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Monday

  1. The Beijing News

    Hands-on comparison of three AI office apps: Doubao Work, Qwen Office, and WorkBuddy

    Reporters from The Beijing News Shell Finance conducted a series of hands-on task tests on three AI office apps—Doubao Work, Qwen Office, and WorkBuddy—using the Doubao 2.1 Lite0921, Qwen3.87-Max, and Hy4 preview models, respectively. In the long-horizon task from the "2026 AI Office Sector Research Report," Doubao Work produced 10,000 words in 20 minutes 46 seconds, WorkBuddy produced 25,000 words in 21 minutes 18 seconds, and Qwen Office took over 1 hour to produce 50,000 words but consumed about 1,800 tokens, roughly 60 times that of the other two, requiring the reporter to top up 78 yuan to purchase a membership. In the multimodal tests, Doubao Work's poster and video had the highest degree of completion, and the 3D model generated by WorkBuddy was the closest to the original figurine, but when generating a comic it mistook its own icon for a teal pig face.

    Reporters from The Beijing News Shell Finance conducted a series of hands-on task tests on three AI office apps—Doubao Work, Qwen Office, and WorkBuddy—using the Doubao 2.1 Lite0921, Qwen3.87-Max, and Hy4 preview models, respectively. In the long-horizon task from the "2026 AI Office Sector Research Report," Doubao Work produced 10,000 words in 20 minutes 46 seconds, WorkBuddy produced 25,000 words in 21 minutes 18 seconds, and Qwen Office took over 1 hour to produce 50,000 words but consumed ab

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    #chinese#Evaluations / benchmarks#Agents#Multimodal

Saturday

Wednesday

Tuesday

Friday

Friday

  1. Story1 reports · 1 facts

    Matt Palmer demonstrated using the Cursor cloud Agent to generate an interface motion animation video against real Slack

    On October 30, 2026, Matt Palmer demonstrated opening Chrome and real Slack on the Linux remote desktop of the Cursor cloud Agent, having the Agent use code to generate a Slack interface motion animation video, and then iterating and revising after checking the easing and motion patterns against the real interface. He broke the process down into an inner loop (the Agent does the work, checks against the real thing, and fixes it) and an outer loop (a human provides references, preferences, and permissions and accepts the output), and proposed the ladder of Do→Codify→Generalize, turning one success into a Skill and then generalizing it. He emphasized that Slack was not decompiled; he merely gave the Agent a reference and asked it to extract visual patterns by comparison.

    On October 30, 2026, Matt Palmer demonstrated opening Chrome and real Slack on the Linux remote desktop of the Cursor cloud Agent, having the Agent use code to generate a Slack interface motion animation video, and then iterating and revising after checking the easing and motion patterns against the real interface. He broke the process down into an inner loop (the Agent does the work, checks against the real thing, and fixes it) and an outer loop (a human provides references, preferences, and pe

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  2. FactRelated story

    Matt demonstrates using Cursor Cloud Agent to generate UI motion videos by referencing real Slack

    On October 30, 2026, Matt Palmer demonstrated opening Chrome and real Slack on the Linux remote desktop of the Cursor cloud Agent, having the Agent use code to generate a Slack interface motion animation video, and then iterating and revising after checking the easing and motion patterns against the real interface. He broke the process down into an inner loop (the Agent does the work, checks against the real thing, and fixes it) and an outer loop (a human provides references, preferences, and permissions and accepts the output), and proposed the ladder of Do→Codify→Generalize, turning one success into a Skill and then generalizing it. He emphasized that Slack was not decompiled; he merely gave the Agent a reference and asked it to extract visual patterns by comparison.

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    View story:Matt Palmer demonstrated using the Cursor cloud Agent to generate an interface motion animation video against real Slack

  3. Story1 reports · 1 facts

    Artificial Analysis launches image-to-video benchmark AA-Video-I2V v2.1

    Artificial Analysis launches the image-to-video evaluation benchmarks AA-Video-I2V v2.1 and AA-Video-I2V-Silent v2.1, ranking models at up to 1080p resolution across 10 use-case categories, 10 capabilities, and multiple visual styles. The two versions are based on more than 58,000 human preference votes on over 1,000 prompts and more than 44,000 votes on 500 prompts, respectively, with only 5% of prompts made public in the public arena and rotated monthly. In the first version of the leaderboard, Dreamina Seedance 2.5 ranks first overall, statistically tied with the Seedance 2.0 and MiniMax H3 series, at a price of $34.12/min; the open-weight MiniMax H3 (768p) ranks third, at a price of $4.80/min.

