Every Ling 2.0 model uses the same sparse Mixture of Experts layer. Each layer has 256 routed experts and one shared expert. The router picks 8 routed experts for every token, the shared expert is ...
How do you convert real agent traces into reinforcement learning RL transitions to improve policy LLMs without changing your existing agent stack? Microsoft AI team releases Agent Lightning to help ...
What is new in Granite 4.0 Nano series? Granite 4.0 Nano consists of four model lines and their base counterparts. Granite 4.0 H 1B uses a hybrid SSM based architecture and is about 1.5B parameters.
Can an open source MoE truly power agentic coding workflows at a fraction of flagship model costs while sustaining long-horizon tool use across MCP, shell, browser, retrieval, and code? MiniMax team ...
Can we render long texts as images and use a VLM to achieve 3–4× token compression, preserving accuracy while scaling a 128K context toward 1M-token workloads? A team of researchers from Zhipu AI ...
AI companies use model specifications to define target behaviors during training and evaluation. Do current specs state the intended behaviors with enough precision, and do frontier models exhibit ...
In this article we will analyze how Google, OpenAI, and Anthropic are productizing ‘agentic’ capabilities across computer-use control, tool/function calling, orchestration, governance, and enterprise ...
Anthropic recently released a guide on effective Context Engineering for AI Agents — a reminder that context is a critical yet limited resource. The... In this tutorial, we explore how to build a ...
Orchestration Host routes across many servers/tools App-local chaining Agent/toolkit routes intents → operations ...
StreamTensor: A PyTorch-to-Accelerator Compiler that Streams LLM Intermediates Across FPGA Dataflows
Why treat LLM inference as batched kernels to DRAM when a dataflow compiler can pipe tiles through on-chip FIFOs and stream converters? StreamTensor is a compiler that lowers PyTorch LLM graphs (GPT-2 ...
TUMIX runs a group of heterogeneous agents—text-only Chain-of-Thought, code-executing, web-searching, and guided variants—in parallel, then iterates a small number of refinement rounds where each ...
Google AI Proposes ReasoningBank: A Strategy-Level AI Agent Memory Framework that Makes LLM Agents Self-Evolve at Test Time ...
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