“We combine these two optical systems in a single camera by splitting the aperture: one half applies application-specific modulation using a diffractive optical element, and the other captures a conventional image. This co-design with a dual-pixel sensor allows simultaneous capture of coded and uncoded images — without increasing physical or computational footprint.”
The EU Artificial Intelligence (AI) Act, which went into effect on August 1, 2024.
This act implements a risk-based approach to AI regulation, categorizing AI systems based on the level of risk they pose. High-risk systems, such as those used in healthcare, transport, and law enforcement, face stringent requirements, including risk management, transparency, and human oversight.
Key provisions of the AI Act include:
Transparency and Safety Requirements: AI systems must be designed to be safe, transparent, and easily understandable to users. This includes labeling requirements for AI-generated content, such as deepfakes (Engadget).
Risk Management and Compliance: Companies must establish comprehensive governance frameworks to assess and manage the risks associated with their AI systems. This includes compliance programs that cover data privacy, ethical use, and geographical considerations (Faegre Drinker Biddle & Reath LLP) (Passle).
Copyright and Data Mining: Companies must adhere to copyright laws when training AI models, obtaining proper authorization from rights holders for text and data mining unless it is for research purposes (Engadget).
Prohibitions and Restrictions: AI systems that manipulate behavior, exploit vulnerabilities, or perform social scoring are prohibited. The act also sets out specific rules for high-risk AI applications and imposes fines for non-compliance (Passle).
For US tech firms, compliance with the EU AI Act is critical due to the EU’s significant market size
FLUX (or FLUX. 1) is a suite of text-to-image models from Black Forest Labs, a new company set up by some of the AI researchers behind innovations and models like VQGAN, Stable Diffusion, Latent Diffusion, and Adversarial Diffusion Distillation
In color technology, color depth also known as bit depth, is either the number of bits used to indicate the color of a single pixel, OR the number of bits used for each color component of a single pixel.
When referring to a pixel, the concept can be defined as bits per pixel (bpp).
When referring to a color component, the concept can be defined as bits per component, bits per channel, bits per color (all three abbreviated bpc), and also bits per pixel component, bits per color channel or bits per sample (bps). Modern standards tend to use bits per component, but historical lower-depth systems used bits per pixel more often.
Color depth is only one aspect of color representation, expressing the precision with which the amount of each primary can be expressed; the other aspect is how broad a range of colors can be expressed (the gamut). The definition of both color precision and gamut is accomplished with a color encoding specification which assigns a digital code value to a location in a color space.
Spline Path Control is a simple tool designed to make it easy to create motion controls. It allows you to create and animate shapes that follow splines, and then export the result as a .webm video file. This project was created to simplify the process of generating control videos for tools like VACE. Use it to control the motion of anything (camera movement, objects, humans etc) all without extra prompting.
