📰 Hackernoon

FLUX is great at photos and bad at illustration because the pretraining mix fights you. This article catalogs five reproducible failure modes when training illu

This article documents a multimodal AI study pipeline built on NVIDIA Nemotron Omni and vLLM that converts textbooks, lecture videos, handwritten notes, and stu

OceanPile is a large-scale dataset combining multiple types of ocean data—images, text, videos, and other information—designed to train AI foundation models

In the span of a single weekend, thousands of developers, writers, researchers, and power users woke up to the same grim notification: Anthropic had shut down o

From Homebrew Computer Club to GNU & Linux, we study OpenClaw in the context of open source community-driven technology revolution.

AI-powered applications don't crash when they fail — they hallucinate confidently, drift silently, and get exploited in ways traditional QA was never designed t

I audited vLLM's C++ and CUDA code and found 221 places where PyTorch's 64-bit tensor metadata is silently truncated to 32-bit int before being used in GPU buff

Large AI models cost millions, run slow, and explain nothing. TinyBrain++ is a compact alternative: 0.002s latency, 10M+ predictions/day on CPU, with human-read

Researchers improved AI models by “instruction finetuning” them on 1,800+ tasks and adding chain-of-thought reasoning data. The result: Flan-PaLM significantly

Researchers found that giving AI examples that include step-by-step reasoning (“chain-of-thought”) dramatically improves its ability to solve complex problems.

Direct Preference Optimization (DPO) offers a simpler, more stable alternative to traditional RLHF for aligning large language models with human preferences. By

Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-v2-GGUF delivers shorter reasoning chains and 96.91% HumanEval pass@1.

After Anthropic refused Pentagon demands to enable autonomous weapons and mass surveillance, the U.S. government did something unprecedented: it branded an Amer

GLM-4.7-Flash-GGUF offers fast local text generation with multiple quantization options for PCs, edge devices, and small servers.

Multi-agent RL does not mainly have a modeling problem. It has a systems-design problem. Real-world coordination needs explicit task stages, selective communica

The industry is obsessed with agents and prompting. That focus is not wrong—but it is incomplete. Real production systems require architecture, determinism, int

Real-world data often includes significant obstacles, such as privacy concerns, restrictions imposed by regulations, and sheer scarcity. This is where Synthetic

Machine learning isn’t failing because of hype—it’s failing because control is lagging behind capability. As AI moves into real-world systems, the risks come fr

Human-in-the-loop wasn’t built for the scale of agentic AI. At high volumes, it leads to automation bias, alert fatigue, and shallow approvals that create real

AMI Labs has raised over $1 billion to develop “world models,” a new class of AI systems focused on understanding physical reality rather than predicting langua

daVinci-MagiHuman is a 15B unified model that generates synchronized video and speech from text prompts with fast, high-quality results.

Text-only LLMs may already know enough about sound to predict downstream audio model performance before an encoder is ever attached.