★Emu3.5 in Plain English: One Autoregressive Model for Images, Text, and World Simulation★ “ What’s the big deal? Emu3.5 treats images, text, and video frames as one long token stream and learns to predict the next token—nothing else. The result is a single checkpoint that can chat, draw, edit, tell stories, give step-by-step visual tutorials, explore imaginary worlds, and even plan robot actions—without any task-specific heads. Table of Contents Quick Glance Why “Next Token” Works for Pictures Training Diet: 13 Trillion Multimodal Tokens Post-Training Magic: RL That Knows Beauty, OCR, Physics DiDA: Waiting 10 s Instead of 200 s for …
A Frustrating Scenario for Users Imagine spending 20 minutes planning a Tokyo trip with your AI assistant—from flight times to民宿 (minshuku) bookings. Two hours later, you ask, “What’s the Shinkansen schedule to Kyoto?” and it replies, “Did you mention Tokyo or Kyoto earlier?” This isn’t a sci-fi comedy trope; it was the “memory lapse” dilemma plaguing most LLM-powered agents in 2024. That all changed in October 2025, when a team from Zhejiang University unveiled LightMem—a framework that finally gave AI agents the ability to “remember” consistently. More importantly, it achieved the impossible balance: retaining more information while using fewer resources. …
Introduction: When You Hit Enter and Realize Your AI Isn’t That Smart Do you remember the first time you dropped a 5,000-line Python project into an AI model? I was full of excitement, expecting the model to act like a senior engineer—untangling dependencies, fixing annoying bugs, maybe even suggesting a better architecture. Reality hit hard: by the time the model reached line 3,000, it had already forgotten half the functions, produced contradictory answers, and sometimes hallucinated classes that didn’t exist. That’s when it struck me: the size of the context window and the way reasoning is handled determine whether an …
How MIT Taught AI to Plan with 94% Accuracy: A Deep Dive into PDDL-Instruct Imagine asking a powerful AI like ChatGPT to devise a plan for building a piece of furniture. It might produce a list of steps that sound perfectly logical: “Attach leg A to panel B using screw C.” It looks right. It sounds right. But if you try to follow it, you might find that step 3 requires a tool you don’t have, or step 7 tells you to attach a part you already sealed away inside the structure in step 2. The plan is plausible-sounding nonsense. …
Claude Sonnet 4.5: When AI Coding Agents Learn “Undo” and “Multithreaded Thinking” How Anthropic’s latest release is transforming AI from a coding assistant to a true collaborative partner It’s 2 AM. You’re staring at a massive codebase that needs refactoring, with hundreds of git commits behind you, and every change risks introducing new bugs. Have you ever wished for a technical partner who not only understands your needs but can also rewind mistakes with a single command? This is no longer science fiction. With Anthropic’s latest release of Claude Sonnet 4.5 and the accompanying Claude Code upgrades, this experience is …
Logics-Parsing: Breaking Boundaries in Complex Document Parsing – Why I’m Impressed by Alibaba’s Open-Source “All-Rounder” When faced with academic papers featuring multi-column layouts, mathematical formulas, and chemical structures, traditional OCR tools consistently fall short—until I encountered this 7B-parameter “compact powerhouse.” I still remember the last time I needed to parse a double-column academic paper. I had to launch three different tools in sequence: one for text recognition, another for tables, and a third specifically for mathematical formulas. The entire process felt like playing a technical version of “whack-a-mole”—just as I solved one problem, another popped up. That frustration persisted until …
Have you ever wondered how AI could take over those tedious tasks on your computer screen, like clicking buttons or filling forms, just by looking at what’s there? That’s where models like Holo1.5 come in. These are specialized vision-language models designed to help create agents that interact with user interfaces in a natural way. In this post, I’ll walk you through what Holo1.5 is all about, why it matters, and how it stacks up against others. We’ll break it down step by step, so even if you’re not a deep AI expert, you’ll get a clear picture. Let’s dive in. …
The end of the query-response paradigm and dawn of anticipatory computing For decades, human-computer interaction has followed a simple pattern: we ask, machines answer. This fundamental dynamic has constrained artificial intelligence to reactive roles—digital servants waiting for commands. ChatGPT Pulse shatters this paradigm by introducing something unprecedented: AI that initiates. Imagine waking up to find your AI assistant has already researched London travel tips because it noticed your upcoming trip, curated healthy dinner recipes based on your recent dietary conversations, and outlined next steps for that triathlon training you’ve been discussing. This isn’t future speculation—it’s what Pulse delivers today to …
“ What if an AI could not only write code but also simulate in its mind how that code will alter the state of a system? This is the paradigm shift offered by Code World Model (CWM). As developers, when a new code-generation model emerges, we ask two key questions: 1) How good is it at writing code? 2) Does it truly understand what happens when the code runs? Most large language models (LLMs) excel at the first but struggle with the second, leading to code that looks correct but fails at runtime or can’t reason about multi-step software engineering …
In today’s connected world, breaking down language barriers can make all the difference in a conversation, whether it’s a business meeting or a casual chat with friends from another country. On September 24, 2025, just a day after its release, I took a closer look at Qwen3-LiveTranslate-Flash, a new tool from the Qwen team at Alibaba Cloud. This system handles real-time translation for audio and video in 18 languages, both offline and during live sessions. What stands out is its ability to combine hearing, seeing, and speaking—making translations feel more natural and accurate, especially in tricky situations like noisy rooms. …
Introduction In the fast-paced world of AI, it feels like every few months we hear about a new “king of large language models.” OpenAI, Anthropic, Google DeepMind, Mistral — these names dominate headlines. But this time, the spotlight shifts to Qwen3-Max, Alibaba’s trillion-parameter giant. Naturally, the first questions developers and AI enthusiasts will ask are: How does Qwen3-Max compare to GPT-5? What makes it different from Claude Opus 4? Is it just a research prototype, or can developers actually use it? This article breaks it down in plain English, with benchmarks, API examples, and a practical multi-model benchmark script so …
