Lifeboat Foundation

Here’s some interesting SpaceX News!

For the last few months, SpaceX has been having trouble launching Starlink satellites, once going almost two months between Starlink launches. The problem wasn’t that SpaceX was launching less often, but that SpaceX had a surge in business. The long-term solution was to go from 61 launches last year to about 100 launches this year. (SpaceX only did 31 launches in 2021, so they are growing rapidly!)

This month was much better for Starlink launches, with 3 this month. The key to squeezing in 3 launches was that SpaceX did 7 launches this month which is a 7 12 = 84 launch rate, definitely higher than last’s years 61 launch rate.

Continue reading “What Is Wright’s Law” »

For years the dream of competition in the world of home internet has been just that; a dream. Now in 2023, we are starting to see it become a reality. Wireless internet from places like T-Mobile and Verizon has come on strong recently. New faster satellite internet from SpaceX, and fiber internet have all expanded recently, meaning many Americans who may have had two options in the past now have 4 or 5 options.

Now Amazon wants to join that list by offering high speed internet from space, similar to SpaceX’s Starlink service.

Here is everything we know about Amazon’s new home internet service:

The workshop discusses the recent issue Systems Neuroscience Through The Lens of Evolutionary Theory edited by Paul Cisek and Ben Hayden published by the Royal Society:

https://royalsocietypublishing.org/toc/rstb/2022/377/1844

Continue reading “Systems Neuroscience Through the Lens of Evolutionary Theory Workshop” »

A double-whammy for systematic education since the need for knowledge-workers will decrease at the same time as AI fundamentally questions the need for / uses of “Knowledge Gatekeepers” — establishment academia, lawyers, even actors — the chatterbot classes.

When high school English teacher Kelly Gibson first encountered ChatGPT in December, the existential anxiety kicked in fast. While the internet delighted in the chatbot’s superficially sophisticated answers to users’ prompts, many educators were less amused. If anyone could ask ChatGPT to “write 300 words on what the green light symbolizes in The Great Gatsby,” what would stop students from feeding their homework to the bot? Speculation swirled about a new era of rampant cheating and even a death knell for essays, or education itself. “I thought, ‘Oh my god, this is literally what I teach,’” Gibson says.

But amid the panic, some enterprising teachers see ChatGPT as an opportunity to redesign what learning looks like—and what they invent could shape the future of the classroom. Gibson is one of them. After her initial alarm subsided, she spent her winter vacation tinkering with ChatGPT and figuring out ways to incorporate it into her lessons. She might ask kids to generate text using the bot and then edit it themselves to find the chatbot’s errors or improve upon its writing style. Gibson, who has been teaching for 25 years, likened it to more familiar tech tools that enhance, not replace, learning and critical thinking. “I don’t know how to do it well yet, but I want AI chatbots to become like calculators for writing,” she says.

Continue reading “ChatGPT Is Coming for Classrooms. Don’t Panic” »

“The future of AI is much bigger than anyone realizes — not just in terms of technology, but in its impact on society as a whole.” — Mark Zuckerberg

Prompt engineering is a process of crafting optimized input texts (prompts) to generate accurate results from the artificial intelligence model. By the launch of ChatGPT, prompt engineering is the booming term in internet. Actually what is its deep meaning and is it be the future of AI. Prompt engineering is a relatively new field that focuses on the design and development of systems that can generate human-like prompts, such as text, speech, and images. These prompts can be used to interact with users in a more natural and intuitive way, making it easier for them to understand and use AI-powered systems.

By the advance of artificial intelligence models like ChatGPT, midjourney and stable diffusion which are enriched with high potential people are confused how to use it and what are the optimized prompts that could be used to extract the full potential of these models. One key aspect of prompt engineering is data preprocessing and preparation. This includes cleaning, normalizing, and formatting the data used to train the model, so that it is in the right format and of high quality.

Blizzard entertainment’s servers were shut down this week after two decades.

Millions of gamers who grew up with stories of achievements in the medieval digital world of Azeroth were in tears after Tuesday night after their access to the World of Warcraft (WoW) game servers was removed in China, CNN.

