Loading video...

Video Failed to Load

Go Home

Qwen3.6-Plus delivers advanced reasoning and real-world performance, optimized for complex workflows like UI-to-code and data analysis. Its Enhanced API utilizes Context Reuse to minimize redundant reasoning and reduce token consumption.

alibaba_cloud's profile picture

Alibaba Cloud

1,190,189 subscribers

54,383,338 views • 2 months ago •via X (Twitter)

EducationNews & PoliticsScience & Technology
LIVE

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Run Python with the Gemini API. Nikita Namjoshi shares how to use the Code Execution tool in AI Studio to solve math problems, perform data analysis, and use code-based reasoning.
4:48

Run Python with the Gemini API. Nikita Namjoshi shares how to use the Code Execution tool in AI Studio to solve math problems, perform data analysis, and use code-based reasoning.

Google AI Developers

16,481 views • 8 months ago

With this new release, Gemini applies advanced reasoning to make sense of complex, changing information in real-time. 3.1 Pro can utilize advanced reasoning to bridge the gap between complex APIs and user-friendly design. For example, Gemini built a live aerospace dashboard, taking live telemetry from a public API and designing a front end to track the Space Station's orbit.
0:25

With this new release, Gemini applies advanced reasoning to make sense of complex, changing information in real-time. 3.1 Pro can utilize advanced reasoning to bridge the gap between complex APIs and user-friendly design. For example, Gemini built a live aerospace dashboard, taking live telemetry from a public API and designing a front end to track the Space Station's orbit.

Google Gemini

106,360 views • 4 months ago

Gemini 2.0 with Code Execution is actually INSANE🔥 90% don't even know about this feature. - Run Python code in real-time - Handles complex data analysis & makes charts instantly - Works in both API & AI Studio - Use Multimodal Live API and Reasoning model Here's how you can use 👇 1/4 Example 1: Real-time analysis & visualization
2:22

Gemini 2.0 with Code Execution is actually INSANE🔥 90% don't even know about this feature. - Run Python code in real-time - Handles complex data analysis & makes charts instantly - Works in both API & AI Studio - Use Multimodal Live API and Reasoning model Here's how you can use 👇 1/4 Example 1: Real-time analysis & visualization

AshutoshShrivastava

92,641 views • 1 year ago

GPT-5.4 is here. Native computer-use capabilities. Up to 1M tokens of context in Codex and the API. Best-in-class agentic coding for complex tasks. Scalable tool search across larger ecosystems. More efficient reasoning for long, tool-heavy workflows.
3:02

GPT-5.4 is here. Native computer-use capabilities. Up to 1M tokens of context in Codex and the API. Best-in-class agentic coding for complex tasks. Scalable tool search across larger ecosystems. More efficient reasoning for long, tool-heavy workflows.

OpenAI Developers

1,074,161 views • 4 months ago

Scale enterprise agents with Gemini 3 Pro and @eigent_ai 🚀 This integration combines Gemini 3 Pro’s long context window with Eigent’s infrastructure to support reliable, high-performance workflows. Use it to build agents for complex data analysis and automated decision-making.
0:49

Scale enterprise agents with Gemini 3 Pro and @eigent_ai 🚀 This integration combines Gemini 3 Pro’s long context window with Eigent’s infrastructure to support reliable, high-performance workflows. Use it to build agents for complex data analysis and automated decision-making.

Google AI Developers

43,495 views • 5 months ago

Current AI cannot solve difficult, real-world problems. The path to AGI is a focus on improving reasoning systems, multi agent workflows, and coordination.
0:33

Current AI cannot solve difficult, real-world problems. The path to AGI is a focus on improving reasoning systems, multi agent workflows, and coordination.

Sentient

12,844 views • 5 months ago

Chonkie (@ChonkieAI) is building the open source library for connecting your data to AI. Split unstructured data into optimized AI-ingestible chunks that boost your AI accuracy, improve app performance, and reduce token costs. Congrats on the launch, Shreyash Nigam and !
1:04

Chonkie (@ChonkieAI) is building the open source library for connecting your data to AI. Split unstructured data into optimized AI-ingestible chunks that boost your AI accuracy, improve app performance, and reduce token costs. Congrats on the launch, Shreyash Nigam and !

