Sunday, January 18

Reddit

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A new AI assistant with Gemini
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A new AI assistant with Gemini

I got the bug to try and develop an assistant and Google Gemini APIs are pretty cost effective. I started with an idea based on Geminis remote system calls that allow it to make a request locally to call a function or service. I started with an intent and tool calling agent. The intent agent is given a cached context of current tools and how to use them. this way as more tools and functions becom available, the model doesn't need to be retrained. each tool is a function within python. when a user asks about the weather for example, the intent agent simply calls the weather tool. I programmed it so most tools when called simply make API calls to separate agents. Having agents run separately greatly improves development and improvement on the fly. the most important and hardest part was the ...
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“I kind of think of ads as like a last resort for us as a business model” – Sam Altman , October 2024

Announced initially only for the go and free tiers. Will follow into the higher tier subs pretty soon knowing Sam Altman. Cancelling my plus sub and switching over completely to Perplexity and Claude now. Atleast they're ad free. (No thank you, I don't want product recommendations in my answers when I make important health emergency related questions.) submitted by /u/NoSquirrel4840 [link] [comments]
Modern Android phones are powerful enough to run 16x AI Upscaling locally, yet most apps force you to the cloud. So I built an offline, GPU-accelerated alternative.
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Modern Android phones are powerful enough to run 16x AI Upscaling locally, yet most apps force you to the cloud. So I built an offline, GPU-accelerated alternative.

Hi everyone, I wanted to share a project I have been working on to bring high-quality super-resolution models directly to Android devices without relying on cloud processing. I have developed RendrFlow, a complete AI image utility belt designed to perform heavy processing entirely on-device. The Tech Stack (Under the Hood): Instead of relying on an internet connection, the app runs the inference locally. I have implemented a few specific features to manage the load: - Hardware Acceleration: You can toggle between CPU, GPU, and a specific "GPU Burst" mode to maximize throughput for heavier models. - The Models: It supports 2x, 4x, and even 16x Super-Resolution upscaling using High and Ultra quality models. - Privacy: Because there is no backend server, it works in Airplane mode. Your photos...
Google went from being
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Google went from being “disrupted” by ChatGPT, to having the best LLM as well as rivalling Nvidia in hardware (TPUs). The narrative has changed

The public narrative around Google has changed significantly over the past 1 year. (I say public, because people who were closely following google probably saw this coming). Since Google's revenue primarily comes from ads, LLMs eating up that market share questioned their future revenue potential. Then there was this whole saga of selling the Chrome browser. But they made a great comeback with the Gemini 3 and also TPUs being used for training it. Now the narrative is that Google is the best position company in the AI era. submitted by /u/No_Turnip_1023 [link] [comments]
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