    Artificial Analysis launches the image-to-video evaluation benchmarks AA-Video-I2V v2.1 and AA-Video-I2V-Silent v2.1, ranking models at up to 1080p resolution across 10 use-case categories, 10 capabilities, and multiple visual styles. The two versions are based on more than 58,000 human preference votes on over 1,000 prompts and more than 44,000 votes on 500 prompts, respectively, with only 5% of prompts made public in the public arena and rotated monthly. In the first version of the leaderboard

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  4. FactRelated story

    Artificial Analysis launches image-to-video benchmark AA-Video-I2V v2.1

    Artificial Analysis launches the image-to-video evaluation benchmarks AA-Video-I2V v2.1 and AA-Video-I2V-Silent v2.1, ranking models at up to 1080p resolution across 10 use-case categories, 10 capabilities, and multiple visual styles. The two versions are based on more than 58,000 human preference votes on over 1,000 prompts and more than 44,000 votes on 500 prompts, respectively, with only 5% of prompts made public in the public arena and rotated monthly. In the first version of the leaderboard, Dreamina Seedance 2.5 ranks first overall, statistically tied with the Seedance 2.0 and MiniMax H3 series, at a price of $34.12/min; the open-weight MiniMax H3 (768p) ranks third, at a price of $4.80/min.

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    View story:Artificial Analysis launches image-to-video benchmark AA-Video-I2V v2.1

Saturday

Sunday

  1. Story1 reports · 1 facts

    User Says Grok Bot Generated an Educational Animation Video Using Pure Front-End Code

    On October 22, 2026, a user claimed that Grok Bot generated an illustrated educational animation video. According to an article published by A Yi AI Notes that day, the author stated that they only provided Grok Bot with one sentence and one avatar image, without writing any storyboard prompts, and the backend then used pure front-end code to compile the newly open-sourced memory large model MemT-1.0 into a one-minute illustrated educational animation, with the animation, voiceover, and storyboard all written as code in one go and rendered on the spot. The author also claimed that because the video is code, it is easy to extend: to change the avatar, only one image path line needs to be modified, and to switch to English narration, re-running the compilation automatically aligns the timing. Currently, this claim comes only from this one author's description, and no other sources have cross-verified it.

    On October 22, 2026, a user claimed that Grok Bot generated an illustrated educational animation video. According to an article published by A Yi AI Notes that day, the author stated that they only provided Grok Bot with one sentence and one avatar image, without writing any storyboard prompts, and the backend then used pure front-end code to compile the newly open-sourced memory large model MemT-1.0 into a one-minute illustrated educational animation, with the animation, voiceover, and storyboa

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  2. Story1 reports · 1 facts

    Stanford releases public video and lecture notes for CME 295 Lecture 4

    Stanford course CME 295 Transformers & Large Language Models has been updated to Lecture 4, with both the video and lecture notes now publicly available. The topic of this lecture is Reinforcement learning with LLMs, covering everything from reinforcement learning and reward design to PPO, GRPO, RLVR, and DAPO, explaining each of the notations one by one. The course is taught by Afshine and Shervine Amidi, with 9 lectures in total, covering the Transformer architecture, attention variants, RoPE, LoRA fine-tuning, RLHF/GRPO training, Flash Attention inference optimization, MCP and AI Agents, and diffusion language models. Currently, Lecture 4 is public, and no evidence of updates for subsequent lectures has been seen yet.

    Stanford course CME 295 Transformers & Large Language Models has been updated to Lecture 4, with both the video and lecture notes now publicly available. The topic of this lecture is Reinforcement learning with LLMs, covering everything from reinforcement learning and reward design to PPO, GRPO, RLVR, and DAPO, explaining each of the notations one by one. The course is taught by Afshine and Shervine Amidi, with 9 lectures in total, covering the Transformer architecture, attention variants, RoPE,

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Thursday

  1. FactRelated story

    User says Grok Bot generates an educational animation video using pure front-end code

    On October 22, 2026, a user claimed that Grok Bot generated an illustrated educational animation video. According to an article published by A Yi AI Notes that day, the author stated that they only provided Grok Bot with one sentence and one avatar image, without writing any storyboard prompts, and the backend then used pure front-end code to compile the newly open-sourced memory large model MemT-1.0 into a one-minute illustrated educational animation, with the animation, voiceover, and storyboard all written as code in one go and rendered on the spot. The author also claimed that because the video is code, it is easy to extend: to change the avatar, only one image path line needs to be modified, and to switch to English narration, re-running the compilation automatically aligns the timing. Currently, this claim comes only from this one author's description, and no other sources have cross-verified it.

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    View story:User Says Grok Bot Generated an Educational Animation Video Using Pure Front-End Code

Tuesday

  1. FactRelated story

    Stanford CME 295 Lecture 4 public video and lecture notes

    Stanford course CME 295 Transformers & Large Language Models has been updated to Lecture 4, with both the video and lecture notes now publicly available. The topic of this lecture is Reinforcement learning with LLMs, covering everything from reinforcement learning and reward design to PPO, GRPO, RLVR, and DAPO, explaining each of the notations one by one. The course is taught by Afshine and Shervine Amidi, with 9 lectures in total, covering the Transformer architecture, attention variants, RoPE, LoRA fine-tuning, RLHF/GRPO training, Flash Attention inference optimization, MCP and AI Agents, and diffusion language models. Currently, Lecture 4 is public, and no evidence of updates for subsequent lectures has been seen yet.

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    View story:Stanford releases public video and lecture notes for CME 295 Lecture 4

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Friday