-

Apparently, the mistake in their ad caused Google to lose over 100 Billion Dollars in Valuation.

However, looking through the AI research conducted by both parties presents a very different picture. In this article, I will be going over some of the ways that Google’s Bard holds the advantage over ChatGPT. As you will see, these advantages will be hard to overcome. Towards the end, I will also touch upon how you can take advantage of this situation and benefit from this multi-billion dollar AI arms race.

Multimodality

Amongst the biggest advantages that Google has over ChatGPT is the multimodal capability of Google’s AI Systems. Simply put, Bard will be far for than a language model. It will integrate language, images, sound and other senses. To quote their writeup- Introducing Pathways: A next-generation AI architecture- in which they introduced their Pathways training system for Machine Learning Models-

To read more about the Pathways model, check this out

The multi-modal capabilities have a lot of potential. The ability to synthesize information from multiple sources means a deeper and richer final output. It could also be sued to improve the accessibility of their products (can you imagine real-time translation into different languages/sign language). It would also unleash the potential of smartphones, giving us more potential to search by videos and pictures. This is something that we can already sort of see in this video, where Google’s AI is able to describe a picture and even update its views when it goes wrong.

Google already has a massive library of multimodal information to pull from, thanks to the content indexed in their search and on YouTube. ChatGPT is impressive, no doubt. And it can explain concepts very well. But can you imagine asking the potential when you give Bard code and it helps you visualize the different components? Multi-modal capabilities don’t just add to the utility of a system, they make increase them exponentially.

I can’t understand how important this is, especially when we combine it with the next advantage.

Deepmind Robotics

So far, I’ve seen hundreds of people talk about ChatGPT and Bard. I haven’t seen a single person bring this up. Probably because they’re all too busy being distracted by the shiny new thing.

In the last section, I covered the multimodal capabilities that Google has been building into its AI. However, that is not all that Google and its subsidiaries have achieved. Last year, Deepmind released GATO, which demonstrated remarkable fluency in a multitude of tasks.

The same network with the same weights can play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button presses, or other tokens
-Source, A Generalist Agent

This allows Google to monetize Bard and ML in ways that ChatGPT can’t touch. Physical agents have a unique set of constraints and challenges that ChatGPT won’t easily translate to. Given the one-for-all training philosophy that Pathways is built around, there is a good chance that Bard will have some hardware-oriented capabilities. This gives Google a shot at monetizing other revenue streams since they can offer more value-adds than ChatGPT.

Pure Performance

There is another factor that people have been missing, one that could decisively swing things in Google’s Favor. Google’s Models are decisively better. Google has been at the top of the benchmarks for multiple tasks for a while now-

Flamingo is another Google Model, introduced in Tackling multiple tasks with a single visual language model.

In most cases, better performance on benchmarks is pretty meaningless. The extra 2–3% performance is not a huge difference maker. However, there are two reasons that it will be important here -

If it comes to monetization, then having better performance (even if only marginally) is a great marketing tool. If I see Bard doing better than ChatGPT, then I’m not likely to pay for ChatGPT.
On the scale of Google, 2–3% more correct decisions is a large number. This would swing things in Bard’s favor.

There is another element to this. Google has enjoyed a pathbreaking 2021–23. They have made advancements in Protein Modeling, Cancer, Math, and much more. For example, their revolutionary “AlphaFold can accurately predict 3D models of protein structures and is accelerating research in nearly every field of biology” (or so they claim, if you have experience with that let me know).

This extends beyond just traditional Deep Learning. Google’s AI blog has an article called, “AutoML-Zero: Evolving Code that Learns” uses EAs to create ML algorithms. The results were impressive with Evolutionary methods even outperforming Reinforcement Learning. This is quite impressive. Following is a quote from the authors,

“The approach we propose, called AutoML-Zero, starts from empty programs and, using only basic mathematical operations as building blocks, applies evolutionary methods to automatically find the code for complete ML algorithms. Given small image classification problems, our method rediscovered fundamental ML techniques, such as 2-layer neural networks with backpropagation, linear regression and the like, which have been invented by researchers throughout the years. This result demonstrates the plausibility of automatically discovering more novel ML algorithms to address harder problems in the future.”

