AI News
Building Reflective Prompt Optimization with GEPA: Multi-Component Prompts, Structured Feedback, and Held-Out Validation
def make_problems(n, seed=0): rng = random.Random(seed) out = for _ in range(n): t = rng.choice() if t == "discount": unit...
Best 21 Low-Code and No-Code AI Tools in 2026
Low-code and no-code platforms have moved from simple drag-and-drop builders to AI-native development environments. In 2026, most of them ship...
Hideo Kojima Did AI Video For Prada?! #ai #ainews #aivideo
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Google’s New Colab CLI Lets Developers and AI Agents Run Python on Remote Colab GPUs and TPUs From the Terminal
This week, Google AI team released the Colab CLI. The tool connects your local terminal to remote Colab runtimes. It...
Moonshot AI Releases Kimi Code CLI: A Terminal AI Coding Agent Built in TypeScript for Next-Gen Agents
Moonshot AI has released Kimi Code CLI, an open-source coding agent that runs in the terminal. The tool reads and...
A Hands-On Coding Tutorial on Qualcomm AI Hub Models for Classification, Object Detection, and Hardware-Aware Deployment
In this tutorial, we work through an end-to-end workflow for Qualcomm AI Hub Models. We start by setting up the...
NVIDIA AI Releases Dynamo Snapshot: A CRIU-Based Fast Startup System for AI Inference on Kubernetes
In production inference deployments, demand fluctuates over time, requiring inference replicas to scale elastically. Cold-starting inference workloads on Kubernetes can...
Building a Semantic Search Engine and Open-Status Classifier over the ResearchMath-14k Dataset
from sentence_transformers import util def search(query, k=5): q = model.encode(, normalize_embeddings=True) sims = util.cos_sim(q, emb).cpu().numpy() idx = sims.argsort() print(f'\n=== Query:...
Miso Labs Releases MisoTTS: An 8B Emotive Text-to-Speech Model with Open Weights
Miso Labs has released MisoTTS, an open-weights 8-billion-parameter text-to-speech model. It generates expressive speech from both text and audio context....
How to Build a Document Intelligence Backend with iii Using Workers, Functions, and Cron Triggers
def normalize(data): return {"text": (data.get("text") or "").strip().lower()} def tokenize(data): text = data.get("text", "") cleaned = "".join(c if (c.isalnum() or c.isspace())...
Nous Research Releases Hermes Desktop: A Native Cross-Platform Front End for Hermes Agent v0.15.2 with Streaming Tool Output
Nous Research has released Hermes Desktop in public preview. It is a native application for macOS, Windows, and Linux. It...
How to Fine-Tune LFM2 Using QLoRA and DPO: A Complete Step-by-Step Coding Tutorial on Google Colab
In this tutorial, we fine-tune Liquid AI’s LFM2 model through a complete open-source workflow. We start by loading the base...
Alibaba’s Qwen Team Launches Qwen3.7-Plus, Adding Vision, Deep Reasoning, Tool Invocation, and Autonomous Iteration on the Bailian Platform
Alibaba’s Qwen team has released Qwen3.7-Plus. The model is now available through Alibaba Cloud’s Bailian platform. Bailian is the console...
MiniMax Releases MiniMax M3 with MSA Architecture Supporting 1M-Token Context, Native Multimodality, and Agentic Coding
MiniMax officially released MiniMax M3 on June 1, 2026. The model introduces MSA (MiniMax Sparse Attention), a new sparse attention...
Parallax: A Parameterized Local Linear Attention That Keeps Softmax and Adds a Learned Covariance Correction Branch
The Transformer’s attention mechanism has barely changed since 2017. Most efficiency work has tried to replace softmax attention outright. A...