Y Combinator

38,406 views • 1 year ago

💡Divergence thinking💡 is a hallmark of human creativity and problem-solving 🤖Can LLMs also do divergent reasoning to generate diverse solutions🤔? Introducing Flow-of-Reasoning (FoR) 🌊, a data-efficient way of training LLM policy to generate diverse, high-quality reasoning trajectories Unlike existing RL (like PPO) and planning (like MCTS) to find the max-reward trajectory (akin to convergent thinking), FoR connects LLM reasoning with the #GFlowNet formulation and enables LLMs to find trajectories proportional to reward distribution. 🎬The demo video illustrates how FoR learns and infers multiple solutions to a ♠️Game24 puzzle. 🎯Inferring for diverse solutions could be useful for robustness, data augmentation, and enhanced model generalization. Project page: Paper: Github:
0:35

💡Divergence thinking💡 is a hallmark of human creativity and problem-solving 🤖Can LLMs also do divergent reasoning to generate diverse solutions🤔? Introducing Flow-of-Reasoning (FoR) 🌊, a data-efficient way of training LLM policy to generate diverse, high-quality reasoning trajectories Unlike existing RL (like PPO) and planning (like MCTS) to find the max-reward trajectory (akin to convergent thinking), FoR connects LLM reasoning with the #GFlowNet formulation and enables LLMs to find trajectories proportional to reward distribution. 🎬The demo video illustrates how FoR learns and infers multiple solutions to a ♠️Game24 puzzle. 🎯Inferring for diverse solutions could be useful for robustness, data augmentation, and enhanced model generalization. Project page: Paper: Github:

Lianhui Qin

50,447 views • 2 years ago

2/ In GitHub Copilot, GPT-5.2 is a fantastic multi-purpose model, especially when it comes to long-context and reasoning when coding or investigating a complex code base. Also available today.
0:22

2/ In GitHub Copilot, GPT-5.2 is a fantastic multi-purpose model, especially when it comes to long-context and reasoning when coding or investigating a complex code base. Also available today.

Satya Nadella

70,468 views • 7 months ago

Google DeepMind introduced two foundational models for embodied reasoning, enabling robots to comprehend, react, and take action in the physical world: ⦿ Gemini Robotics – built on Gemini 2.0. Integrates vision, language, and action for real-world dexterity, . ⦿ Gemini Robotics-ER – Enhances spatial reasoning for advanced robotic control. They are working with Apptronik to develop the next generation of humanoid robots.
1:11

Google DeepMind introduced two foundational models for embodied reasoning, enabling robots to comprehend, react, and take action in the physical world: ⦿ Gemini Robotics – built on Gemini 2.0. Integrates vision, language, and action for real-world dexterity, . ⦿ Gemini Robotics-ER – Enhances spatial reasoning for advanced robotic control. They are working with Apptronik to develop the next generation of humanoid robots.

The Humanoid Hub

73,097 views • 1 year ago

GPT-5.6 Sol is a breakthrough in complex reasoning and data analysis. Here, it analyzes hundreds of pages across a lending deal, reconciles terms across agreements, financials, diligence, collateral, and risk materials, flags issues, and saves a source-cited report to Box.
0:48

GPT-5.6 Sol is a breakthrough in complex reasoning and data analysis. Here, it analyzes hundreds of pages across a lending deal, reconciles terms across agreements, financials, diligence, collateral, and risk materials, flags issues, and saves a source-cited report to Box.

Box

742,623 views • 4 days ago

Qwen3.6-35B-A3B-NVFP4 Benchmark: MoE vs. Dense Performance Report This report details a performance comparisonbetween two artificial intelligence models, focusing on the Qwen3.6-35B-A3B-NVFP4 and its predecessor. While both models achieved flawless accuracy across a comprehensive 65-test benchmark covering vision, video, and reasoning, the 35B version demonstrated significant speed advantages. Utilizing a Mixture of Experts architecture, the 35B model achieved nearly four times higher throughput and drastically reduced latency for initial responses. It also showed superior efficiency in speculative decoding and successfully managed massive context lengths up to 128,000 tokens. Ultimately, the source recommends the 35B model for high-speed production environments, while noting the 27B model remains more stable for specific complex reasoning modes.
1:57

Qwen3.6-35B-A3B-NVFP4 Benchmark: MoE vs. Dense Performance Report This report details a performance comparisonbetween two artificial intelligence models, focusing on the Qwen3.6-35B-A3B-NVFP4 and its predecessor. While both models achieved flawless accuracy across a comprehensive 65-test benchmark covering vision, video, and reasoning, the 35B version demonstrated significant speed advantages. Utilizing a Mixture of Experts architecture, the 35B model achieved nearly four times higher throughput and drastically reduced latency for initial responses. It also showed superior efficiency in speculative decoding and successfully managed massive context lengths up to 128,000 tokens. Ultimately, the source recommends the 35B model for high-speed production environments, while noting the 27B model remains more stable for specific complex reasoning modes.

