Do you have an image idea in mind and propose to use one of these trendy Generative Artificial Intelligences to create it? Whether it’s MidJourney or DALL·E 3, they all promise to generate your idea within seconds. You input a phrase, and voila! Before your eyes appears a spectacular image, supposedly entirely original and tailored to your request. Or is it?
Microsoft’s recent earnings report may have seemed standard fare to the casual observer, but for those with a keen eye, a standout figure suggested something more profound is at play. The tech behemoth disclosed a seemingly modest increase in artificial intelligence (AI) services—contributing to a 7% growth in its Azure data center business. Despite this slight uptick, Microsoft has announced plans to ramp up its data center spending by an astonishing 50% this year. But why?
In the sprawling megacity of NeoYork, where the buzzing of tech had become the second language of its inhabitants, Dr. Lena Mirov, a prominent AI communications expert, had just embarked on what was to be the most significant day of her career. Her latest invention, the AIC-500, a device that promised to revolutionize human interaction, was to be unveiled.
In the realm of technological advancements, artificial intelligence (AI) stands as a titan, promising to reshape our world with every algorithm and application. Yet, beneath the sheen of progress, a darker narrative simmers—one of potential peril and paranoia that AI might not just outsmart us but could lead to our undoing.
As we stand on the brink of a new technological revolution, the field of video production is undergoing a transformative change, spearheaded by advancements in artificial intelligence. The introduction of tools like SORA has not just improved the quality of video content but has fundamentally altered the creative process itself. This evolution is not merely technical but a renaissance of creativity, blending AI capabilities with human ingenuity.
What DLSS essentially does is it averages out the pixels around us, much like what our computer does. For instance, when we’re playing a game and we want to lower the resolution. Imagine you have a 4K monitor, but the game isn’t running smoothly. So, you decide to lower the resolution to 1080p. The problem is, the graphics card would be generating four times fewer pixels than the screen actually has, and it needs to know what to display. It could either just put something there in the middle in a tiny square or it has to have some technique to stretch this image and fill in the pixels.
A few years back, NVIDIA introduced a series of graphics cards that came with a couple of rather groundbreaking ideas for the time. The first of the two was ray tracing, a technology that literally simulates the physics of light instead of relying on cheap tricks to achieve more lifelike illumination. NVIDIA was so confident in this endeavor that they even changed the name of their graphics cards from GTX to RTX in honor of Ray Tracing. However, they also introduced another, less flashy technology that garnered a bit more attention over time: DLSS, a technique aimed at making games run smoother using artificial intelligence.
