“There are many good reasons to be concerned about the rise of generative AI(…). Unfortunately, there are also many good reasons to be concerned about copyright’s growing prevalence in the policy discourse around AI’s regulation. Insisting that copyright protects an exclusive right to use materials for text and data mining practices (whether for informational analysis or machine learning to train generative AI models) is likely to do more harm than good. As many others have explained, imposing copyright constraints will certainly limit competition in the AI industry, creating cost-prohibitive barriers to quality data and ensuring that only the most powerful players have the means to build the best AI tools (provoking all of the usual monopoly concerns that accompany this kind of market reality but arguably on a greater scale than ever before). It will not, however, prevent the continued development and widespread use of generative AI.”
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“(…) As Michal Shur-Ofry has explained, the technical traits of generative AI already mean that its outputs will tend towards the dominant, likely reflecting ‘a relatively narrow, mainstream view, prioritizing the popular and conventional over diverse contents and narratives.’ Perhaps, then, if the political goal is to push for equality, participation, and representation in the AI age, critics’ demands should focus not on exclusivity but inclusivity. If we want to encourage the development of ethical and responsible AI, maybe we should be asking what kind of material and training data must be included in the inputs and outputs of AI to advance that goal. Certainly, relying on copyright and the market to dictate what is in and what is out is unlikely to advance a public interest or equality-oriented agenda.”
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“If copyright is not the solution, however, it might reasonably be asked: what is? The first step to answering that question—to producing a purposively sound prescription and evidence-based prognosis, is to correctly diagnose the problem. If, as I have argued, the problem is not that AI models are being trained on copyright works without their owners’ consent, then requiring copyright owners’ consent and/or compensation for the use of their work in AI-training datasets is not the appropriate solution. (…)If the only real copyright problem is that the outputs of generative AI may be substantially similar to specific human-authored and copyright-protected works, then copyright law as we know it already provides the solution.”
Narrative voice via Artlistai, News Reporter PlayAI, All other voices are V2V in Elevenlabs. Powered by (in order of amount) ‘HailuoAI’, ‘KlingAI’ and of course some of our special source. Performance capture by ‘Runway’s Act-One’. Edited and color graded in ‘DaVinci Resolve’. Composited with ‘After Effects’.
In this film, the ‘Newton’s Cradle’ isn’t just a symbolic object—it represents the fragile balance between control and freedom in a world where time itself is being manipulated. The oscillation of the cradle reflects the constant push and pull of power in this dystopian society. By the end of the film, we discover that this seemingly innocuous object holds the potential to disrupt the system, offering a glimmer of hope that time can be reset and balance restored.
About 576 megapixels for the entire field of view.
Consider a view in front of you that is 90 degrees by 90 degrees, like looking through an open window at a scene. The number of pixels would be:
90 degrees * 60 arc-minutes/degree * 1/0.3 * 90 * 60 * 1/0.3 = 324,000,000 pixels (324 megapixels).
At any one moment, you actually do not perceive that many pixels, but your eye moves around the scene to see all the detail you want. But the human eye really sees a larger field of view, close to 180 degrees. Let’s be conservative and use 120 degrees for the field of view. Then we would see:
In photography, exposure value (EV) is a number that represents a combination of a camera’s shutter speed and f-number, such that all combinations that yield the same exposure have the same EV (for any fixed scene luminance).
The EV concept was developed in an attempt to simplify choosing among combinations of equivalent camera settings. Although all camera settings with the same EV nominally give the same exposure, they do not necessarily give the same picture. EV is also used to indicate an interval on the photographic exposure scale. 1 EV corresponding to a standard power-of-2 exposure step, commonly referred to as a stop
EV 0 corresponds to an exposure time of 1 sec and a relative aperture of f/1.0. If the EV is known, it can be used to select combinations of exposure time and f-number.
Note EV does not equal to photographic exposure. Photographic Exposureis defined as how much light hits the camera’s sensor. It depends on the camera settings mainly aperture and shutter speed. Exposure value (known as EV) is a number that represents theexposure setting of the camera.
Thus, strictly, EV is not a measure of luminance (indirect or reflected exposure) or illuminance (incidentl exposure); rather, an EV corresponds to a luminance (or illuminance) for which a camera with a given ISO speed would use the indicated EV to obtain the nominally correct exposure. Nonetheless, it is common practice among photographic equipment manufacturers to express luminance in EV for ISO 100 speed, as when specifying metering range or autofocus sensitivity.
The exposure depends on two things: how much light gets through the lenses to the camera’s sensor and for how long the sensor is exposed. The former is a function of the aperture value while the latter is a function of the shutter speed. Exposure value is a number that represents this potential amount of light that could hit the sensor. It is important to understand that exposure value is a measure of how exposed the sensor is to light and not a measure of how much light actually hits the sensor. The exposure value is independent of how lit the scene is. For example a pair of aperture value and shutter speed represents the same exposure value both if the camera is used during a very bright day or during a dark night.
Each exposure value number represents all the possible shutter and aperture settings that result in the same exposure. Although the exposure value is the same for different combinations of aperture values and shutter speeds the resulting photo can be very different (the aperture controls the depth of field while shutter speed controls how much motion is captured).
EV 0.0 is defined as the exposure when setting the aperture to f-number 1.0 and the shutter speed to 1 second. All other exposure values are relative to that number. Exposure values are on a base two logarithmic scale. This means that every single step of EV – plus or minus 1 – represents the exposure (actual light that hits the sensor) being halved or doubled.
Spectral sensitivity of eye is influenced by light intensity. And the light intensity determines the level of activity of cones cell and rod cell. This is the main characteristic of human vision. Sensitivity to individual colors, in other words, wavelengths of the light spectrum, is explained by the RGB (red-green-blue) theory. This theory assumed that there are three kinds of cones. It’s selectively sensitive to red (700-630 nm), green (560-500 nm), and blue (490-450 nm) light. And their mutual interaction allow to perceive all colors of the spectrum.
