A SpaceX engineer details how the company is using a fleet of 9,000 lasers over the Starlink constellation to deliver high-speed internet across the globe.
We are witnessing a professional revolution where the boundaries between man and machine slowly fade away, giving rise to innovative collaboration.
Photo by Mateusz Kitka (Pexels)
As Artificial Intelligence (AI) continues to advance by leaps and bounds, it’s impossible to overlook the profound transformations that this technological revolution is imprinting on the professions of the future. A paradigm shift is underway, redefining not only the nature of work but also how we conceptualize collaboration between humans and machines.
As creator of the ETER9 Project (2), I perceive AI not only as a disruptive force but also as a powerful tool to shape a more efficient, innovative, and inclusive future. As we move forward in this new world, it’s crucial for each of us to contribute to building a professional environment that celebrates the interplay between humanity and technology, where the potential of AI is realized for the benefit of all.
In the ETER9 Project, dedicated to exploring the interaction between artificial intelligences and humans, I have gained unique insights into the transformative potential of AI. Reflecting on the future of professions, it’s evident that adaptability and a profound understanding of technological dynamics will be crucial to navigate this new landscape.
BRUSSELS — Three of Europe’s biggest satellite fleet operators — SES, Eutelsat and Hispasat — explained why they are investing in the European Commission’s Iris2 multi-orbit satellite constellation, designed as a public-private partnership with the Commission and the 22-nation European Space Agency (ESA).
Three weeks before their SpaceRise consortium’s best-and-final bid is due, these companies said Iris2 gives them part ownership in a global medium-and low-Earth-orbit network whose capex is mainly government funded.
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Electrons that spin to the right and the left at the same time. Particles that change their states together, even though they are separated by enormous distances. Intriguing phenomena like these are completely commonplace in the world of quantum physics. Researchers at the TUM Garching campus are using them to build quantum computers, high-sensitivity sensors and the internet of the future.
“We cool the chip down to only a few thousandths of a degree above absolute zero—colder than in outer space,” says Rudolf Gross, Professor of Technical Physics and Scientific Director of the Walther Meissner Institute (WMI) at the Garching research campus. He’s standing in front of a delicate-looking device with gold-colored disks connected by cables: The cooling system for a special chip that utilizes the bizarre laws of quantum physics.
For about twenty years now, researchers at WMI have been working on quantum computers, a technology based on a scientific revolution that occurred 100 years ago when quantum physics introduced a new way of looking at physics. Today it serves as the foundation for a “new era of technology,” as Prof. Gross calls it.
4 reviewer reports (4 anonymous)
13 citations in the Web of Science Core Collection.
Classical and Quantum Gravity Published by IOP Publishing Indexed in the Web of Science Core Collection Engages in Transparent Peer Review.
By Chuck Brooks
Computing paradigms as we know them will exponentially change when artificial intelligence is combined with classical, biological, chemical, and quantum computing. Artificial intelligence might guide and enhance quantum computing, run in a 5G or 6G environment, facilitate the Internet of Things, and stimulate materials science, biotech, genomics, and the metaverse.
Computers that can execute more than a quadrillion calculations per second should be available within the next ten years. We will also rely on clever computing software solutions to automate knowledge labor. Artificial intelligence technologies that improve cognitive performance across all envisioned industry verticals will support our future computing.
Continue reading “Computational Capabilities That Will Transform the World” »
The Glaze/Nightshade team, for its part, denies it is seeking destructive ends, writing: Nightshade’s goal is not to break models, but to increase the cost of training on unlicensed data, such that licensing images from their creators becomes a viable alternative.
In other words, the creators are seeking to make it so that AI model developers must pay artists to train on data from them that is uncorrupted.
How did we get here? It all comes down to how AI image generators have been trained: by scraping data from across the web, including scraping original artworks posted by artists who had no prior express knowledge nor decision-making power about this practice, and say the resulting AI models trained on their works threatens their livelihood by competing with them.
Combining three OLED light sources to mimic white light has reduced interference and bit error rates.
Radar altimeters are the sole indicators of altitude above a terrain. Spectrally adjacent 5G cellular bands pose significant risks of jamming altimeters and impacting flight landing and takeoff. As wireless technology expands in frequency coverage and utilizes spatial multiplexing, similar detrimental radio-frequency (RF) interference becomes a pressing issue.
To address this interference, RF front ends with exceptionally low latency are crucial for industries like transportation, health care, and the military, where the timeliness of transmitted messages is critical. Future generations of wireless technologies will impose even more stringent latency requirements on RF front-ends due to increased data rate, carrier frequency, and user count.
Additionally, challenges arise from the physical movement of transceivers, resulting in time-variant mixing ratios between interference and signal-of-interest (SOI). This necessitates real-time adaptability in mobile wireless receivers to handle fluctuating interference, particularly when it carries safety-to-life critical information for navigation and autonomous driving, such as aircraft and ground vehicles.
