211–220 of 582 posts
Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.
Never count out the possibility of a dark horse competitor ripping the sod right out from under
Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.
100% agree. I had Gemini flash 2 chew through thousands of points of nasty unstructured client data and it did a 'better than human intern' level conversion into clean structured output for about $30 of API usage. I am sold. 2.5 pro experimental is a different league though for coding. I'm leveraging it for massive refactoring now and it is almost magical.
What I always wonder in these kinds of cases is: What makes you confident the AI actually did a good job since presumably you haven't looked at the thousands of client data yourself?
For all you know it made up 50% of the result.
More great innovation from Google. OpenAI have two major problems. The first is Google's vertically integrated chip pipeline and deep supply chain and operational knowledge when it comes to creating AI chips and putting them into production. They have a massive cost advantage at every step. This translates into more free services, cheaper paid services, more capabilities due to more affordable compute, and far more g…
Except that they train their model even when you pay. So yeah.. I'd rather not use their "evil"
Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.
I remember everyone saying its a two horse race between Google and OpenAI, then DeepSeek happened. Never count out the possibility of a dark horse competitor ripping the sod right out from under
Earlier quoted context omitted.
They should just get AI to mark them. I genuinely think this is one thing AI would do better than humans.
Grading papers definitely requires intelligence.
There is some level of analysis and feedback than an LLM could provide before a human reviews it. Even if it's just a fancy spelling checker.
Of course it's about 4x as expensive too (I believe), but still, given the release of openai/codex as well, o4-mini will remain a strong competitor for now.
More great innovation from Google. OpenAI have two major problems. The first is Google's vertically integrated chip pipeline and deep supply chain and operational knowledge when it comes to creating AI chips and putting them into production. They have a massive cost advantage at every step. This translates into more free services, cheaper paid services, more capabilities due to more affordable compute, and far more g…
Another advantage that Google has is the deep integration of Gemini into Google Office products and Gmail. I was part of a pilot group and got to use a pre-release version and it's really powerful and not something that will be easy for OpenAI to match.
Gemini flash models have the least hype, but in my experience in production have the best bang for the buck and multimodal tooling. Google is silently winning the AI race.
>”Google is silently winning the AI race.” It’s not surprising. What was surprising honestly was how they were caught off guard by OpenAI. It feels like in 2022 just about all the big players had a GPT-3 level system in the works internally, but SamA and co. knew they had a winning hand at the time, and just showed their cards first.
Earlier quoted context omitted.
After comparing Gemini Pro and Claude Sonnet 3.7 coding answers side by side a few times, I decided to cancel my Anthropic subscription and just stick to Gemini.
Google has killed so many amazing businesses -- entire industries, even, by giving people something expensive for free until the competition dies, and then they enshittify hard. It's cool to have access to it, but please be careful not to mistake corporate loss leaders for authentic products.
To this day, the Google Home (or is it called Nest now?) speaker is the only physical product i've ever owned where it lost features over time. I used to be able to play the audio of a Youtube video (like a podcast) through it, but then Google decided that it was very very important that I only be able to play a Youtube video through a device with a screen, because it is imperative that I see a still image when I play a longform history podcast.
Obviously, this is a silly and highly specific example, but it is emblematic of how they neglect or enshittify massive swathes of their products as soon as the executive team loses interest and puts their A team on some shiny new object.
For a non programmer like me google is becoming shockingly good. It is giving working code the first time. I was playing around with it asked it to write code to scrape some data of a website to analyse. I was expecting it to write something that would scrape the data and later I would upload the data to it to analyse. But it actually wrote code that scraped and analysed the data. It was basic categorizing and counti…
I've been continually disappointed. I've been told it's getting exponentially better and we won't be able to keep up with how good they get, but I'm not convinced. I'm using them every single day and I'm never shocked or awed by its competence, but instead continually vexxed that isn't not living up to the hype I keep reading. Case in point: there was a post here recently about implementing a JS algorithm that highli…