TECHNOLOGY
Google's AI Labyrinth: Sorting Out the Chaos
USAThu May 22 2025
Google has been on a roll with AI, but it's left many scratching their heads. The tech company has unleashed a bunch of new AI tools, each with its own name and features. This has led to a confusing mix of products that often do similar things. The newest additions include Deep Think, Deep Search, and Google AI Pro. There's also Gemini in Chrome, AI Mode in search, and Google Beam, which used to be called Project Starline. And that's not all—there's Gems, Jules, Astra, and Aura. It's a tangled web of names and overlapping features, making it hard for anyone to keep track.
To understand this mess, it helps to look back. Google's AI chatbot was first called Bard. This was during the Great Chatbot Rush of 2023, when OpenAI launched ChatGPT and Google felt the need to catch up. Bard was quickly replaced by Gemini, which took over Duet. This was a good move, but the naming confusion seems to be back. This week's Google I/O event showed the problem clearly. There's Gemini 2. 5 Pro Deep Think for complex math and coding, a product of DeepMind. Then there's Deep Search, part of the new AI Mode in Google Search. And don't forget Search Live, which lets you point your camera at something and ask questions. But don't mix it up with Gemini Live, which does the same thing. It's enough to make anyone's head spin.
The confusion doesn't end there. There's Veo for creating images, Flow for editing videos with AI, and Flow TV for watching AI-made videos. Then there are Vertex, Lyria, and Imagen, which sound more like names for babies than AI tools. The different versions of Gemini add to the mix, including a multimodal AI assistant. But don't get it mixed up with Project Astra, another multimodal AI assistant that's not out yet. And what about Project Mariner, the feature that lets you click around a website? It's a lot to take in, and it's easy to see why people are getting lost.
Google is under pressure from competitors like OpenAI and Meta, as well as its investors, to roll out AI features fast. This quick development leaves little time for good naming strategies. The result is a confusing array of products that often do similar things. But this isn't new for Google. Different teams working on similar technologies without talking to each other can lead to a bunch of similar products with slightly different names and features. It's like having too many cooks in the kitchen, each trying to outdo the others.
So, what's the fix? Google needs to simplify. It's time to streamline the product line and make it easier for users to understand what's what. The current chaos is a recipe for confusion and frustration. It's a tough job, but it's necessary if Google wants to stay on top in the AI world. The company has the brains and the resources to sort out this mess. It's time to use them to bring some clarity to the AI labyrinth.
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questions
What are the potential long-term effects of Google's confusing AI product naming conventions on market competitiveness?
How might Google's internal communication and collaboration practices be improved to avoid such naming confusion in the future?
Why does Google continue to release AI products with such confusing and similar names?
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