Lifeboat Foundation

“When checking the system this morning, I noticed your account logged in for over 20 hours,” begins a December 1998 email from the president of my dial-up Internet service provider (ISP) at the time. “Our service is unlimited, but we ask that you actually be using the connection while logged in.”

But I’m getting ahead of myself—why do I have an email from 1998?

The Internet just changed forever, but most people living in the United States don’t even realize what just happened. A draconian new law known as the “Digital Services Act” went into effect in the European Union on Friday, and it establishes an extremely strict regime of Internet censorship that is far more authoritarian than anything we have ever seen before.

From this point forward, hordes of European bureaucrats will be the arbiters of what is acceptable to say on the Internet. If they discover something that you have said on a large online platform that they do not like, they can force that platform to take it down, because someone in Europe might see it. So even though this is a European law, the truth is that it is going to have a tremendous impact on all of us.

NASA Commercial Space Capabilities office and SpaceX have a 24 page agreed plan to develop the SpaceX starship into a low earth orbit space station design by 2028. This is unfunded and aspirational. The parties will cooperate to try and make it happen. SpaceX with successful Starlink commercial services will have the funds to make this happen.

There are many other milestones that NASA and SpaceX are trying to achieve with Starship.

It will take another 2–4 years to actually launch the Starship space station.

Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.

To tackle all of these missions effectively, UAVs should be able to reliably detect targets and objects of interest in their surroundings. Computer scientists have thus been trying to devise new computational techniques that could enable these capabilities, using deep learning or other approaches.

Researchers at Yunnan University and the Chinese Academy of Sciences recently introduced a new object-detection system based on edge computing. Their proposed system, introduced in the IEEE Internet of Things Journal, could provide UAVs with the ability to spot relevant objects and targets in their surroundings without significantly increasing their power-consumption.

Elon Musk’s rocket manufacturing company SpaceX has completed 60 launches this year, much to the CEO’s excitement.

What Happened: SpaceX’s Falcon 9 rocket launched 22 Starlink satellites to low-Earth orbit from Florida on Thursday at about 10:21 p.m. ET, marking the company’s 60th launch this year.

“Congrats to the SpaceX team on launch 60 of 2023!” Musk wrote.

Examples the team gives include choosing an object to use as a hammer when there’s no hammer available (the robot chooses a rock) and picking the best drink for a tired person (the robot chooses an energy drink).

“RT-2 shows improved generalization capabilities and semantic and visual understanding beyond the robotic data it was exposed to,” the researchers wrote in a Google blog post. “This includes interpreting new commands and responding to user commands by performing rudimentary reasoning, such as reasoning about object categories or high-level descriptions.”

The dream of general-purpose robots that can help humans with whatever may come up—whether in a home, a commercial setting, or an industrial setting—won’t be achievable until robots can learn on the go. What seems like the most basic instinct to us is, for robots, a complex combination of understanding context, being able to reason through it, and taking actions to solve problems that weren’t anticipated to pop up. Programming them to react appropriately to a variety of unplanned scenarios is impossible, so they need to be able to generalize and learn from experience, just like humans do.

For the first time in my timezone, SpaceX completed 9 launches in a month. Previously, if you were based in Europe, you saw 9 launches in a month a few months ago. At 9 launches/month that is a current rate of 108 launches/year, making SpaceX’s goal of 100 launches this year a possibility.

They had a lot of trouble getting this flight off today as a recent hurricane is still affecting the weather some. They got around this by having a 5 and a half hour launch window so they just waited a few hours until the weather was clear for several minutes and they launched!

Continue reading “SpaceX Falcon 9 Launches Starlink 6-13 Mission” »

Digital sociology explores the interplay between digital technology, social behaviors, and societal structures. As an emerging discipline, it delves into how online interactions, social media platforms, and digital tools shape and reflect cultural dynamics, personal identities, and group norms. Digital sociologists analyze trends in cyber communities, the implications of digital data collection, and the broader impact of the internet on social evolution.

In this age of rapid technological advancement — where we find ourselves in the midst of a Digital Revolution and most recently, in an AI Revolution, the fast-spinning changes in society require analysis and understanding. Digital sociology provides critical insights into the multifaceted relationship between technology and the fabric of society.

Experts warn that AI-generated content may pose a threat to the AI technology that produced it.

In a recent paper on how generative AI tools like ChatGPT are trained, a team of AI researchers from schools like the University of Oxford and the University of Cambridge found that the large language models behind the technology may potentially be trained on other AI-generated content as it continues to spread in droves across the internet — a phenomenon they coined as “model collapse.” In turn, the researchers claim that generative AI tools may respond to user queries with lower-quality outputs, as their models become more widely trained on “synthetic data” instead of the human-made content that make their responses unique.

Other AI researchers have coined their own terms to describe the training method. In a paper released in July, researchers from Stanford and Rice universities called this phenomenon the “Model Autography Disorder,” in which the “self-consuming” loop of AI training itself on content generated by other AI could result in generative AI tools “doomed” to have their “quality” and “diversity” of images and text generated falter. Jathan Sadowski, a senior fellow at the Emerging Technologies Research Lab in Australia who researches AI, called this phenomenon “Habsburg AI,” arguing that AI systems heavily trained on outputs of other generative AI tools can create “inbred mutant” responses that contain “exaggerated, grotesque features.”