Lifeboat Foundation

“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.

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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.

‘This technology may be scaled to monitor the well-being of elderly people or just identify suspicious behaviours at home,’ scientists claim Scientists have figured out how to identify people in a building by using artificial intelligence to analyse WiFi signals. A team at Carnegie Mellon University developed a deep neural network to digitally map human bodies when in the presence of WiFi signals.

A chatbot powered by reams of data from the internet has passed exams at a US law school after writing essays on topics ranging from constitutional law to taxation and torts.

ChatGPT from OpenAI, a US company that this week got a massive injection of cash from Microsoft, uses artificial intelligence (AI) to generate streams of text from simple prompts.

The results have been so good that educators have warned it could lead to widespread cheating and even signal the end of traditional classroom teaching methods.

Machine learning can analyse how the signals from Wi-Fi transmitters are disrupted by human bodies to reveal what position people are sitting, standing or lying in.

Year 2012 The dwave quantum computers could essentially host the entire internet with low cost and even photonic room temperature quantum computers could eventually host the internet for even cheaper even down to pennies. Also if starling had casimir energy generators and casimir propulsion systems it could be even free for satellite operation costs with full automation we could essentially have low cost of pennies for the full system operation. At least some ideas for future operation costs.

This question was originally answered by Greg Price on Quora.