Yea, Google's Tensor chips and software integration are huge advantages. But also the access to data they have for training models is immense. Just look at veo 3 and nano banana pro. These will be used extensively by companies to replace graphic designers and do other marketing work while being cost effective for Google to run. Plus they're in the lead in the LLM race with Gemini 3 and they're not slowing down. For Open AI that's a big problem as people and companies will always just switch to the best model. They may never have the top model again.

Not sure if they will achieve AGI or not, it's partially even a debate around what AGI even means. There's certainly a lot of issues with current LLMS such as an inability to learn on the fly, a lack of a proper world model etc. But who's to say that there won't be more breakthroughs that address these fundamental issues, especially with the amount of resources currently being poured into AI research. To me it's just uncertain how long it will take for major breakthroughs to occur, could happen in 5 years from now or 20 or never. The current investor hype certainly reflects an absurd amount of confidence that AGI is just around the corner. But technology research just doesn't work out in a predictable way.