Gemini 2.0: our new AI model for the agentic era

Post by simonw » Wed, Dec 11, 2024, 10:00 PM UTC

SimianSci wrote: post #225

maeil wrote: post #72

Earlier quoted context omitted.

> i don’t think they need to win the on device market. The second Apple comes out with strong on-device AI - and it very much looks like they will - Google will have to respond on Android. They can't just sit and pray that e.g. Samsung makes a competitive chip for this purpose.

I think Apple is uniquely disadvantaged in the AI race to a point people dont realize. They have less training data to use, having famously been focused on privacy for its users and thus having no particular advantage in this space due to not having customer data to train on. They have little to no cloud business, and while they operate a couple of services for their users, they do not have the infrastructure scale t…

Post by danpalmer » Wed, Dec 11, 2024, 10:17 PM UTC

OutOfHere wrote: post #73

airstrike wrote: post #19

OT: I’m not entirely sure why, but "agentic" sets my teeth on edge. I don't mind the concept, but the word itself has that hollow, buzzwordy flavor I associate with overblown LinkedIn jargon, particularly as it is not actually in the dictionary...unlike perfectly serviceable entries such as "versatile", "multifaceted" or "autonomous"

To play devil's advocate, the correct use of the word would be when multiple AIs are coordinating and handing off tasks to each other with limited context, such that the handoffs are dynamically decided at runtime by the AI, not by any routine code. I have yet to see a single example where this is required. Most problems can be solved with static workflows and simple rule based code. As such, I do believe that >95% o…

Post by mnky9800n » Wed, Dec 11, 2024, 10:21 PM UTC

pcwelder wrote: post #256

simonw wrote: post #113

I released a new llm-gemini plugin with support for the Gemini 2.0 Flash model, here's how to use that in the terminal: llm install -U llm-gemini llm -m gemini-2.0-flash-exp 'prompt goes here' LLM installation: https://llm.datasette.io/en/stable/setup.html Worth noting that the Gemini models have the ability to write and then execute Python code. I tried that like this: llm -m gemini-2.0-flash-exp -o code_execution 1…

Code execution is okay, but soon runs into the problem of missing packages that it can't install. Practically, sandboxing hasn't been super important for me. Running claude with mcp based shell access has been working fine for me, as long as you instruct it to use venv, temporary directory, etc.

Post by kernal » Wed, Dec 11, 2024, 10:30 PM UTC

fpgaminer wrote: post #216

I work with LLMs and MLLMs all day (as part of my work on JoyCaption, an open source VLM). Specifically, I spend a lot of time interacting with multiple models at the same time, so I get the chance to very frequently compare models head-to-head on real tasks. I'll give Flash 2 a try soon, but I gotta say that Google has been doing a great job catching up with Gemini. Both Gemini 1.5 Pro 002 and Flash 1.5 can trade bl…

Post by danpalmer » Wed, Dec 11, 2024, 10:38 PM UTC

siliconc0w wrote: post #44

What's everyone's favorite LLM leaderboard? Gemini 2 seems to be edging out 4o on chatbot arena( https://lmarena.ai/?leaderboard )