Have you ever stared at a blank canvas, your mind buzzing with ideas but unsure where to begin? Whether you’re planning a home renovation, brainstorming a product concept, or organizing an event, translating abstract thoughts into a concrete vision can be the biggest hurdle. Enter Mixboard, the latest experiment from Google Labs. This new tool aims to revolutionize how we organize and explore creativity using the power of generative AI. This article provides a deep dive into what Mixboard is, how it works, and how it can become the catalyst for your next great project. What is Mixboard? Your Dynamic …
Introduction In September 2025, we’re excited to introduce Qwen-Image-Edit-2509, the latest iteration of our image editing framework. This model represents a significant leap forward in AI-powered visual tools, offering enhanced capabilities for multi-image editing, improved consistency in single-image edits, and native support for ControlNet conditions. Whether you’re a professional designer, a content creator, or an enthusiast, this update promises to streamline your workflow and elevate your creative output. Key Improvements in Qwen-Image-Edit-2509 Multi-Image Editing Support Qwen-Image-Edit-2509 now seamlessly handles multiple input images (1–3 images recommended), enabling complex compositions like “person + person,” “person + product,” or “person + scene.” By …
Introduction: Why Qwen3-Omni is AI’s “All-Round Champion” Remember traditional AI models that could only process text? They were like musicians who mastered only one instrument—skilled but limited in expression. Now, Alibaba’s Qwen team has introduced Qwen3-Omni, which operates like a full symphony orchestra—capable of simultaneously processing text, images, audio, and video while responding in both text and natural speech. “ “This isn’t simple feature stacking—it’s true multimodal fusion.” — The Qwen technical team describes their innovation. Imagine telling the model: “Watch this video, tell me what the people are saying, and analyze the background music style.” Qwen3-Omni not only understands …
Introduction We live in an era where search is everywhere. From asking Google “What’s the weather like in Tokyo tomorrow?” to querying ChatGPT about “How to implement a vector database,” information retrieval shapes almost every decision we make. But here’s the catch: most existing systems struggle when the question is complex, multi-step, or requires long reasoning. For example: “ “List 19th-century female painters in Paris and identify which museums currently exhibit their works.” That’s not a single keyword match. It’s a multi-hop reasoning task involving entity linking, temporal filtering, knowledge integration, and source verification. Traditional search engines fail because they’re …
Stock GPT: Your Natural Language Inventory Management Assistant In the world of inventory management, we’ve all faced this frustrating scenario: needing quick answers about stock levels but getting stuck behind complex database queries and technical barriers. Stock GPT completely transforms this experience, serving as an intelligent inventory assistant that understands everyday language, making inventory management as simple as having a conversation. What Exactly is Stock GPT? Stock GPT represents a breakthrough in inventory management technology. It’s an artificial intelligence-powered system that allows you to ask questions about your inventory using plain, conversational language – no coding knowledge or SQL expertise …
In the rapidly evolving world of artificial intelligence, large language models (LLMs) are pushing the boundaries of what’s possible in reasoning and problem-solving. Today, we’re diving deep into LongCat-Flash-Thinking, a groundbreaking 560-billion-parameter Mixture-of-Experts (MoE) model developed by the Meituan LongCat Team. This open-source powerhouse activates an average of 27 billion parameters, making it both efficient and powerful for tasks like math, coding, and agentic reasoning. If you’re an AI enthusiast, researcher, or developer searching for the latest in open-source AI reasoning models, this blog post is your ultimate guide. We’ll explore its architecture, training pipeline, key features, benchmarks, and how …
Klear-46B-A2.5B: A Revolutionary Mixture-of-Experts Model for Efficient AI Applications Understanding the Klear-46B-A2.5B Architecture At its core, the Klear-46B-A2.5B model represents a breakthrough in Mixture-of-Experts (MoE) architecture design. Developed by the Kwai-Klear team at Kuaishou, this model balances huge parameter scale (46 billion total parameters) with remarkable computational efficiency, activating just 2.5 billion parameters during inference. This innovation makes it ideal for real-world deployments where cost and performance are critical factors. Key Architectural Features Dynamic Expert Activation: Each layer activates 8 specialized experts plus 1 shared layer, enabling domain-specific processing without overwhelming system resources. Example: For coding tasks, math-focused experts handle …
Exploring Solution Aggregation in Large Language Models: When Majority Voting Falls Short Hey there, if you’re diving into the world of large language models (LLMs) and wondering how we can make them smarter at solving tough problems, you’ve come to the right place. I’ve been thinking about this a lot lately—especially how generating multiple solutions and then picking the best one can boost performance on reasoning tasks. But what if the most popular answer among those solutions isn’t the right one? That’s where things get interesting. In this post, we’ll unpack a method called AggLM, which uses reinforcement learning to …
# DeepSeek-R1: Enhancing Reasoning in Large Language Models via Reinforcement Learning ## Abstract DeepSeek-R1 is an advanced large language model (LLM) developed by DeepSeek-AI that leverages reinforcement learning (RL) to autonomously evolve reasoning capabilities without heavy reliance on human-annotated data. The model demonstrates remarkable improvements in mathematical reasoning, code generation, and a variety of academic benchmarks—for instance, achieving an accuracy of 77.9% on the AIME 2024 math competition, up from an initial 15.6%. This article details the training methodology, experimental results, engineering insights, and limitations of DeepSeek-R1, along with open-source resources for replication. ## 1. Introduction Reasoning capability is a …