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AI-powered misinformation detectors—artificial intelligence tools that identify false or inaccurate online content—have emerged as a potential intervention for helping internet users understand the veracity of the content they view. However, the algorithms used to create these detectors are experimental and largely untested at the scale necessary to be effective on a social media platform.

Ready to set another industry record!


New multi-launch agreement between Firefly Aerospace and True Anomaly includes three Alpha missions to provide rapid launch capabilities for Tactically Responsive Space mission sets

Cedar Park, Texas, October 17, 2024Firefly Aerospace, Inc., an end-to-end space transportation company, and space defense technology company True Anomaly, Inc., today announced a multi-launch agreement for three responsive launch missions aboard Firefly’s Alpha rocket. The first mission will deploy the True Anomaly Jackal Autonomous Orbital Vehicle (AOV) for the U.S. Space Force Space Systems Command’s VICTUS HAZE Tactically Responsive Space (TacRS) mission targeted for 2025. The two additional missions are available for execution between 2025 and 2027.

“VICTUS HAZE is an exemplar for how strong partnerships between the U.S. government and an exceptional industry team can create asymmetric capabilities at record speeds,” said Even Rogers, CEO of True Anomaly. “Firefly Aerospace has consistently demonstrated innovation and agility in the rapidly evolving landscape of responsive space launch logistics and space vehicle deployment. We are confident that they will build on their track record from VICTUS NOX, enabling True Anomaly to deploy the Jackal Autonomous Orbital Vehicle for VITCUS HAZE. The procurement of additional rapid, responsive launch capacity from Firefly beyond VICTUS HAZE, paired with True Anomaly’s rapid manufacturing capability will enable standing capacity for the U.S. National Security Space enterprise to rapidly respond to mission requirements in Low Earth Orbit and Medium Earth Orbit.”

She’s a real Vincent van Go-bot.

In a first for Sotheby’s, the famed auction house will sell a painting made by a humanoid robot — and it’s expected to fetch up to a whopping $180,000.

The robot, known as Ai-Da, created the painting of renowned mathematician and computer scientist Alan Turing entitled “AI God” with its own hydraulically powered hands.

Would you be comfortable having Optimus in your home? Share your thoughts in the comments.

At Tesla’s We, Robot Cybercab event, Elon Musk unveiled a surprising appearance by Tesla’s humanoid robot, Optimus. A group of these robots walked alongside the reveal of the new Robovan. Optimus bots were shown in a video performing daily tasks such as delivering packages and watering plants, with Musk emphasizing that these robots could soon do nearly anything—from walking your dog to babysitting kids. With a long-term price between $20,000 to $30,000, Musk claims that Optimus could be Tesla’s biggest product yet, eventually transforming civilization.

Watch as the Honey Badger legged robot from MAB Robotics demonstrates its underwater locomotion capabilities. Designed for extreme environments, this innovative robot showcases robust movement across submerged terrain, pushing the boundaries of legged robotics. Perfect for inspection and maintenance in flooded or challenging areas, the Honey Badger is a leap forward in autonomous robotics.

For more contact us or visit:
https://www.mabrobotics.pl/

If it were up to Larry Ellison, the exorbitantly rich cofounder of software outfit Oracle, all of us will soon be smiling for the camera — constantly. Not for a cheery photograph, but to appease our super-invasive, if not totally omnipresent, algorithmic overseers.

As Business Insider reports, the tech centibillionaire glibly predicts that the wonders of AI will bring about a new paradigm of supercharged surveillance, guaranteeing that the proles — excuse us, “citizens” — all behave and stay in line.

“We’re going to have supervision,” Ellison said this week at an Oracle financial analysts meeting, per BI. “Every police officer is going to be supervised at all times, and if there’s a problem, AI will report that problem and report it to the appropriate person.”

In recent years, artificial intelligence (AI) and deep learning models have advanced rapidly, becoming easily accessible. This has enabled people, even those without specialized expertise, to perform various tasks with AI. Among these models, generative adversarial networks (GANs) stand out for their outstanding performance in generating new data instances with the same characteristics as the training data, making them particularly effective for generating images, music, and text.

GANs consist of two , namely, a generator that creates new data distributions starting from random noise, and a discriminator which checks whether the generated data distribution is “real” (matching the training data) or “fake.” As training progresses, the generator improves at generating realistic distributions, and the discriminator at identifying the generated data as fake.

GANs use a loss function to measure differences between the fake and real distributions. However, this approach can cause issues like gradient vanishing and unstable learning, directly impacting stability and efficiency. Despite considerable progress in improving GANs, including structural modifications and loss function adjustments, challenges such as gradient vanishing and mode collapse, where the generator produces a limited variety, continue to limit their applicability.