Lifeboat Foundation

Echopraxia is a book set in one of the most interesting sci-fi universes that I have covered on this channel. It is technically a sequel to Blindsight, but it is not necessary that you read Blindsight to understand Echopraxia is set in the late 21 century. About 14 years after man’s first contact with alien life.

This book brings up one of the most interesting concepts I’ve ever encountered in any sci-fi book ever. And that is the concept of the “Digital Universe” and God as a Virus. Now this is a concept that comes from the field of digital physics, which keep in mind is all theoretical. It is based on the premise that the universe is pure mathematics at its base, every event that occurs can be thought of as a kind of computation. This could mean that the universe is a simulation, but that is not necessary for the idea to work.

Continue reading “Is God A Virus? | Echopraxia” »

OAKLAND, California, March 28 (Reuters) — Artificial intelligence chip startup Cerebras Systems on Tuesday said it released open source ChatGPT-like models for the research and business community to use for free in an effort to foster more collaboration.

Silicon Valley-based Cerebras released seven models all trained on its AI supercomputer called Andromeda, including smaller 111 million parameter language models to a larger 13 billion parameter model.

“There is a big movement to close what has been open sourced in AI…it’s not surprising as there’s now huge money in it,” said Andrew Feldman, founder and CEO of Cerebras. “The excitement in the community, the progress we’ve made, has been in large part because it’s been so open.”

I dunno if anyone has seen this. As a former Linux user, I’ve been an Nvidia fan for a long time and now they’ve gone on from games and Bitcoin mining. Sorry if this is a double post. I’m on my way out the door for my mom’s Dr appointment. I always worry I’ll double post by accident.

NVIDIA’s Jensen Huang just announced a set of revolutionary new Artificial Intelligence Models and Partnerships at GTC 2023. NVIDIA has always been one of, if not the most important company in the AI Industry by creating the most powerful AI hardware to date. Among them the A100 and future H100 GPU’s which are powering GPT-4 from OpenAI, Midjourney and everyone else. This gives them a lot of power to jump into the AI race themselves and allows them to surpass and beat the currently best AI models from Large Language Models and Image Generation with software like Omniverse and Hardware like the DGX H100 Supercomputer and Grace CPU’s.
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TIMESTAMPS:
00:00 NVIDIA enters the AI Industry.
01:43 GTC 2023 Announcements.
04:48 How NVIDIA Beat Every Competitor at AI
07:40 Running High End AI Locally.
10:20 What is NVIDIA’s Future?
13:05 Accelerating Future.
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Technology is improving at an almost exponential rate. Robots are learning to walk & think, Brain Computer Interfaces are becoming commonplace, new Biotechnology is allowing for age reversal and Artificial Intelligence is starting to surpass humans in many areas. Follow FutureNET to always be up to date on what is happening in the world of Futuristic Technology and Documentaries about humanities past achievements.
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#nvidia #ai #gtc

Year 2018 😗😁 Biological singularity here we come 💜 😌 💕

Building a computer out of the skeletons that hold our cells together could make them smaller and far more energy efficient.

Supercomputers and quantum computers are potent tools for handling difficult calculations, problem-solving, and data analysis. Although they both have the potential to transform computing technology, their speeds and capacities differ greatly.

Supercomputers quickly process massive volumes of data to provide a single result using a conventional computing strategy with numerous processors. These computers are the most powerful in terms of raw computing speed, but they can only do one task at a time, and Moore’s Law places a cap on how much data they can process (the principle that computer processor speeds double every two years).

Quantum computers, on the other hand, utilize laws of quantum mechanics to process information in ways that regular computers cannot, resulting in vastly higher processing speeds. They can manage several activities at once and take on challenging issues that would take supercomputer months to resolve. Yet, because of their great sensitivity to temperature fluctuations and need for isolation from outside influences, quantum computers require more upkeep than their conventional equivalents.

The “iPhone moment for A.I.” hype takes many hues, but Nvidia is about the future of computing itself. NVIDIA DGX supercomputers, originally used as an AI research instrument, are now running 24/7 at businesses across the world to refine data and process AI.

While OpenAI gets a lot of the glory, I believe the credit should go to Nvidia. Launched late last year, ChatGPT went mainstream almost instantaneously, attracting over 100 million users, making it the fastest-growing application in history. “We are at the iPhone moment of AI,” Huang said. Nvidia makes about $6 to $7 Billion a fiscal quarter in revenue.

Continue reading “The iPhone Moment of A.I. Has Started” »

At its annual GTC event, Nvidia announced a partnership with Tel Aviv-based Quantum Machines to create a state-of-the-art architecture for quantum-classical computing.

The collaboration intends to bring about purpose-built infrastructure for quantum computing and GPU supercomputing capable of real-time quantum error correction. Known as DGX Quantum, the first system is expected to deploy to the Israel Quantum Computing Center.

Chipmaker Nvidia has announced a new service that will allow users to access supercomputer level computing power from web browsers. The service, called Nvidia DGX Cloud, is an AI supercomputing service that allows enterprises to run workloads on the company’s A100 and H100 chips remotely.

“DGX Cloud provides dedicated clusters of NVIDIA DGX AI supercomputing, paired with NVIDIA AI software. The service makes it possible for every enterprise to access its own AI supercomputer using a simple web browser, removing the complexity of acquiring, deploying and managing on-premises infrastructure,” the company said in a blog post.

As reported by Reuters, however, the service isn’t cheap. Nvidia is charging $37,000 per month for access to eight of the A100 or H100 chips — the company’s flagship chips, which are both designed for AI computing. “Each instance of DGX Cloud features eight Nvidia H100 or A100 80GB Tensor Core GPUs for a total of 640GB of GPU memory per node. A high-performance, low-latency fabric built with Nvidia Networking ensures workloads can scale across clusters of interconnected systems, allowing multiple instances to act as one massive GPU to meet the performance requirements of advanced AI training,” Nvidia’s blog post explained.

The introduction of a novel idea of quantum computing in industrial applications is the result of the slow but steady progress of computing systems and equipment. Quantum computers, which are primarily used to aid in complex computations, are anticipated to significantly progress several industries and open up new prospects.

The promotion of IBM’s supercomputers is not far behind that of other tech behemoths like Google, who claim to have a better grasp on quantum dominance. What’s more crucial, though, is that enterprises and entire sectors will undoubtedly benefit from massive automation and digital transformation thanks to the industrial applications of quantum computing development. Quantum computing in 2023 offers countless opportunities. The world will eventually learn about the actual potential of quantum computing. With each passing day, the demand for effective processing grows, and it appears that the only option is to develop quantum applications. In this article, we have enlisted the top 10 industrial applications of quantum computing.