A new feature story out on book Transhuman Citizen:
A former presidential candidate who believes a dramatic increase in science funding can help humans achieve biological immortality has told Newsweek he is considering a third White House run in 2028.
Zoltan Istvan ran as an independent candidate during the 2016 presidential election when he attracted widespread media attention for driving a bus modified to look like a coffin from San Francisco to Washington D.C., to illustrate his believe that death can be overcome.
In 2019 he challenged Trump for the Republican presidential nomination using the campaign motto “Upgrading America,” in what he admitted was primarily a stunt to increase conservative interest in his ideas.
1/ Cloudflare analyzed the most active AI web crawlers on the Internet based on their query volume.
An analysis by Cloudflare shows that Bytespider, Amazonbot, and ClaudeBot are among the most active AI crawlers on the web.
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Over the past year, Cloudflare has analyzed which AI crawlers with known user agent strings have the highest request volume. Bytedance’s Bytespider crawler tops the list of most active AI web crawlers, followed by Amazonbot, ClaudeBot, and OpenAI’s GPTBot.
Grief-laden vitriol directed at AI fails to help us understand paths to better futures that are neither utopian nor dystopian, but open to radically weird possibilities.
Generative AI models have changed the way we create and consume content, particularly images and art. Diffusion models such as MidJourney and Stable Diffusion have been trained on large datasets of scraped images from online, many of which are copyrighted, private, or sensitive in subject matter. Many artists have discovered significant numbers of their art pieces in training data such as LAION-5B, without their knowledge, consent, credit or compensation.
To make it worse, many of these models are now used to copy individual artists, through a process called style mimicry. Home users can take art work from human artists, perform “fine-tuning” or LoRA on models like stable diffusion, and end up with a model that is capable of producing arbitrary images in the “style” of the target artist, when evoked with their name as a prompt. Popular independent artists find low quality facsimilies of their artwork online, often with their names still embedded in the metadata from model prompts.
Style mimicry produces a number of harmful outcomes that may not be obvious at first glance. For artists whose styles are intentionally copied, not only do they see loss in commissions and basic income, but low quality synthetic copies scattered online dilute their brand and reputation. Most importantly, artists associate their styles with their very identity. Seeing the artistic style they worked years to develop taken to create content without their consent or compensation is akin to identity theft. Finally, style mimicry and its impacts on successful artists have demoralized and disincentivized young aspiring artists. We have heard administrators at art schools and art teachers talking about plummeting student enrollment, and panicked parents concerned for the future of their aspiring artist children.
Tech companies, including Amazon Web Services, are striking deals with U.S. nuclear power plants to secure electricity for their data centers, driven by the skyrocketing demands of artificial intelligence. This move promises 24/7 carbon-free power but stirs controversy, as it could divert existing energy supplies, raise prices, and increase reliance on natural gas. These nuclear-powered data centers might accelerate the AI race, but they also spark debates over economic development, grid reliability, and climate goals. Could this be the future of tech or a risky gamble with unforeseen consequences?
As reported by WSJ, tech businesses searching the country for electrical supplies have focused on one important target: America’s nuclear power facilities.
The owners of about one-third of the United States’ nuclear power reactors are in negotiations with technology companies about providing electricity to new data centers needed to satisfy the needs of an artificial intelligence boom.
Chinese researchers have developed an open-source “brain-on-chip” interface system, which is the first of its kind in the world. The system can instruct a robot to avoid obstacles, track, and grasp through “mind control,” the Science and Technology Daily reported on Wednesday.
The interface system was co-developed by research teams from Tianjin University and Southern University of Science and Technology.
The system uses an artificial brain cultivated in vitro – such as a “brain-like organ,” which can interact with external information through encoding, decoding and stimulus-feedback when coupled with electrode chips, according to the report.
Terahertz technology has the potential to address the growing need for faster data transfer rates, but converting terahertz signals to various lower frequencies remains a challenge. Recently, Japanese researchers have devised a novel approach to both up-and down-convert terahertz signals within a waveguide. This is achieved by dynamically altering the waveguide’s conductivity using light, thereby creating a temporal boundary. Their breakthrough could lead to advancements in optoelectronics and improved telecommunications efficiency.
As we plunge deeper into the Information Age, the demand for faster data transmission keeps soaring, accentuated by fast progress in fields like deep learning and robotics. Against this backdrop, more and more scientists are exploring the potential of using terahertz waves to develop high-speed telecommunication technologies.
However, to use the terahertz band efficiently, we need frequency division multiplexing (FDM) techniques to transmit multiple signals simultaneously. Of course, being able to up-convert or down-convert the frequency of a terahertz signal to another arbitrary frequency is a logical prerequisite to FDM. This has unfortunately proven quite difficult with current technologies. The main issue is that terahertz waves are extremely high-frequency waves from the viewpoint of conventional electronics and very low-energy light in the context of optics, exceeding the capabilities of most devices and configurations across both fields. Therefore, a radically different approach will be needed to overcome current limitations.