Compare this to ChatGPT and Open AI. While it is impressive, it hasn’t been path-breaking in the same way. And yes, Microsoft research is as good as Google. But Google has had a lot longer to integrate its various branches into one cohesive system. MS will have to play catchup in this regard. This lends well to the next point.

Integration with Products

Take a second to think about this- how will you monetize ChaGPT? In my post covering Microsoft’s Move on Open AI, I talked about how Microsoft would most likely use ChatGPT first with MS Office. This made sense because this is a pretty low-risk way to get started and they weren’t likely to lose customers if something really broke. This prediction came true.

However, this low-risk approach also has a downside. Since, MS has an effective monopoly on the Office Segment, adding more features isn’t likely to get more people onto their services. Pretty much anyone who would need Teams has it anyway, and most companies don’t really have any alternatives. Thus the additional revenue gained from integrating it isn’t likely to be massive.

The only other option would be to build out new product streams/modify existing products. This is going to be much harder and costlier. Given the resources at MS’s disposal, they will be able to get this done. However, Google has much longer to integrate this into its various products. Thus, it will have a headstart. And the more versatile capabilities of Bard will give it a huge leg over ChatGPT when it comes down to this.

Hopefully, this should bring some balance to the overall discussion around ChatGPT and Bard. Recent events have had a lot of people post about how it’s the end for Google and how they are about to lose its dominance in the marketplace. Despite Bard’s recent Goofup (FYI I’ve been talking about the inherently fragile nature of Deep Learning for over 2 years), they are still in a pole position to continue developing their capabilities and maintain their amazing profits. With that out of the way, how can you benefit from this AI war?

How you can win the war between Google and ChatGPT

This situation is part of what I described as the Big Tech War last year. Big Tech Companies have monopolized their primary markets and are now throwing a lot of money around because now their primary competition is against each other. Therefore, they can’t just roll in and bully their way to the top (the way they have so far).

So how can you benefit from this? In a nutshell- by becoming very good at what you do and learning how to highlight them. Your skills will act as gravity, pulling money towards you. Take my example. I’m a nobody. I come from a non-traditional background (don’t even have a Master’s Degree), don’t have a Big Name FAANG Company on my resume, or a degree from a fancy institution. I don’t even have any real institutional backing (I’m doing everything solo). However, my writing seems to have some attention, to the point where I get various offers through my articles.

If you’d like to work with me, let me know.

However, this is not the only way to the top. Based on your goals and needs, you will have a different path. Broadly speaking, you can perform 3 different kinds of roles to come out on top. I call these personas. Each has its own pros and cons-

The Employee- This is what most people think when they think of making money in this war. Get a nice high-paying job, and cash in. Nothing wrong with this. However, this will come with a capped earning potential and you will not have as much autonomy. This is also the lowest risk option, with the clearest and most straightforward way forward.
The consultant- Offer your expertise to firms/organizations for very specific problems. This is a step up from the employee when it comes to having more autonomy and flexibility. You’ll also have a higher potential earning here. However, you will typically not have any benefits and it is much riskier than the employer.
The entrepreneur- This is in many ways the Silicon Valley Dream. Create a startup, and run it long enough to either go public or be bought by a bigger company and make millions. This requires a lot of luck, expertise, and networking. The highest risk, but the highest potential upside.

These aren’t hard and fast boundaries, but closer to guidelines. Your life and career will have shades of all these roles. I’m just differentiating between these to make it clear to understand. Once again, my piece on the Big Tech War goes into more detail about what you need to succeed as the first 2 personas. I will be doing a separate post dedicated to succeeding as an entrepreneur soon.

The Big Tech War has started. Here is how you will win [Finance Fridays]

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