How to Use Plannex AI: Step-by-Step Guide for the Plannex Excel Tool
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Google DeepMind Releases Lyria 3: An Advanced Music Generation AI Model that Turns Photos and Text into Custom Tracks with Included Lyrics and Vocals
Google DeepMind is pushing the boundaries of generative AI again. This time, the focus is not on text or images....
Google Introduces Jetpack Compose Glimmer: A New Spatial UI Framework Designed Specifically for the Next Generation of AI Glasses
Google is moving beyond the rectangular screen. For over 10 years, Google designers have explored how to build interfaces for...
Anthropic Releases Claude 4.6 Sonnet with 1 Million Token Context to Solve Complex Coding and Search for Developers
Anthropic is officially entering its ‘Thinking’ era. Today, the company announced Claude 4.6 Sonnet, a model designed to transform how...
Agoda Open Sources APIAgent to Convert Any REST pr GraphQL API into an MCP Server with Zero Code
Building AI agents is the new gold rush. But every developer knows the biggest bottleneck: getting the AI to actually...
Alibaba Qwen Team Releases Qwen3.5-397B MoE Model with 17B Active Parameters and 1M Token Context for AI agents
Alibaba Cloud just updated the open-source landscape. Today, the Qwen team released Qwen3.5, the newest generation of their large language...
Like a boss #AI #braun
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Moonshot AI Launches Kimi Claw: Native OpenClaw on Kimi.com with 5,000 Community Skills and 40GB Cloud Storage Now
Moonshot AI has officially brought the power of OpenClaw framework directly to the browser. The newly rebranded Kimi Claw is...
Meet ‘Kani-TTS-2’: A 400M Param Open Source Text-to-Speech Model that Runs in 3GB VRAM with Voice Cloning Support
The landscape of generative audio is shifting toward efficiency. A new open-source contender, Kani-TTS-2, has been released by the team...
How to Build a Self-Organizing Agent Memory System for Long-Term AI Reasoning
In this tutorial, we build a self-organizing memory system for an agent that goes beyond storing raw conversation history and...
Exa AI Introduces Exa Instant: A Sub-200ms Neural Search Engine Designed to Eliminate Bottlenecks for Real-Time Agentic Workflows
In the world of Large Language Models (LLMs), speed is the only feature that matters once accuracy is solved. For...
![[In-Depth Guide] The Complete CTGAN + SDV Pipeline for High-Fidelity Synthetic Data](https://gocryptoventure.com/wp-content/uploads/2026/02/In-Depth-Guide-The-Complete-CTGAN-SDV-Pipeline-for-High-Fidelity-540x340.png)
[In-Depth Guide] The Complete CTGAN + SDV Pipeline for High-Fidelity Synthetic Data
metadata_dict = metadata.to_dict() diagnostic = DiagnosticReport() diagnostic.generate(real_data=real, synthetic_data=synthetic_sdv, metadata=metadata_dict, verbose=True) print("Diagnostic score:", diagnostic.get_score()) quality = QualityReport() quality.generate(real_data=real, synthetic_data=synthetic_sdv, metadata=metadata_dict, verbose=True)...
Google DeepMind Introduces Aletheia: The AI Agent Moving from Math Competitions to Fully Autonomous Professional Research Discoveries
Google DeepMind team has introduced Aletheia, a specialized AI agent designed to bridge the gap between competition-level math and professional...
The Energy Crisis Behind the AI Boom #ai #energy #news
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Google AI Introduces Natively Adaptive Interfaces (NAI): An Agentic Multimodal Accessibility Framework Built on Gemini for Adaptive UI Design
Google Research is proposing a new way to build accessible software with Natively Adaptive Interfaces (NAI), an agentic framework where...
How to Build a Matryoshka-Optimized Sentence Embedding Model for Ultra-Fast Retrieval with 64-Dimension Truncation
In this tutorial, we fine-tune a Sentence-Transformers embedding model using Matryoshka Representation Learning so that the earliest dimensions of the...
How to Build an Atomic-Agents RAG Pipeline with Typed Schemas, Dynamic Context Injection, and Agent Chaining
In this tutorial, we build an advanced, end-to-end learning pipeline around Atomic-Agents by wiring together typed agent interfaces, structured prompting,...
NVIDIA Researchers Introduce KVTC Transform Coding Pipeline to Compress Key-Value Caches by 20x for Efficient LLM Serving
Serving Large Language Models (LLMs) at scale is a massive engineering challenge because of Key-Value (KV) cache management. As models...