Mike Gannotti

10,457 views • 8 days ago

Today we are launching the next phase of AI reasoning development with Founders Fund, Franklin Templeton, Pantera Capital, Fireworks AI, OpenRouter, OpenHands, Dedalus Labs, alphaXiv, and more. AI is advancing at a relentless pace, but there are many reasoning capabilities we have yet to discover. Announcing Arena—an evaluation-driven platform for ideation, prototyping, and high-quality data generation—with top AI developers advancing SOTA performance on real-world enterprise reasoning tasks.
2:06

Today we are launching the next phase of AI reasoning development with Founders Fund, Franklin Templeton, Pantera Capital, Fireworks AI, OpenRouter, OpenHands, Dedalus Labs, alphaXiv, and more. AI is advancing at a relentless pace, but there are many reasoning capabilities we have yet to discover. Announcing Arena—an evaluation-driven platform for ideation, prototyping, and high-quality data generation—with top AI developers advancing SOTA performance on real-world enterprise reasoning tasks.

Sentient

271,979 views • 4 months ago

🕹️We are excited to introduce "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation" ChronoEdit reframes image editing as a video generation task to encourage temporal consistency. It leverages a temporal reasoning stage that denoises with “video reasoning tokens” to "reason" on physically plausible edits. See the attached video for results. Project Page: Arxiv: Code and model are coming.
1:38

🕹️We are excited to introduce "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation" ChronoEdit reframes image editing as a video generation task to encourage temporal consistency. It leverages a temporal reasoning stage that denoises with “video reasoning tokens” to "reason" on physically plausible edits. See the attached video for results. Project Page: Arxiv: Code and model are coming.

Huan Ling

36,869 views • 9 months ago

Most AI demos stop at text prompts. I wanted to see what Qwen3.7-Plus could do beyond chat, so I tested it through the API using an Airbnb interface screenshot. The model analyzed the UI, identified key components, explained the visual hierarchy, highlighted usability strengths, suggested UX improvements, and even generated a React + Tailwind structure to recreate the interface. A few things that stood out: 👁️ Multimodal understanding from a single screenshot 🧠 Strong reasoning around UX and product design decisions 💻 Able to bridge visual inputs and code generation ⚡ OpenAI-compatible API that was easy to integrate 💰 Impressive capability-to-cost ratio Qwen3.7-Plus isn't just a chatbot. It's a multimodal agent model designed for workflows that combine vision, reasoning, coding, and automation. Try Qwen3.7-Plus with limited time 20% off:
3:12

Most AI demos stop at text prompts. I wanted to see what Qwen3.7-Plus could do beyond chat, so I tested it through the API using an Airbnb interface screenshot. The model analyzed the UI, identified key components, explained the visual hierarchy, highlighted usability strengths, suggested UX improvements, and even generated a React + Tailwind structure to recreate the interface. A few things that stood out: 👁️ Multimodal understanding from a single screenshot 🧠 Strong reasoning around UX and product design decisions 💻 Able to bridge visual inputs and code generation ⚡ OpenAI-compatible API that was easy to integrate 💰 Impressive capability-to-cost ratio Qwen3.7-Plus isn't just a chatbot. It's a multimodal agent model designed for workflows that combine vision, reasoning, coding, and automation. Try Qwen3.7-Plus with limited time 20% off:

Kuria | AI

17,044 views • 1 month ago

INTRODUCING Nebula ☄️ The most powerful AI to read and write to every EVM chain — with advanced blockchain reasoning and execution capabilities. ◆ Query real-time onchain data ◆ Perform any onchain action ◆ Build autonomous web3 agents Get Early Access👇
0:41

INTRODUCING Nebula ☄️ The most powerful AI to read and write to every EVM chain — with advanced blockchain reasoning and execution capabilities. ◆ Query real-time onchain data ◆ Perform any onchain action ◆ Build autonomous web3 agents Get Early Access👇

thirdweb

956,053 views • 1 year ago

Many economists doubted AI until it hit their workflows. Now, tools like Claude Code do weeks of analysis in hours. As analysis becomes cheap, the real value shifts to novel ideas and gathering unique, proprietary data. (Video inspired by #econtwitter)
1:46

Many economists doubted AI until it hit their workflows. Now, tools like Claude Code do weeks of analysis in hours. As analysis becomes cheap, the real value shifts to novel ideas and gathering unique, proprietary data. (Video inspired by #econtwitter)

Daryl Fairweather, PhD | Chief Economist

44,432 views • 6 months ago