#Video

AIActor Ben Affleck drew attention this week for explaining machine learning concepts, including convolutional neural networks, tensors, and transformers, in several recent interviews. He said he fine-tuned open video models by unfreezing weights and training only the last cinematic layer, using a dataset he built over about eight months for his startup. Affleck said he worries about students and learned helplessness more than Skynet, and predicted AI will be additive to the movie business.

AISantiago says physical consistency is the most important and hardest feature of a world model, and that many generated videos show objects defying gravity. He reports that Seedance 2.5 is currently the best among the evaluated world models. The post links to a physics evaluation benchmark in which eight video world models reached a top score of 57.76/100.

AIRyan Serhant has launched a second Instagram page featuring entirely AI-generated content, using a HeyGen avatar of himself in different outfits. The author praises the transparent disclosure of AI use and the choice to run it as a separate channel, and suggests the page as an example for anyone doubting current AI avatar quality.

AISara Hooker shared a video explainer, made by an Adaption AI team member, of Invent, a system for creating training datasets without existing data. She argues that curating high-quality, diverse data is the biggest hurdle in frontier AI, and that Invent is designed for this zero-data regime.

AIAravind Srinivas posted that "we're living in incredible times," highlighting a fully computer-made animated scene produced from concept art to final edit. The quoted post says the scene was planned in Blender, with reference images generated by Nano Banana and animation and score produced by Seedance 2.5.

AILuma Labs says there is no one model that excels at every task, since ideation and final-frame generation require different strengths. The post's point is that creative work should be matched to the best model for each stage rather than a single model for all.

AILuma argues that a model alone has never made a film, and that the real work lies in getting new capabilities into creators' hands and ensuring they can use them. The post frames this delivery and usability as how research becomes part of the creative craft.

AIFelix Rieseberg, who posts from Anthropic's account, says this is his favorite Claude music video so far. He prefers Claude as a human-directed tool for making art rather than generating art unattended, though he enjoyed this one, which he calls a little meta.

AIBen Affleck described fine-tuning open video models by freezing base weights and training only the last cinematic layer, using a learning rate of 2e-4. He said his company, InterPositive, built a private model per film from its own dailies after raising money to shoot a controlled dataset over eight months.

AIMatt Shumer reports that videos generated with Opus have appeared on LinkedIn. The post gives no further details on the videos, their creators, or how widely they are circulating.

AIYuchen Jin says no AI today can generate an Andrej Karpathy video from a prompt, and he hopes Karpathy will return, noting he has not uploaded a YouTube video in over a year. The post builds on Karpathy's suggestion that LLMs can produce bespoke explainer videos on arbitrary topics, though that idea is still emerging.

AIThe author jokes about founding a consulting firm that would use agents for work, Griffin for meetings, and Griffin for interviews to fill remote roles. They then question whether remote engineers and consultancies would still be needed if that became reality. The quoted Tavus post says Griffin passed a video Turing test with 48% of live interlocutors believing it was human.

AIIn an in-depth Q&A, the Runway Research team discusses real-time models, generative interfaces, and future directions for robotics. The post gives no specific model names, benchmarks, or release details.

AIWatch the OpenAI 2026 Developer Conference in 100 seconds === Opus 5.5 is really fun. It's been out for a week, but I use it to make a few videos every day, and each video process lets me iterate and optimize my video workflow.

AIGoogle's Jeff Dean says he is proud to have worked with many others on quite a few projects. The post is a brief reflection and names no specific products or figures.

AIRunway co-founder and Co-CEO Alex Germanidis explains why he sees world models as the endgame for AI video, with applications in robotics simulation and real-time generation. He also discusses how Sora pushed Runway into an intense competitive sprint and his vision of a fully neural operating system where interfaces are generated as pixels rather than HTML and code.

AIHowie.serious says Opus 5.5 with only medium thinking enabled produced a video of impressive quality, suggesting a grim outlook for human video work. The quoted post says the model made a promo video for the Applore app in a few minutes, and the author calls the result remarkable.

AIA Wan 3.0 feature can change a video's camera angle while keeping the exact same action from the original clip, according to a shared example. The main post only thanks the author for sharing a prompt, so no further details are confirmed.

AIA creator made a game-style video with Wan 3.0 and Nadou Pro, highlighting its quality and especially the consistency between scenes. The main post jokingly suggests the creator may have hit record mid-game, implying the clip is a real gameplay capture.

AIAlibaba's Wan account replied to a post praising Wan 3.0, which was shown producing a video in a Higgsfield demo alongside a GPT Image 2.5 "Sunburst" image. The main post itself only says "nice work!" and gives no specs, benchmarks, or availability details.

AIWorld Labs co-founders discuss Atlas, a world model for spatial intelligence, as the key to unifying pixel-level generation and reconstruction. The source says Atlas can digitally capture a 3D representation of a space from three photos, where previously 100 to 300 were needed.

AIAt an August 27 Ai2 event on expanding its work with the Paul G. Allen Research Center at Providence Swedish Cancer Institute, panelists identified five persistent challenges for scientific AI. The main ones are keeping AI steerable as research evolves, deciding which tasks to delegate, and avoiding the amplification of weak study design or bad data.

AIAt Google I/O, creators behind Flow, Project Genie, and Google Flow Music said human imagination, not the technology itself, shapes new storytelling. Designers Khyati Trehan and Kaloyan blend traditional design knowledge with vibe-coding to build Google Flow Tools, with Trehan saying that if the right tool doesn't exist, she can make it. Google Labs points users to Google Flow, Project Genie, and Google Flow Music at labs.google.

AISoumith Chintala, a Thinky-linked voice, said the company is at step one of a plan to increase human-AI bandwidth and raise the ceiling of joint intelligence. He shared a preview of interaction models, described as real-time collaborative tools that talk, listen, watch, and think alongside people. A linked Thinking Machines post describes the approach and early results.

AIChip Huyen praised projects at last weekend's Agentic Hackathon, which hosted by MongoDB and Cerebral Valley, where she served as a judge. Teams tackled long-running tasks such as memory management, recovery from mid-task failures, and consistency across steps and sub-agents, along with adaptive retrieval across databases, search indices, and websites. Finalist demos are scheduled in San Francisco tomorrow, with talks by Douglas Eck.