Lifeboat Foundation

“Learn to code.” That three-word pejorative is perpetually on the lips and at the fingertips of internet trolls and tech bros whenever media layoffs are announced. A useless sentiment in its own right, but with the recent advent of code generating AIs, knowing the ins and outs of a programming language like Python could soon be about as useful as knowing how to fluently speak a dead language like Sanskrit. In fact, these genAIs are already helping professional software developers code faster and more effectively by handling much of the programming grunt work.

Two of today’s most widely distributed and written coding languages are Java and Python. The former almost single handedly revolutionized cross-platform operation when it was released in the mid-’90s and now drives “everything from smartcards to space vehicles,” as Java Magazine put it in 2020 — not to mention Wikipedia’s search function and all of Minecraft. The latter actually predates Java by a few years and serves as the code basis for many modern apps like Dropbox, Spotify and Instagram.

They differ significantly in their operation in that Java needs to be compiled (having its human-readable code translated into computer-executable machine code) before it can run. Python, meanwhile, is an interpreted language, which means that its human code is converted into machine code line-by-line as the program executes, enabling it to run without first being compiled. The interpretation method allows code to be more easily written for multiple platforms while compiled code tends to be focused to a specific processor type. Regardless of how they run, the actual code-writing process is nearly identical between the two: Somebody has to sit down, crack open a text editor or Integrated Development Environment (IDE) and actually write out all those lines of instruction. And until recently, that somebody typically was a human.

NASA and other space agencies have captured vivid images of galaxies, planets, moons, stars, and beyond in 2023. Here are some of the most stunning cosmic photos, so far.

If those two examples didn’t make you feel like an underachiever, we now have news of yet another child prodigy. AP reported on Alena Wicker, a 12-year-old who has been accepted to Arizona State University (ASU) and who aims to become a NASA engineer by age 16.

Researchers have created synthetic human embryos using stem cells, according to media reports. Remarkably, these embryos have reportedly been created from embryonic stem cells, meaning they do not require sperm and ova.

This development, widely described as a breakthrough that could help scientists learn more about human development and genetic disorders, was revealed this week in Boston at the annual meeting of the International Society for Stem Cell Research.

The research, announced by Professor Magdalena Żernicka-Goetz of the University of Cambridge and the California Institute of Technology, has not yet been published in a peer-reviewed journal. But Żernicka-Goetz told the meeting these human-like embryos had been made by reprogramming human embryonic stem cells.

In an effort to explain the accelerating expansion of the universe as well as the nature of Dark Matter, researchers have zeroed in on an upcoming set of experiments designed to measure time dilation.

According to the researchers behind the pioneering approach, these time dilation experiments should either add support to Albert Einstein’s theory of general relativity and the theories of Leonhard Euler regarding the movement of celestial objects or open the door to a whole new understanding of time and matter.

Einstein and Euler Still Unable to Fully Explain Dark Matter and the Expanding Universe.

Researchers have discovered that senescent pigment cells in skin moles can stimulate robust hair growth, challenging the belief that these cells impede regeneration. The study showed that molecules osteopontin and CD44 play a key role in this process, potentially opening new avenues for therapies for common hair loss conditions.

The process by which aged, or senescent, pigment-making cells in the skin cause significant growth of hair inside skin moles, called nevi, has been identified by a research team led by the University of California, Irvine. The discovery may offer a road map for an entirely new generation of molecular therapies for androgenetic alopecia, a common form of hair loss in both women and men.

The study, published on June 21 in the journal Nature, describes the essential role that the osteopontin and CD44 molecules play in activating hair growth inside hairy skin nevi. These skin nevi accumulate particularly large numbers of senescent pigment cells and yet display very robust hair growth.

Loughborough University scientists are the first to demonstrate that a terahertz wave camera can capture 3D images of microscopic items hidden inside small objects.

Lead researcher Dr. Luana Olivieri says though the research is in the early stages, the team’s latest study could have “major implications for a range of fields with relevance in cancer screenings, security, and materials research.”

The research, which is in collaboration with Professor Marco Peccianti, Dr. Luke Peters, Dr. Juan S. Totero and a team of experts from the Emergent Photonics Research Center (EPicX), demonstrates that terahertz waves can be used to locate and recognize embedded objects and features, such as cracks and bubbles, in microscopic three-dimensional space. The study has been published in the journal ACS Photonics and is featured on the front cover of the latest issue, published today (June 21).

Experts warned that AI’s autonomy is just a “veneer,” and that it’s being used as surveillance through the scraped data it needs to train on.

Machine sentience is overrated.