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Meet MemPrivacy: An Edge-Cloud Framework that Uses Local Reversible Pseudonymization to Protect User Data Without Breaking Memory Utility

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As LLM-powered agents move from research to production, one design tension is becoming harder to ignore: the more useful cloud-hosted memory becomes, the more private user data it exposes. Researchers from MemTensor (Shanghai), HONOR Device and Tongji University have introduced MemPrivacy, a framework that attempts to resolve this tension without sacrificing the utility that makes […]

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Vercel Labs Introduces Zero, a Systems Programming Language Designed So AI Agents Can Read, Repair, and Ship Native Programs

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Vercel Labs has released Zero, an experimental systems programming language designed so AI agents can read, repair, and ship native programs without requiring human interpretation of compiler output. The language emits JSON diagnostics with stable codes and typed repair metadata, enforces capability-based I/O at compile time, and compiles to sub-10 KiB native binaries.

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Meet LiteLLM Agent Platform: A Kubernetes-Based, Self-Hosted Infrastructure Layer for Isolated Agent Sandboxes and Persistent Session Management in Production

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Running AI agents in a local script is straightforward. Running them reliably in production across teams, across restarts, with isolated environments per context is a different problem entirely. BerriAI, the company behind the LiteLLM AI Gateway, is now open-sourcing a purpose-built answer to that problem: the LiteLLM Agent Platform. The platform is described as a […]

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NVIDIA Introduces SANA-WM: A 2.6B-Parameter Open-Source World Model That Generates Minute-Scale 720p Video on a Single GPU

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Researchers from NVIDIA introduce SANA-WM, an open-source camera-controlled world model that generates 60-second, 720p videos with precise 6-DoF camera control — trained on 64 H100 GPUs and deployable on a single RTX 5090.

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Best AI Agents for Software Development Ranked: A Benchmark-Driven Look at the Current Field

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The AI coding agent field in 2026 is more capable, more fragmented, and harder to benchmark than it looks. Claude Code leads on code quality at 87.6% SWE-bench Verified. GPT-5.5 tops Terminal-Bench at 82.7%. But the benchmark OpenAI itself declared contaminated in February 2026 is still being used to rank these tools — including by the labs publishing their own scores.

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Supertone Releases Supertonic v3: On-Device Text-to-Speech Model with 31-Language Support, Fewer Reading Failures, and Expression Tags

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The Seoul-based speech AI company ships its third generation of its on-device TTS engine, adding expressive tags, improved reading stability, and a 6× increase in language coverage — all while keeping the inference contract unchanged for existing integrations.

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Poetiq’s Meta-System Automatically Builds a Model-Agnostic Harness That Improved Every LLM Tested on LiveCodeBench Pro Without Fine-Tuning

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Poetiq’s Meta-System automatically constructed and optimized an inference harness for LiveCodeBench Pro using only Gemini 3.1 Pro — no fine-tuning, no model internals. The same harness, applied without modification to GPT 5.5 High, Kimi K2.6, Gemini 3.0 Flash, and four other models, improved every one of them.

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Cline Releases Cline SDK: An Open-Source Agent Runtime Now Powering Its CLI and Kanban, With IDE Extensions Being Migrated

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Cline has extracted its internal agent harness into an open-source TypeScript SDK called @cline/sdk, the same runtime now powering its CLI and Kanban, with VS Code and JetBrains extensions being migrated. The SDK is structured as a four-layer stack — @cline/shared, @cline/llms, @cline/agents, and @cline/core — with native support for plugins, subagents, CRON scheduling, checkpointing, and MCP connectors. On Terminal Benchmark 2.0, Cline CLI scored 74.2% on claude-opus-4.7, compared to Anthropic’s published 69.4% for Claude Code on the same model. Install via npm install @cline/sdk. Requires Node.js 22+.

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Nous Research Releases Token Superposition Training to Speed Up LLM Pre-Training by Up to 2.5x Across 270M to 10B Parameter Models

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Nous Research releases Token Superposition Training (TST), a two-phase pre-training method that cuts wall-clock training time by up to 2.5x at matched FLOPs by averaging contiguous token embeddings into bags during Phase 1 and reverting to standard next-token prediction in Phase 2 — without changing the model architecture, tokenizer, optimizer, or inference-time behavior. Validated at 270M, 600M, 3B dense, and 10B-A1B MoE scales.

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Fastino Labs Open-Sources GLiGuard: A 300M Parameter Safety Moderation Model That Matches or Exceeds Accuracy of Models 23–90x Its Size

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Fastino Labs has released GLiGuard, a 300M parameter open-source safety moderation model that evaluates four safety tasks — prompt safety, jailbreak strategy detection, harm category classification, and refusal detection — in a single forward pass. Built on an encoder architecture rather than the decoder-only design used by most guardrail models, GLiGuard achieves up to 16x higher throughput and 16.6x lower latency than current state-of-the-art models, while matching or exceeding the accuracy of models 23 to 90 times its size across nine safety benchmarks. Model weights are available under the Apache 2.0 license on Hugging Face.

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