Sascha Steinbach/Getty.

Continue reading “Millions of gamers in China lose access to World of Warcraft” »

The advent of Large Language Models (LLMs) has unleashed a torrent of possibilities for cutting-edge technology. These powerful computer programs, capable of processing vast amounts of human language data, have paved the way for revolutionary tools like advanced chatbots and voice-controlled devices.

Perhaps the most striking example of this technology in action is ChatGPT, one of today’s hottest internet sensations as of late. ChatGPT is an AI platform that represents the forefront of what we can achieve when we infuse natural language with AI.

But as humans continue to push the boundaries of what’s possible, we are also turning our attention to another frontier: decoding the languages of animals. This article will explore the latest progress in this research, the potential opportunities it could unlock, and the possible risks it could unleash.

Tech giants from Google to Amazon and Alibaba —not to mention nation-states vying for technological supremacy—are racing to dominate this space. The global quantum-computing industry is projected to grow from $412 million in 2020 to $8.6 billion in 2027, according to an International Data Corp. analysis.

Whereas traditional computers rely on binary “bits”—switches either on or off, denoted as 1s and 0s—to process information, the “qubits” that underpin quantum computing are tiny subatomic particles that can exist in some percentage of both states simultaneously, rather like a coin spinning in midair. This leap from dual to multivariate processing exponentially boosts computing power. Complex problems that currently take the most powerful supercomputer several years could potentially be solved in seconds. Future quantum computers could open hitherto unfathomable frontiers in mathematics and science, helping to solve existential challenges like climate change and food security. A flurry of recent breakthroughs and government investment means we now sit on the cusp of a quantum revolution. “I believe we will do more in the next five years in quantum innovation than we did in the last 30,” says Gambetta.

But any disrupter comes with risks, and quantum has become a national-security migraine. Its problem-solving capacity will soon render all existing cryptography obsolete, jeopardizing communications, financial transactions, and even military defenses. “People describe quantum as a new space race,” says Dan O’Shea, operations manager for Inside Quantum Technology, an industry publication. In October, U.S. President Joe Biden toured IBM’s quantum data center in Poughkeepsie, N.Y., calling quantum “vital to our economy and equally important to our national security.” In this new era of great-power competition, China and the U.S. are particularly hell-bent on conquering the technology lest they lose vital ground. “This technology is going to be the next industrial revolution,” says Tony Uttley, president and COO for Quantinuum, a Colorado-based firm that offers commercial quantum applications. “It’s like the beginning of the internet, or the beginning of classical computing.”

Whether we realize it or not, cryptography is the fundamental building block on which our digital lives are based. Without sufficient cryptography and the inherent trust that it engenders, every aspect of the digital human condition we know and rely on today would never have come to fruition much less continue to evolve at its current staggering pace. The internet, digital signatures, critical infrastructure, financial systems and even the remote work that helped the world limp along during the recent global pandemic all rely on one critical assumption – that the current encryption employed today is unbreakable by even the most powerful computers in existence. But what if that assumption was not only challenged but realistically compromised?

This is exactly what happened when Peter Shor proposed his algorithm in 1995, dubbed Shor’s Algorithm. The key to unlocking the encryption on which today’s digital security relies is in finding the prime factors of large integers. While factoring is relatively simple with small integers that have only a few digits, factoring integers that have thousands of digits or more is another matter altogether. Shor proposed a polynomial-time quantum algorithm to solve this factoring problem. I’ll leave it to the more qualified mathematicians to explain the theory behind this algorithm but suffice it to say that when coupled with a quantum computer, Shor’s Algorithm drastically reduces the time it would take to factor these larger integers by multiple orders of magnitude.

Prior to Shor’s Algorithm, for example, the most powerful computer today would take millions of years to find the prime factors of a 2048-bit composite integer. Without Shor’s algorithm, even quantum computers would take such an inordinate amount of time to accomplish the task as to render it unusable by bad actors. With Shor’s Algorithm, this same factoring can potentially be accomplished in a matter of hours.