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VillageRoadShow production studio files for bankruptcy
Village Roadshow (prod company/financier: Wonka, the Matrix series, and Ocean’s 11) has filed for bankruptcy.
It’s a rough indicator of where we are in 2025 when one of the last independent production companies working with the studios goes under.
Here’s their balance sheet:
$400 M in library value of 100+ films (89 of which they co-own with Warner Bros.)
$500 M – $1bn total debt
$1.4 M in debt to WGA, whose members were told to stop working with Roadshow in December
$794 K owed to Bryan Cranston’s prod company
$250 K owed to Sony Pictures TV
$300 K/month overhead
The crowning expense that brought down this 36-year-old production company is the $18 M in (unpaid) legal fees from a lengthy and currently unresolved arbitration with their long-time partner Warner Bros, who they’ve had a co-financing arrangement since the late 90s.
Roadshow sued when WBD released their Matrix Resurrections (2021) film in theaters and on Max simultaneously, causing Roadshow to withhold their portion of the $190 M production costs.
Due to mounting financial pressures, Village Roadshow’s CEO, Steve Mosko, a veteran film and TV exec, left the company in January.
Now, this all falls on the shoulders of Jim Moore, CEO of Vine, an equity firm that owns Village Roadshow, as well as Luc Besson’s prod company EuropaCorp. -
Google Gemini Robotics
For safety considerations, Google mentions a “layered, holistic approach” that maintains traditional robot safety measures like collision avoidance and force limitations. The company describes developing a “Robot Constitution” framework inspired by Isaac Asimov’s Three Laws of Robotics and releasing a dataset unsurprisingly called “ASIMOV” to help researchers evaluate safety implications of robotic actions.
This new ASIMOV dataset represents Google’s attempt to create standardized ways to assess robot safety beyond physical harm prevention. The dataset appears designed to help researchers test how well AI models understand the potential consequences of actions a robot might take in various scenarios. According to Google’s announcement, the dataset will “help researchers to rigorously measure the safety implications of robotic actions in real-world scenarios.”
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Personalize Anything – For Free with Diffusion Transformer
https://fenghora.github.io/Personalize-Anything-Page
Customize any subject with advanced DiT without additional fine-tuning.
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Google Gemini 2.0 Flash new AI model extremely proficient at removing watermarks from images
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Stability.ai – Introducing Stable Virtual Camera: Multi-View Video Generation with 3D Camera Control
Capabilities
Stable Virtual Camera offers advanced capabilities for generating 3D videos, including:
- Dynamic Camera Control: Supports user-defined camera trajectories as well as multiple dynamic camera paths, including: 360°, Lemniscate (∞ shaped path), Spiral, Dolly Zoom In, Dolly Zoom Out, Zoom In, Zoom Out, Move Forward, Move Backward, Pan Up, Pan Down, Pan Left, Pan Right, and Roll.
- Flexible Inputs: Generates 3D videos from just one input image or up to 32.
- Multiple Aspect Ratios: Capable of producing videos in square (1:1), portrait (9:16), landscape (16:9), and other custom aspect ratios without additional training.
- Long Video Generation: Ensures 3D consistency in videos up to 1,000 frames, enabling seamless
Model limitations
In its initial version, Stable Virtual Camera may produce lower-quality results in certain scenarios. Input images featuring humans, animals, or dynamic textures like water often lead to degraded outputs. Additionally, highly ambiguous scenes, complex camera paths that intersect objects or surfaces, and irregularly shaped objects can cause flickering artifacts, especially when target viewpoints differ significantly from the input images.
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Types of AI Explained in a few Minutes – AI Glossary
1️⃣ 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗔𝗜) – The broadest category, covering automation, reasoning, and decision-making. Early AI was rule-based, but today, it’s mainly data-driven.
2️⃣ 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟) – AI that learns patterns from data without explicit programming. Includes decision trees, clustering, and regression models.
3️⃣ 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 (𝗡𝗡) – A subset of ML, inspired by the human brain, designed for pattern recognition and feature extraction.
4️⃣ 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗗𝗟) – Multi-layered neural networks that drives a lot of modern AI advancements, for example enabling image recognition, speech processing, and more.
5️⃣ 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 – A revolutionary deep learning architecture introduced by Google in 2017 that allows models to understand and generate language efficiently.
6️⃣ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 (𝗚𝗲𝗻𝗔𝗜) – AI that doesn’t just analyze data—it creates. From text and images to music and code, this layer powers today’s most advanced AI models.
7️⃣ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗣𝗿𝗲-𝗧𝗿𝗮𝗶𝗻𝗲𝗱 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 (𝗚𝗣𝗧) – A specific subset of Generative AI that uses transformers for text generation.
8️⃣ 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠) – Massive AI models trained on extensive datasets to understand and generate human-like language.
9️⃣ 𝗚𝗣𝗧-4 – One of the most advanced LLMs, built on transformer architecture, trained on vast datasets to generate human-like responses.
🔟 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 – A specific application of GPT-4, optimized for conversational AI and interactive use.
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The Maya civilization and the color blue
Maya blue is a highly unusual pigment because it is a mix of organic indigo and an inorganic clay mineral called palygorskite.
Echoing the color of an azure sky, the indelible pigment was used to accentuate everything from ceramics to human sacrifices in the Late Preclassic period (300 B.C. to A.D. 300).
A team of researchers led by Dean Arnold, an adjunct curator of anthropology at the Field Museum in Chicago, determined that the key to Maya blue was actually a sacred incense called copal.
By heating the mixture of indigo, copal and palygorskite over a fire, the Maya produced the unique pigment, he reported at the time.