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NASA has reestablished connection with Voyager 2 after a tense two weeks of not hearing anything from the probe. On July 21st, the agency lost contact with Voyager 2 following a series of planned commands that mistakenly pointed it two degrees away from our planet. While it is scheduled to automatically reset its orientation on October 15th, it’s not surprising that NASA scientists didn’t just wait for that date to know whether the spacecraft is still running. Voyager 2 was launched way back in 1977, and it’s one of the only two probes sending us back valuable data on interstellar space.

For a few days after July 21st, NASA wasn’t even sure what the spacecraft’s condition was. It wasn’t until August 1st that multiple ground antennas from the Deep Space Network (DSN) were able to detect a carrier signal from the probe. A carrier signal is what a spacecraft uses to beam data back to the ground, but NASA said the one DSN detected was too weak to be able to transmit any information. Still, it was enough to confirm that Voyager 2 was still working and that it hadn’t deviated from its trajectory.

Instead of simply waiting for October, Voyager’s ground team decided to take action. They concocted a plan to “shout” a command to the spacecraft across over 12.3 billion miles of space using the DSN, telling it to turn its antenna back to Earth. The whole process illustrated just how vast outer space truly is: It took 18.5 hours for that message to reach the probe, and another 18.5 hours for NASA to start receiving science and telemetry data again, indicating that Voyager 2 had received the command.

The Universe we live in is a transparent one, where light from stars and galaxies shines bright against a clear, dark backdrop.

But this wasn’t always the case – in its early years, the Universe was filled with a fog of hydrogen atoms that obscured light from the earliest stars and galaxies.

The intense ultraviolet light from the first generations of stars and galaxies is thought to have burned through the hydrogen fog, transforming the Universe into what we see today.

Using a private observatory, astronomers have performed the first photometric study of a peculiar W UMa-type binary known as CSS J003106.8+313347. Results of the study, published July 27 on the preprint server arXiv, shed more light on the properties of this system.

In general, W Ursae Majoris-type, or W UMa-type binaries (EWs) are eclipsing binaries with a short orbital period (below one day) and continuous light variation during a cycle. They are composed of two with similar temperature and luminosity, sharing a common envelope of material and are thus in contact with one another. Therefore, they are often dubbed “contact binaries.”

Located some 4,900 away, CSS J003106.8+313347 is an EW with an apparent magnitude of 14.73. The orbital period of the system is estimated to be approximately 0.344 days.

That’s how Andrew Feldman, CEO of Silicon Valley AI computer maker Cerebras, begins his introduction to his company’s latest achievement: An AI supercomputer capable of 2 billion billion operations per second (2 exaflops). The system, called Condor Galaxy 1, is on track to double in size within 12 weeks. In early 2024, it will be joined by two more systems of double that size. The Silicon Valley company plans to keep adding Condor Galaxy installations next year until it is running a network of nine supercomputers capable of 36 exaflops in total.

If large-language models and other generative AI are eating the world, Cerebras’s plan is to help them digest it. And the Sunnyvale, Calif., company is not alone. Other makers of AI-focused computers are building massive systems around either their own specialized processors or Nvidia’s latest GPU, the H100. While it’s difficult to judge the size and capabilities of most of these systems, Feldman claims Condor Galaxy 1 is already among the largest.

Condor Galaxy 1—assembled and started up in just 10 days—is made up of 32 Cerebras CS-2 computers and is set to expand to 64. The next two systems, to be built in Austin, Texas, and Ashville, N.C., will also house 64 CS-2s each.

AI singularity refers to the future point where artificial intelligence becomes so advanced that it surpasses human intelligence and undergoes rapid, unpredictable self-improvement, leading to an exponential increase in capabilities. At this stage, AI could potentially reshape society, science, and civilization in profound and transformative ways, and its behavior might become difficult for humans to comprehend or control.

The AI alignment problem refers to the challenge of ensuring that artificial intelligence systems are designed and programmed to act in accordance with human values, goals, and intentions. It involves developing AI systems that align with human interests, do not produce harmful outcomes, and operate transparently and predictably, so they can be trusted and reliably controlled. Addressing the AI alignment problem is crucial to avoid potential risks and negative consequences associated with AI development and deployment.

The AI Singularity Future is an aspiring Decentralized Autonomous Organization(DAO) on Discord (Link) working on the AI alignment and the human alignment problem. We aim to solve the AI alignment problem by guiding the evolution of the AI towards the utopian future of Resource Based Economy. This organisation is being run by the volunteers and the Regional Coordinators of The-Venus-Project Support Community.

A new study reports conclusive evidence for the breakdown of standard gravity in the low acceleration limit from a verifiable analysis of the orbital motions of long-period, widely separated, binary stars, usually referred to as wide binaries in astronomy and astrophysics.

The study carried out by Kyu-Hyun Chae, professor of physics and astronomy at Sejong University in Seoul, used up to 26,500 wide binaries within 650 (LY) observed by European Space Agency’s Gaia space telescope. The study was published in the 1 August 2023 issue of the Astrophysical Journal.

For a key improvement over other studies Chae’s study focused on calculating gravitational accelerations experienced by as a function of their separation or, equivalently the orbital period, by a Monte Carlo deprojection of observed sky-projected motions to the three-dimensional space.