Table of Contents Agentic AI Vision System: Object Segmentation with SAM 3 and Qwen Why Agentic AI Outperforms Traditional Vision Pipelines Why Agentic AI Improves Computer Vision and Segmentation Tasks What We Will Build: An Agentic AI Vision and Segmentation… The post Agentic AI Vision System: Object Segmentation with SAM 3 and Qwen appeared first on PyImageSearch.

Early in my career at SpaceX, I was the only person dedicated to training the mission control team for Dragon. For three years, I built the training for the operations team. The documentation came second, always the thing I’d get to later, always the thing that felt like overhead against the actual work of getting the mission ready.

U.S. and Canadian companies secured a staggering $252.6 billion in seed- through growth-stage funding rounds in the first quarter of 2026 per Crunchbase data. That’s more than 3x the total raised in the prior quarter, and the largest quarterly total of all time.

A pilot program to support independent safety and alignment research and develop the next generation of talent

PLUS: How to take AI notes on phone calls

AI is consuming staggering amounts of energy—already over 10% of U.S. electricity—and the demand is only accelerating. Now, researchers have unveiled a radically more efficient approach that could slash AI energy use by up to 100× while actually improving accuracy. By combining neural networks with human-like symbolic reasoning, their system helps robots think more logically instead of relying on brute-force trial and error.

In this article, we discuss the DeepSeek-OCR 2 paper. We start from the DeepEncoder V2, the architecture, and finally discuss the code from Hugging Face. The post Understanding DeepSeek-OCR 2 appeared first on DebuggerCafe.

Most discussions of continual learning in AI focus on one thing: updating model weights. But for AI agents, learning can happen at three distinct layers: the model, the harness, and the context. Understanding the difference changes how you think about building systems that improve over time. The three main layers

How coding agents use tools, memory, and repo context to make LLMs work better in practice

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Data privacy labels are a great idea for mobile apps, but the current versions just aren't good enough.

Startup investors kept up the busy dealmaking pace this week with a number of big rounds. Top among them was a $1.75 billion Series D for Austin-based Saronic, developer of autonomous vessels.

Even organizations with users unwilling or unable to adopt iOS 26 can now protect themselves from a severe mobile OS-cracking tool.

As organizations disclose breaches tied to TeamPCP's supply chain attacks, ShinyHunters and Lapsus$ are getting involved, taking credit, and creating a murky situation for enterprises.

The tech giant's latest investment in regional AI infrastructure development in Asia comes soon after new investments in Thailand and Singapore.

"Skull vibration harmonics generated by vital signs" can be used to sign in to VR, AR, and MR headsets, according to emerging research.

Impressive, but is AI introducing feature bloat? Plus: YouTube's CEO on hard product trade-offs, Google's David East demos how to use Stitch, a new design tool raises $44m to take on Figma

Or, why the software supply chain should be treated as critical infrastructure with guardrails built in at every layer.

The rebuilt Chainguard platform adds deeper security designed to continuously reconcile open source artifacts across containers, libraries, agent skills, and GitHub Actions.

The new offering is designed for advanced reasoning and multimodal capabilities.