Google 'Gemma 4' AI model: This new AI tool can build AI agents for you and handle text, image, audio tasks - MSN
Google 'Gemma 4' AI model: This new AI tool can build AI agents for you and handle text, image, audio tasks MSN
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I am curious, now that Claude Code is “open-source” will developers and vibe-coders consider cancelling subscriptions to “coding-agent harnesses” like Windsurf, Cursor, etc, as they essentially achieve the same outcome and quality, or do users of this tech view Claude (the LLM) as irreplaceable?
View Poll submitted by /u/madSaiyanUltra_9789 [link] [comments]
Hypothesis: small models and optimized prompt perform better than larger models
For the agentic coding use case, I'm wondering if there's hope use a small model, but with the "perfect" prompts and tooling and custom workflows (eg claude code recent leaked architecture), could it surpass larger models "off the shelf"? Stretching the concept through history, Are the 30B models today, smarter than the 30B a year ago? would this trend continue so that 15B next year is equivalent as 30B this year? Just trying to categorize if it's just an optima problem and research is valid, or there's a hard wall and there's no way around larger models for more complex problems and tasks. submitted by /u/Radiant_Condition861 [link] [comments]
New to local AI. Best model recommendations for my specs?
Hi everyone, I'm completely new to running AI models locally and would appreciate some guidance. Here are my specs: CPU: AMD Ryzen 9 5950X RAM: 16GB DDR4 GPU: NVIDIA RTX 4060 (8GB VRAM) I know my specs are pretty poor for running local AI, but I wanted to try running some tests to see how it performs. As for software, I've downloaded LM Studio. Thanks. submitted by /u/wunk0 [link] [comments]
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Hypothesis: small models and optimized prompt perform better than larger models
For the agentic coding use case, I'm wondering if there's hope use a small model, but with the "perfect" prompts and tooling and custom workflows (eg claude code recent leaked architecture), could it surpass larger models "off the shelf"? Stretching the concept through history, Are the 30B models today, smarter than the 30B a year ago? would this trend continue so that 15B next year is equivalent as 30B this year? Just trying to categorize if it's just an optima problem and research is valid, or there's a hard wall and there's no way around larger models for more complex problems and tasks. submitted by /u/Radiant_Condition861 [link] [comments]
New to local AI. Best model recommendations for my specs?
Hi everyone, I'm completely new to running AI models locally and would appreciate some guidance. Here are my specs: CPU: AMD Ryzen 9 5950X RAM: 16GB DDR4 GPU: NVIDIA RTX 4060 (8GB VRAM) I know my specs are pretty poor for running local AI, but I wanted to try running some tests to see how it performs. As for software, I've downloaded LM Studio. Thanks. submitted by /u/wunk0 [link] [comments]
30 Days of Building a Small Language Model: Day 2: PyTorch
Today, we have completed Day 2. The topic for today is PyTorch: tensors, operations, and getting data ready for real training code. If you are new to PyTorch, these 10 pieces show up constantly: ✔️ torch.tensor — build a tensor from Python lists or arrays. ✔️ torch.rand / torch.zeros / torch.ones — create tensors of a given shape (random, all zeros, all ones). ✔️ torch.zeros_like / torch.ones_like — same shape as another tensor, without reshaping by hand. ✔️ .to(...) — change dtype (for example float32) or move to CPU/GPU. ✔️ torch.matmul — matrix multiply (core for layers and attention later). ✔️ torch.sum / torch.mean — reduce over the whole tensor or along a dim (batch and sequence axes). ✔️ torch.relu — nonlinearity you will see everywhere in MLPs. ✔️ torch.softmax — turn logits into p
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