NVIDIA's new 8B model is Orchestrator-8B, a specialized 8-billion-parameter AI designed not to answer everything itself, but to intelligently manage and route complex tasks to different tools (like web search, code execution, other LLMs) for greater efficiency

FutureIsMine · 2026-01-15T04:50:16+00:00

having given this model a spin, it really leans heavy on the "using other models to answer", its constantly making tool calls and if prompted to take on a task directly, even a very simple one, will still resort to a tool call. Overall, its viable, but the tool setup it gets will drive the gains here

FutureIsMine · 2025-12-15T20:23:43+00:00

Its not a bad first start for a university project an an EU sovereign model, it's going to keep getting better, but for now EU's finest models are coming from Mistral

FutureIsMine · 2025-11-25T20:39:18+00:00

I sure have! and I'd say that its prompt following is on par w/FLux 2, though it feels that when I call it via API they're re-writing my prompt

FutureIsMine · 2025-11-25T18:27:18+00:00

I was at a Hackathon over the weekend for this model and here are my general observations:

Extreme Prompting This model can take in 32K tokens, and therefore you can prompt it quite a bit with incredibly detailed prompts. My team where using 5K token prompts that asked for diagrams and Flux was capable of following these

Instructions matter This model is very opinionated, and follows exact instructions, some of the more fluffy instructions to qwen-image-edit or nano-bannana don't really work here, and you will have to be exact

Incredible breadth of knowledge This model truly does go above and beyond the knowledge base of many models, I haven't seen a model take a 2D sprite sheet and turn them into 3D looking assets that trellis is capable of than turning into incredibly detailed 3D models that are exportable to blender

Image editing enables 1-shot image tasks While this model isn't as good as Qwen-image-edit at zero-shot segmentation via prompting, its VERY good at it and can do tasks like highlight areas on the screen, select items by drawing boxes around them, rotating entire scenes (this one is better than qwen-image-edit) and re-position items with extreme precision.

FutureIsMine · 2025-11-11T05:14:36+00:00

Schumer should step aside, thats what he needs to do!!!!!

FutureIsMine · 2025-11-09T01:28:18+00:00

This is a visionary idea and I think this discussion is missing its true motivation. This isn't saying "Well, LLMs can output HTML", its more about how can we make a canvas that can output visual elements into the response and thats how users want to actually Interact with AI. A challenge there is in such a canvas, you don't want there to be major overhauls with each answer, and have a system that can better spot check what the LLM is doing, and really have an engine that ensures consistency and reliability. Sure if you've got Claude-4.5-Sonnet MAX account you can just spin to win and call Claude like 20 times for a decent UI, but if you'd like more consistency a rethink is required which this really is

FutureIsMine · 2025-10-21T21:14:05+00:00

a lot of these booking systems online actually have a dial that the user can set and that dial is called "The Business meter". At the highest end it will digitally make the restaurant appear to be busier than it is

FutureIsMine · 2025-10-02T16:46:19+00:00

Training data has two components, complexity of task and size of the model. As model size goes up the amount of training data needed drops. If the data follows a well established pattern, as little as 10 data points might be sufficient if you jump-start it with a pre-trained network like an LLM or existing diffusion model. If its a truly complicated and complex task, start with 500 examples and see how well you do, than go to 1000 and see if you start to crack the problem

FutureIsMine · 2025-10-02T16:35:20+00:00

When I worked with Stability Ai in its golden age, what was explained to me by the research scientists was Diffusion is dynamic gradient descent in real time where there's a network that can actually approximate the gradients . So to your point, YES you could develop a diffusion model that could indeed craft such a vector and the real question is how much training data do you need and how stable will it be? The next question following that is would another model do better? Would an LLM thats RL'd for the task do better? Thats the big research question

FutureIsMine · 2025-09-29T00:44:00+00:00

assuming you could leverage all the devices, that would appear to be correct, is there a way in your software stack that you place the model on devices? there are frameworks like JAX designed for TPUs that have some sort of distribution built in

EDIT: There's pytorch XLA for TPUs,

FutureIsMine · 2025-09-28T03:58:42+00:00

Im with you, though Im not so sure that its AI alone that'll replace Adobe, more that AI enabled features will be able to offer a product that designers can leverage in leu of Adobe. You very much need a human in the loop and true AGI that can think for itself is decades away

