Baidu’s AI Assistant Reaches Milestone of 200 Million Monthly Active Users - WSJ
Baidu’s AI Assistant Reaches Milestone of 200 Million Monthly Active Users WSJ
Could not retrieve the full article text.
Read on GNews AI Baidu →Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
assistantmillion
We aren’t even close to AGI
Supposedly we’ve reached AGI according to Jensen Huang and Marc Andreessen. What a load of shit. I tried to get Claude code with Opus 4.6 max plan to play Elden Ring. Couldn’t even get past the first room. It made it past the character creator, but couldn’t leave the original chapel. If it can’t play a game that millions have beat, if it can’t even get past the first room, how are we even close to Artificial GENERAL Intelligence? I understand that this isn’t in its training data but that’s the entire point. Artificial general intelligence is supposed to be able to reason and think outside of its training data. submitted by /u/CrimsonShikabane [link] [comments]
![[OpenAI] Industrial policy for the Intelligence Age](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-matrix-rain-CvjLrWJiXfamUnvj5xT9J9.webp)
[OpenAI] Industrial policy for the Intelligence Age
As we move toward superintelligence, incremental policy updates won’t be enough. To kick-start this much needed conversation, OpenAI is offering a slate of people-first policy ideas(opens in a new window) designed to expand opportunity, share prosperity, and build resilient institutions—ensuring that advanced AI benefits everyone. These ideas are ambitious, but intentionally early and exploratory. We offer them not as a comprehensive or final set of recommendations, but as a starting point for discussion that we invite others to build on, refine, challenge, or choose among through the democratic process. To help sustain momentum, OpenAI is: welcoming and organizing feedback through [email protected] establishing a pilot program of fellowships and focused research grants of u
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Products
![[D] USQL Joins Were Cool, But Now I Want to Join the GenAI Party](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-server-room-ecVW4zMJjpPttojVbHXZCX.webp)
[D] USQL Joins Were Cool, But Now I Want to Join the GenAI Party
Hi Experts, I have 1.5 years of experience in Data Engineering, and now I want to start learning AI, ML, and Generative AI. I already have some knowledge of AI and ML from my college days as a CSE (AI) student. I’ve also worked on a few image classification projects and explored the application of AI in real-life problems. Currently, I want to dive deeper into Generative AI. However, before that, I’d like to strengthen my understanding of the core concepts behind it—such as neural networks and NLP—so that I can later focus on real-world applications. If you have a roadmap or guidance that data scientists or other professionals usually follow, it would be very helpful for me as I want to switch from a Data Engineering role to a Data Scientist role. submitted by /u/Far-Mixture-2254 [link] [c

Seedance 2.0 API: Integration Guide with Three Access Paths and Full Mode Reference
This post covers the Seedance 2.0 API — ByteDance’s multimodal AI video generation model, now accessible through EvoLink. The focus is on practical integration: three access methods, all three generation modes with code examples, the async task workflow, pricing model, and optimization techniques. Model Capabilities Overview Seedance 2.0 introduces several capabilities that distinguish it from previous-generation video models: Multimodal @-reference system : Up to 9 images + 3 video clips + 3 audio tracks as simultaneous input references per request Video-to-video editing : Modify specific elements in existing video while preserving overall structure and timing Frame-accurate audio synchronization : Auto-generated dialogue, sound effects, and background music aligned to individual frames M

Ant Group Launches Anvita for AI Agent Crypto
Ant Digital Technologies, the blockchain arm of Alipay's parent company, has unveiled Anvita — a two-part platform that lets AI agents autonomously hold crypto assets, execute trades, and settle payments in real time using stablecoins. For any fintech developer or crypto developer building payment infrastructure in the UK, this marks the moment a major Asian fintech giant went all in on the agent-to-agent economy running on crypto rails. Announced at the Real Up summit in Cannes on 5 April, Anvita sits at the exact intersection of agentic AI and crypto payment infrastructure — two domains converging faster than most payment developers anticipated. What Anvita Means for Payment Developers Anvita ships in two distinct modules, each targeting a different layer of the fintech stack: Anvita Taa

How MCP Is Changing Test Management — And Which Tools Support It
Quick Answer MCP (Model Context Protocol) is an open standard that lets AI agents — Claude, GitHub Copilot, Cursor, and others — interact directly with external tools through a unified interface. For test management, this means you can create test cases, start test cycles, assign testers, and pull coverage reports using natural language — without opening a browser. Only two test management platforms currently support MCP: TestKase and Qase. If your tool does not support MCP, your team is missing the biggest productivity shift in QA since test automation. Top 3 Key Takeaways MCP eliminates context switching. Instead of bouncing between your IDE, browser, and test management tool, you talk to an AI agent that handles everything in one place. Only 2 of 5 major test management tools support MC



Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!