Comment by rhubarbtree
10 hours ago
Google are stuck because they have to compete with OpenAI. If they don’t, they face an existential threat to their advertising business.
But then they leave the door open for Anthropic on coding, enterprise and agentic workflows. Sensibly, that’s what they seem to be doing.
That said Gemini is noticeably worse than ChatGPT (it’s quite erratic) and Anthropic’s work on coding / reasoning seems to be filtering back to its chatbot.
So right now it feels like Anthropic is doing great, OpenAI is slowing but has significant mindshare, and Google are in there competing but their game plan seems a bit of a mess.
Google might be a mess now, but they have time. OpenAI and Anthropic are on barrowed time, Google has a built in money printer. They just need to outlast the others.
Plus they started making AI processors 11 years ago and invented the math behind “GPTs” 9 years ago. Gemini is way cheaper to run for them than it does for everyone else.
I think Gemini is really built for their biggest market — Google Search. You ask questions and get answers.
I’m sure they’ll figure out agentic flows. Google is always a mess when it comes to product. Don’t forget the Google chat sagas where it seems as if different parts of the company were making the same product.
They are also a mess in UI now.
In the "Intelligence applied" section, where they show the comparison animations, they are shown using a non-optimal UI.
There is not enough time to read the text, see old animation, and see new animation. Better would have been to keep the same animation on repeat, so that people have unlimited time to read the text and observer the animations.
Also, it jumps from example to example in the same video. Better would have been to show each separately, so that once user is done observing one example at their own pace, they can proceed to the next.
As a workaround, I had to open the video (just the video) in a new tab, pause once an example came up, read the text, then rewind to the start of the animation to see the old animation example, then rewind again, then see the new animation example, and then sometimes rewind again if I wanted to see the animation again. Then, once done with the example, I had to forward to the next example and repeat the above process again.
Somewhere along that process, they lost me.
Who they? Do the engineers who actually did that work at Google still? I heard that the guy who made TPUs has his own startup now.
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Why do you assume they’ll figure it out when they pretty consistently mess things up?
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Google is Google. Too much restrictions on the model output. Ask it to create a pentest or let it request a pub key for ssh access and it will refuse.
They have much much less time than one would think. Their ads business is about to go into freefall, this will cause the whole company to spiral.
I mean their ads business just broke $80b per quarter, not sure where this idea is coming from...
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Yup, you got it. It's a weird situation for sure.
You know what's also weird: Gem3 'Pro' is pretty dumb.
OAI has 'thinking levels' which work pretty well, it's nice to have the 'super duper' button - but also - they have the 'Pro' product which is another model altogether and thinks for 20 min. It's different than 'Research'.
OAI Pro (+ maybe Spark) is the only reason I have OAI sub. Neither Anthropic nor Google seem to want to try to compete.
I feel for the head of Google AI, they're probably pulled in major different directions all the time ...
Can you explain what’s so different about pro?
I’ve used everything frontier model and had Pro a while ago but it seemed to just be the same models served faster at the time.
It's a different model and designed to 'think very hard' about issues. It's basically a 'very extended thinking mixed with research' type of solution.
While the 'research' solutions tend to go very wide and come back with a 'paper' the Pro model seems to do an exhaustive amount of thinking combined with research, and tries to integrate findings. I think it goes down a lot of rabbit holes.
I find it's by far the best way to find solutions to hard problems, but it typically does require a 'hard problem' in order to shine.
And it takes an enormous amount of time. Ito could be essentially a form of 'saturating the problem with tokens'. It's OAI's most expensive model by far. A prompt usually costs me $1-3 if paying per token.
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If you want that level of research I suggest you ask the model to draft a markdown plan with "[ ]" gates for todo items, and plan it in as many steps as needed. Then ask another LLM to review the plan, judge it. In the end use the plan as the execution state tracker, the model solves one by one the checkboxes.
Using this method I could recreate "deep research" mode on a private collection of documents in a few minutes. A markdown file can be like a script or playbook, just use checkboxes for progress. This works for models that have file storage and edit tools, which is most, starting with any coding agent.
OAI Pro is not a 'research' tool in that sense, and it's definitely different than the 'deep research' options avail on most platforms, as I indicated.
It's a different kind of solution altogether.
I suggest trying it.
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In my experience Gemini 3.0 pro is noticeably better than chatgpt 5.2 for non-coding tasks. The latter gives me blatantly wrong information all the time, the former very rarely.
I agree and it has been my almost exclusive go to ever since Gemini 3 Pro came out in November.
In my opinion Google isn't as far behind in coding as comments here would suggest. With Fast, it might already have edited 5 files before Claude Sonnet finished processing your prompt.
There is a lot of potential here, and with Antigravity as well as Gemini CLI - I did not test that one - they are working on capitalizing on it.
Strange that you say that because the general consensus (and my experience) seems to be the opposite, as well as the AA-Omniscience Hallucination Rate Benchmark which puts 3.0 Pro among the higher hallucinating models. 3.1 seems to be a noticeable improvement though.
Google actually has the BEST ratings in the AA-Omniscience Index: AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer.
Gemini 3.1 is the top spot, followed by 3.0 and then opus 4.6 max
I can only speak to my own experience, but for the past couple of months I've been duplicating prompts across both for high value tasks, and that has been my consistent finding.
Google is good for answering questions but its writing is lacking. I’ve had to deal with Gemini slop and it’s worse than ChatGPT
They all suck!!!
Google is scoring one own goal after another by making people working with their own data wonder how much of that data is sent off to be used to train their AI on. Without proof to the contrary I'm going to go with 'everything'.
They should have made all of this opt-in instead of force-feeding it to their audience, which they wrongly believe to be captive.