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The 1 Billion Token Challenge: Finding the Perfect Pre-training Mix

Researchers squeezed GPT-2-class performance out of a model trained on just1 billion tokens- 10× less data - by dialing in a sharp dataset mix:50% finePDFs, 30% DCLM-baseline, 20% FineWeb-Edu. Static mixing beat curriculum strategies. No catastrophic forgetting. No overfitting. And it hit90%+of GPT-.. read more  

The 1 Billion Token Challenge: Finding the Perfect Pre-training Mix
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Jensen Huang's Stark Warning: China's 1 Million AI Workers vs America's 20,000

Nvidia CEO Jensen Huang, in some leaked comments, didn’t mince words: U.S. export bans aren’t hobbling China’s AI game - they’re fueling it. He pointed to Huawei’s 910C chip edging close to H100 territory, a forecast putting China ahead in AI compute by 2027, and a fast-growing local chip industry n.. read more  

Jensen Huang's Stark Warning: China's 1 Million AI Workers vs America's 20,000
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Context Management in Amp

Amp stretches the context window into something more useful. It pulls in system prompts, tool info, runtime metadata, even AGENTS.md files - fuel for agentic behavior. It gives devs serious control: edit messages, fork threads, drop in files with @mentions, hand off conversations, or link threads to.. read more  

Context Management in Amp
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Google to release Nano Banana Pro next week

Google dropsGemini 3and the newNano Banana Pronext week. Big swing at image generation - now tied tight to Gemini 3 Pro. Early glimpses in Google Vids hint Nano Banana Pro is built for sharper visuals in creative tools. System shift:Google’s stacking its apps behind a single backbone: Gemini 3 Pro. .. read more  

Google to release Nano Banana Pro next week
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Inside Cursor - Sixty days with the AI coding decacorn

Cursor is shaking up recruiting by treating the hiring process as more about the person than the job, resulting in a fast-growing team of exceptional individuals drawn in by the company's compelling mission and focus on challenging technical problems. Women in product and engineering roles are a kno.. read more  

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The Fatal Math Error Killing Every AI Architecture - Including The New Ones

LLMs are fading as JEPA (Joint Embedding Predictive Architecture) emerges with joint, embedding, predictive architecture. JEPA is a step towards true intelligence by avoiding the flat, finite spreadsheet trap of Euclidean space and opting for a toroidal model... read more  

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Introducing structured output for Custom Model Import in Amazon Bedrock

Amazon Bedrock’s Custom Model Import just got structured output support. Now LLMs can lock their responses to your JSON schema - no prompt hacks, no cleanup after... read more  

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LaTeX, LLMs and Boring Technology 

LLMs are tearing down LaTeX's old walls. Syntax hell, cryptic errors, clunky formatting - easier now. Whether baked into editors or running solo, these models smooth the pain. Why does it work so well? LaTeX has history. Mountains of examples. It's the perfect training set. That puts newer contender.. read more  

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Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac

NVIDIA just droppedIsaac for Healthcare v0.4, and it’s a big one. Headliner: the newSO-ARM starter workflow- a full-stack sim2real pipeline built for surgical robotics. It covers the whole loop: spin up synthetic and real-world data capture, train withGR00t N1.5, and deploy straight to 6-DOF hardwar.. read more  

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Visibility at Scale: How Detects Sensitive Data Exposure

Segment gutted its old permissions table—bloated, slow, tangled in logic - and replaced it with a lean, service-based setup. The new stack runs onPostgres,Redis, and a sharply tunedGo API, cutting query times from 1400ms to under 100ms. Clean, fast, and centralized... read more  

Visibility at Scale: How Detects Sensitive Data Exposure
The use of artificial intelligence (AI) in e-commerce has resulted in significant enhancements to various aspects of the customer experience, including personalization, operations, and sales.

Natural language generation (NLG) tools, powered by machine learning algorithms, have emerged as one of the key ways in which AI has facilitated these improvements. These tools can autonomously create human-like written content, such as product descriptions and website copy, thereby reducing the workload of content creators. By integrating AI with Magento 2, online retailers can reap a multitude of benefits.

MageComp’s Magento 2 ChatGPT AI PRO extension automatically generates content for your Magento 2 store. The AI-powered Magento 2 extension seamlessly streamlines your website content operations. The ChatGPT AI for Magento 2 module automatically generates multiple types of website content like product description, metadata, image ALT text and other CMS page descriptions.

The admin is allowed to choose the length of the metadata and image ALT text content and the Magento 2 plugin will generate the content according to that. The plugin also lets the admin set custom prompts for AI-powered description generation. With the Magento 2 ChatGPT AI PRO module, Magento admins can save tons of valuable time and invest that time in other strategic activities.

Why Choose MageComp’s Magento 2 ChatGPT AI Pro extension?

Connects your Magento 2 store with Open API key.
Increases your Magento 2 store’s productivity.
Generates AI-powered content with the help of the page builder.
You can easily generate SEO-rich website content in bulk.
The module allows you to choose the content limit you want to generate.
You can add content prompts for exact AI-powered results.
Generates metadata like page titles, meta keywords and meta descriptions.
Speed up your content development process.
Improves your search engine rankings with SEO-rich keywords.
Boosts your business by creating SEO-rich content for it.

For More Magento 2 Extension Visit Magecomp.Com