One Model, Three Modalities: ByteDance Releases Lance for Image and Video Understanding, Generation, and Editing
Building a single model that can both understand and generate images and videos is harder than it sounds. The two...
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Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm
Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32...
NVIDIA AI Releases Nemotron-Labs-Diffusion: A Tri-Mode Language Model with 6× Tokens Per Forward Over Qwen3-8B
NVIDIA researchers have released Nemotron-Labs-Diffusion, a language model family that unifies three decoding modes in one architecture. The model supports...
All The News Today On NVIDIA Stock, AI Demand – NVDA Update
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Upstash for Redis vs Supabase vs Neon: Which One Fits Vibe Coding Workflows in 2026?
The short answer most comparison articles skip: these three tools are not competing for the same job. Before picking one,...
Best Enterprise Level Agentic AI Platforms for 2026
In 2026, enterprise agentic AI has moved from pilot budgets to production commitments. Salesforce is closing Agentforce deals at 29,000...
Meet MemPrivacy: An Edge-Cloud Framework that Uses Local Reversible Pseudonymization to Protect User Data Without Breaking Memory Utility
As LLM-powered agents move from research to production, one design tension is becoming harder to ignore: the more useful cloud-hosted...
NVIDIA Introduces a 4-Bit Pretraining Methodology Using NVFP4, Validated on a 12B Hybrid Mamba-Transformer at 10T Token Horizon
Pretraining frontier-scale LLMs in FP8 is now standard practice, but moving to 4-bit floating point has remained an open research...
A Coding Implementation to Compress and Benchmark Instruction-Tuned LLMs with FP8, GPTQ, and SmoothQuant Quantization using llmcompressor
import subprocess, sys def pip(*pkgs): subprocess.check_call() pip("llmcompressor", "compressed-tensors", "transformers>=4.45", "accelerate", "datasets") import os, gc, time, json, math from pathlib import...
Vercel Labs Introduces Zero, a Systems Programming Language Designed So AI Agents Can Read, Repair, and Ship Native Programs
Vercel Labs 01 / 09 · Overview ZeroThe Programming Languagefor Agents An experimental systems language that gives AI agents structured...
Nous Research Proposes Lighthouse Attention: A Training-Only Selection-Based Hierarchical Attention That Delivers 1.4–1.7× Pretraining Speedup at Long Context
Training large language models on long sequences has a well-known problem: attention is expensive. The scaled dot-product attention (SDPA) at...
NVIDIA Introduces SANA-WM: A 2.6B-Parameter Open-Source World Model That Generates Minute-Scale 720p Video on a Single GPU
World models (systems that synthesize realistic video sequences from an initial image and a set of actions) are becoming central...
NHƯ VẬY MÀ NÓI AI NỬA THÌ? #tintuc #tinmoi #news #colatv #tinhbao
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How to Build an MCP Style Routed AI Agent System with Dynamic Tool Exposure Planning, Execution, and Context Injection
class RoutedAgent: def __init__(self, server: MCPToolServer, router: HybridMCPRouter, model: str): self.server = server self.router = router self.model = model def...
Best AI Agents for Software Development Ranked: A Benchmark-Driven Look at the Current Field
The AI coding agent market looks almost unrecognizable compared to 2024 or even early 2025. What started as inline autocomplete...
A Coding Implementation to Master GPU Computing with CuPy, Custom CUDA Kernels, Streams, Sparse Matrices, and Profiling
header("6. RAW CUDA KERNEL — MANDELBROT") mandel = cp.RawKernel(r''' extern "C" __global__ void mandel(float xmin, float xmax, float ymin, float...
Nous Research Releases Token Superposition Training to Speed Up LLM Pre-Training by Up to 2.5x Across 270M to 10B Parameter Models
Pre-training large language models is expensive enough that even modest efficiency improvements can translate into meaningful cost and time savings....