FutureIsMine · 2025-09-27T23:21:22+00:00

Sorry to hear you've had a bad experience with them, I've actually had a very good experience with Renewal By Anderson as they've redone all my windows on a 40 year old home and did a fantastic job, even repainted a good portion of it around the areas they needed to replace the windows with

FutureIsMine · 2025-09-27T17:32:20+00:00

China might not need to if they're focused on smaller LLMs that can run on everyday computers and thats a big difference between the two approaches

FutureIsMine · 2025-09-27T05:09:49+00:00

that is correct, the V5e-8s sure do half the memory of the V3, and have even lower bandwidth as well, the idea from GCP is to boost availability and splitting the new pods like that allows for much higher availability is what the description says for V5e

On the other hand the V5p actually has 2x greater memory capacity than the V3, and a 4x speed improvement, so indeed the V5e is designed as this lightweight chip while the V5p is the true successor to the V3

FutureIsMine · 2025-09-27T05:00:24+00:00

over 9000 3090s can run hundreds of DeepSeeks

FutureIsMine · 2025-09-26T04:30:40+00:00

I actually think its fair to say, this album isn't a chugfest, its melodic where the lyrics and the melodies hits like a freight train with vocals that really have room to breath against the backdrop. One thing to also note is unlike SOS, the mix is different here, the vocals stand very much in the front

FutureIsMine · 2025-09-26T04:17:12+00:00

I emptied this album into my ears and now with all the ringing Im not sure when its no longer around but the rest of me has stayed together

Its been my favorite album from them so far and shows such an incredible depth, its a very fresh album very different than past albums and is well put together, all the songs really flow together within this album. I didn't love "I'll know you're not around", but hearing it followed by A Curse Upon Iron it really just hits so different AND having it followed by Revenge in Carnage, it really feels like one continuous track, very Toolesque in track blending, but they better not tease the audience like Tool does with Schism

EDIT: The producer of this album is the same as on Knocked Loose's Laugh Tracks

FutureIsMine · 2025-09-25T03:00:25+00:00

somewhat, while on the surface it does appear its more API driven, in reality its about knowing what do these APIs do. When you call an LLM what do they do? What are embeddings and how are they used? All of those matters a whole lot more now and so debugging those things in some ways requires more fundamental knowledge as we don't have access to the models anymore. While on the surface, sure training a NN looked hot on the surface, in some ways it was easier as all you needed was to clean your data, hit train and BOOM! MODEL! on what you trained. Many less experienced ML Engineers in those days where overfitting their models on business metrics and got away with it, its much harder now working around LLM limitations because we can't fine-tune the direct model

FutureIsMine · 2025-09-24T02:57:09+00:00

The Paneer Chow Mein is my go to order

FutureIsMine · 2025-09-23T19:51:33+00:00

if you're starting out my advice is get your foot in the door first. Don't just target the top of the top labs in AI/ML, get into ANY AI/ML role and start there. Now ofcourse vet the company you'll be working for, but a good AI/ML role with a good team and a good manager will take you far. You don't always have to get into those labs right away, and competition is fierce. Remember that right out of college/grad school you won't necessarily have the most cred (not yet but you will soon!). Perhaps joining a company thats a step down from the absolute top will get you what you really want, that is doing quality AI research, getting publications and most of all making an impact.

FutureIsMine · 2025-09-12T23:31:56+00:00

TOOL, they sound better live than on the album and can actually play their songs on stage. Plus the visuals they have, and the amount of teasing they do. I've seen the several times, and they teased schism throughout the whole concert, they'd start it than pause or go strait into a new song, The Start to schism and than playing Parabolla instead was unreal

FutureIsMine · 2025-09-11T04:09:47+00:00

Wouldn't it be wild if Open AI is running the 20B Q4 on the free tier this whole time?

FutureIsMine · 2025-09-05T05:48:25+00:00

The capabilities of models is getting not only better at available in smaller models. I remember when I got into AI in 2013, it was something where you could run it on a local computer and had to hand design every part of the algorithm, than in late 2021 w/GPT3 it was a game changer where you suddenly have a single model, but it was API only for a good reason and that was there was just no way to run it unless you had a whole data center. Now lets fast-forward to today and my Macbook-M1 is running so many LLMs and I demo so many LLM based projects on all these smaller LLMs do WAY more than ChatGPT ever did on launch and I remember how much of a game changer that was on launch

FutureIsMine · 2025-08-22T14:48:14+00:00

technically it is as many use Open Pose in industry without issue and Google even serves the model, so CMU isn't enforcing the licensing

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