Beyond Technicolorโs specific challenges, the broader VFX industry continues to grapple with systemic issues, including cost-cutting pressures, exploitative working conditions, and an unsustainable business model. VFX houses often operate on razor-thin margins, competing in a race to the bottom due to studiosโ demand for cheaper and faster work. This results in a cycle of overwork, burnout, and, in many cases, eventual bankruptcy, as seen with Rhythm & Hues in 2013 and now at Technicolor. The reliance on tax incentives and outsourcing further complicates matters, making VFX work highly unstable. With major vendors collapsing and industry workers facing continued uncertainty, many are calling for structural changes, including better contracts, collective bargaining, and a more sustainable production pipeline. Without meaningful reform, the industry risks seeing more historic names disappear and countless skilled artists move to other fields.
For many modern programming languages, the associated tooling has the lock-file based dependency management mechanism baked in. For a great example, consider Rust’s Cargo.
Not so with Python.
The default package manager for Python is pip. The default instruction to install a package is to run pip install package. Unfortunately, this imperative approach for creating your environment is entirely divorced from the versioning of your code. You very quickly end up in a situation where you have 100’s of packages installed. You no longer know which packages you explicitly asked to install, and which packages got installed because they were a transitive dependency. You no longer know which version of the code worked in which environment, and there is no way to roll back to an earlier version of your environment. Installing any new package could break your environment. …
Avat3r takes 4 input images of a person’s face and generates an animatable 3D head avatar in a single forward pass. The resulting 3D head representation can be animated at interactive rates. The entire creation process of the 3D avatar, from taking 4 smartphone pictures to the final result, can be executed within minutes.
The Nemesis system, for those unfamiliar, is a clever in-game mechanic which tracks a player’s actions to create enemies that feel capable of remembering past encounters. In the studio’s Middle-earth games, this allowed foes to rise through the ranks and enact revenge.
The patent itself –ย which you can view hereย – was originally filed back in 2016,ย before it was granted in 2021. It is dubbed “Nemesis characters, nemesis forts, social vendettas and followers in computer games”. As it stands, the patent has an expiration date of 11th August, 2036.
zopieux on Dec 5, 2024 : Ultralytics was attacked (or did it on purpose, waiting for a post mortem there), 8.3.41 contains nefarious code downloading and running a crypto miner hosted as a GitHub blob.
A spokesperson confirmed there will be some layoffs in its Vancouver studio as a result of this shift in business strategy. In addition to theย Tianaย series, the studio is also scrapping an unannounced feature-length project that was set to go straight toย Disney+.
Insiders say that Walt Disney Animation remains committed to releasing one theatrical film per year in addition to other shorts and special projects
The illustration below highlights the algorithms most frequently utilized in our everyday activities: They play a key role in everything we do from online shopping recommendations, navigation apps, social media, email spam filters and even smart home devices.
๐น ๐ฆ๐ผ๐ฟ๐๐ถ๐ป๐ด ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ – Organize data for efficiency. โ Example: Sorting email threads or search results.
๐น ๐๐ถ๐ท๐ธ๐๐๐ฟ๐ฎโ๐ ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ – Finds the shortest path in networks. โ Example: Google Maps driving routes.
๐น ๐ง๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฒ๐ฟ๐ – AI models that understand context and meaning. โ Example: ChatGPT, Claude and other LLMs.
The verdict is in: OpenAI’s newest and most capable traditional AI model, GPT-4.5, is big, expensive, and slow, providing marginally better performance thanย GPT-4oย at 30x the cost for input and 15x the cost for output. The new model seems to prove that longstanding rumors ofย diminishing returnsย in training unsupervised-learning LLMs were correct and that the so-called “scaling laws” cited by many for years have possibly met their natural end.
Stable Diffusion is a latent diffusion model that generates AI images from text. Instead of operating in the high-dimensional image space, it first compresses the image into the latent space.
Stable Diffusion belongs to a class of deep learning models called diffusion models. They are generative models, meaning they are designed to generate new data similar to what they have seen in training. In the case of Stable Diffusion, the data are images.
Why is it called the diffusion model? Because its math looks very much like diffusion in physics. Letโs go through the idea.
“Not every light performs the same way. Lights and lighting are tricky to handle. You have to plan for every circumstance. But the good news is, lighting can be adjusted. Let’s look at different factors that affect lighting in every scene you shoot. “
Use CRI, Luminous Efficacy and color temperature controls to match your needs.
Color Temperature Color temperature describes the โcolorโ of white light by a light source radiated by a perfect black body at a given temperature measured in degrees Kelvin
CRI “The Color Rendering Index is a measurement of how faithfully a light source reveals the colors of whatever it illuminates, it describes the ability of a light source to reveal the color of an object, as compared to the color a natural light source would provide. The highest possible CRI is 100. A CRI of 100 generally refers to a perfect black body, like a tungsten light source or the sun. “
