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Elon Musk’s Space Exploration Technologies, the most highly valued private tech company in the U.S., has told some investors it expects to bring in about $8 billion in revenue in 2023, roughly doubling its revenue from the previous year, according to people familiar with the discussions.

The expectation for rapid growth helps explain the fervor of some investors for SpaceX shares, which have defied recently depressed private tech valuations. The company, valued in a secondary share sale at about $150 billion this month, has also assured investors it expects to pull in about $3 billion in operating profits this year, at least by a measure that excludes expenses tied to building rockets and satellites.

Queen Mary University researchers have engineered a self-sensing, variable-stiffness artificial muscle that mimics natural muscle characteristics. The breakthrough has significant implications for soft robotics and medical applications, moving a step closer to human-machine integration.

In a study published on July 8 in Advanced Intelligent Systems, researchers from Queen Mary University of London have made significant advancements in the field of bionics with the development of a new type of electric variable-stiffness artificial muscle that possesses self-sensing capabilities. This innovative technology has the potential to revolutionize soft robotics and medical applications.

Technology Inspired by Nature.

Experts from CERN, DESY, IBM Quantum and others have published a white paper identifying activities in particle physics that could benefit from the application of quantum-computing technologies.

Last week, researchers published an important identifying activities in where burgeoning technologies could be applied. The paper, authored by experts from CERN, DESY, IBM Quantum and over 30 other organizations, is now available as a preprint on arXiv.

With quantum-computing technologies rapidly improving, the paper sets out where they could be applied within particle physics in order to help tackle computing challenges related not only to the Large Hadron Collider’s ambitious upgrade program, but also to other colliders and low-energy experiments worldwide.

Brushing twice a day keeps the dentist away—but can we improve on the toothpaste we use to maintain clean teeth, preventing medical issues that spiral from poor dental health? Most toothpastes use fluoride, a powerful tool for oral hygiene. However, fluoride can pose health problems in some cases, especially for children who consume too much fluoride by swallowing most of their toothpaste: children normally use only a tiny dose of toothpaste to avoid these problems, but that reduces toothbrushing efficacy.

In the search for alternatives, a team of international scientists and Polish clinicians have identified a hydroxyapatite toothpaste that works just as well as fluoride toothpaste to protect against cavities.

“Hydroxyapatite is a safe and effective alternative to fluoride in caries prevention for daily use,” said Professor Elzbieta Paszynska of the Poznan University of Medical Sciences, co-principal investigator and corresponding author of the study published in Frontiers in Public Health.

Im still in the 2029 camp. But if it happens soon would be great. And, i still project ASI 5 years after arrival of Agi.


The online forecasting community Metaculus currently predicts that there will be a weak human-like AI in January 2026. This is about 25 years earlier than the early 2020 prediction.

Metaculus is a forecasting platform and community focused on compiling and refining predictions about various events, scientific advances, technological breakthroughs, and other topics. Participants submit their predictions to questions posed on the platform, and these predictions are combined into a consensus forecast.

Metaculus uses a scoring system to incentivize accurate predictions and to track participants’ performance over time. This motivates them to revisit and update their forecasts as new information becomes available. The platform is open to anyone who wants to participate.

Shortly after resigning as CEO of Twitter, Musk is expected to assume the position of CEO once again, this time at a fresh AI startup.

The world’s richest person has announced a new startup called xAI. Elon Musk has assembled a team of highly experienced professionals in the realm of artificial intelligence (AI) to establish this enterprise. However, Musk’s Twitter statement merely offers limited information about the venture’s objectives, leaving its purpose ambiguous for the time being.

Musk’s recent foray into AI is not his initial involvement in the field. In 2015, he became an investor in OpenAI, a non-profit research laboratory dedicated to AI exploration. However, over time, Musk… More.


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July 17 — Around a decade after virtual assistants like Siri and Alexa burst onto the scene, a new wave of AI helpers with greater autonomy is raising the stakes, powered by the latest version of the technology behind ChatGPT and its rivals.

Experimental systems that run on GPT-4 or similar models are attracting billions of dollars of investment as Silicon Valley competes to capitalize on the advances in AI. The new assistants — often called “agents” or “copilots” — promise to perform more complex personal and work tasks when commanded to by a human, without needing close supervision.

“High level, we want this to become something like your personal AI friend,” said developer Div Garg, whose company MultiOn is beta-testing an AI agent.

Artificial Intelligence (AI) has transformed our world at an astounding pace. It’s like a vast ocean, and we’re just beginning to navigate its depths.

To appreciate its complexity, let’s embark on a journey through the seven distinct stages of AI, from its simplest forms to the mind-boggling prospects of superintelligence and singularity.

Picture playing chess against a computer. Every move it makes, every strategy it deploys, is governed by a predefined set of rules, its algorithm. This is the earliest stage of AI — rule-based systems. They are excellent at tasks with clear-cut rules, like diagnosing mechanical issues or processing tax forms. But their capacity to learn or adapt is nonexistent, and their decisions are only as good as the rules they’ve been given.