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Know what moved AI today—before your coffee cools.

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Top AI News today

Welcome EmbeddingGemma, Google's new efficient embedding model

huggingface.co • 19h ago

TL;DR

Google releases EmbeddingGemma, a state-of-the-art multilingual embedding model for on-device use cases, achieving top performance on the Massive Text Embedding Benchmark.

Key Takeaways:

EmbeddingGemma is a 308M-parameter model, trained on a 320 billion tokens dataset, and supports over 100 languages.
The model achieves top performance on the Massive Text Embedding Benchmark, while keeping a small memory footprint under 200MB of RAM.
EmbeddingGemma can be integrated with popular frameworks like Sentence Transformers, LangChain, LlamaIndex, and Haystack for efficient computation and inference.

Warp brings new diff-tracking tools to the AI coding arms race

techcrunch.com • Yesterday

The AI coding tool Warp is releasing a new set of features designed to give users more oversight over command-line coding agents, with more extensive ...

TL;DR

Warp introduces Warp Code, a new set of features that provide users with more oversight and control over AI coding agents through pair programming-like interface.

Key Takeaways:

Warp Code enables users to see every little diff made by the agent, comment on them, and adjust the agent as it goes along.
The new feature set aims to create a tighter feedback loop for agentic-style coding, ensuring users understand the code produced and can edit it and review it.
Warp has 600,000 active users and is growing rapidly, with $1 million in ARR added every 10 days.

Atlassian Aims For AI Browser For Knowledge Workers With $610M Acquisition Of Startup Behind Dia

news.crunchbase.com • 1h ago

Australia-based collaborative software giant Atlassian announced on Thursday that it has agreed to acquire The Browser Co. for about $610 million in c...

TL;DR

Atlassian acquires The Browser Co. for $610M to create an AI-powered browser designed for knowledge workers.

Key Takeaways:

Atlassian's acquisition is aimed at creating a browser designed for knowledge workers in the AI era, not a general-purpose browser.
The acquisition price of $610M is part of a growing trend of significant funding for startups, with 2025's first half seeing $100B in disclosed-price startup purchases.
Atlassian plans to pack the AI-powered browser with skills and a user's personal work memory, enabling connections between apps, tabs, and tasks.

Microsoft is about to shake up its Copilot pricing for businesses

www.theverge.com • 3h ago

It's no secret that Microsoft has been struggling to sell its Copilot AI assistant to businesses. The steep pricing has put many businesses off paying...

TL;DR

Microsoft plans to simplify its Copilot subscriptions by bundling its Sales, Service, and Finance Copilots into the main Microsoft 365 Copilot subscription, reducing the price to $30 per user per month.

Key Takeaways:

The bundling move aims to simplify Microsoft's Copilot subscriptions for businesses and make it easier for sales teams to convince customers to buy a single Microsoft 365 Copilot license.
Microsoft is also shifting its focus to three areas of monetizing Copilot: Microsoft 365 Copilot, Copilot Studio, and Dynamics 365.
The company plans to introduce Agent 365, a set of tools to manage AI agents and ensure security and compliance requirements of businesses are met, at its upcoming Ignite conference.

Speeding up PyTorch inference by 87% on Apple with AI-generated Metal kernels

gimletlabs.ai • Yesterday

Article URL: https://gimletlabs.ai/blog/ai-generated-metal-kernels Comments URL: https://news.ycombinator.com/item?id=45118111 Points: 20 # Comments: ...

TL;DR

AI-generated Metal kernels can speed up PyTorch inference by 87% on Apple devices without requiring expertise in kernel engineering.

Key Takeaways:

The use of AI-generated Metal kernels led to an average speedup of 1.87x across 215 PyTorch modules, with some workloads running hundreds of times faster than baseline.
An agentic swarm approach, which combines the output of multiple AI models with dynamic context and profiling, achieved the best results, outperforming even the top individual model, GPT-5.
This technique enables automating kernel optimization for any target platform without requiring user code changes, new frameworks, or porting, which has significant implications for both training and inference workloads.

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