Summary

About

Emerging Technology Observatory

The Emerging Technology Observatory creates free, high-quality data resources to inform critical decisions on emerging technology issues.

Making sense of the often overwhelming world of emerging tech with data-driven tools and resources.
There has never been more information available on global science and technology. Cutting-edge research and innovation are unfolding around the world, in universities, governments, large corporations, startups, nonprofits, and many other venues. This diverse, global enterprise generates data in equally diverse forms, from articles and patents to social media, open-access databases, financial transactions, news, job postings, and beyond.

In theory, all of this data could drive better-informed decisions on emerging technology issues––but in practice, it’s usually just too overwhelming. Accessing, organizing, and making sense of emerging technology data takes hard work and specialized resources, from data science and software engineering to open-source collection and quality control. Even the biggest, wealthiest organizations may not be up to the task.

Source: Emerging Technology Observatory

Digital Technologies

‘Mind-reading’ AI: Japan study sparks ethical debate

Source: Al Jazeera

Osaka University researchers have used AI to decode subjects’ brain activity to create images of what they are seeing.

Tokyo, Japan – Yu Takagi could not believe his eyes. Sitting alone at his desk on a Saturday afternoon in September, he watched in awe as artificial intelligence decoded a subject’s brain activity to create images of what he was seeing on a screen.

“I still remember when I saw the first [AI-generated] images,” Takagi, a 34-year-old neuroscientist and assistant professor at Osaka University, told Al Jazeera.

“I went into the bathroom and looked at myself in the mirror and saw my face, and thought, ‘Okay, that’s normal. Maybe I’m not going crazy’”.

Takagi and his team used Stable Diffusion (SD), a deep learning AI model developed in Germany in 2022, to analyse the brain scans of test subjects shown up to 10,000 images while inside an MRI machine.

Q-Day Is Coming Sooner Than We Think

Source: Forbes

“Q-Day” is the term some experts use to describe when large-scale quantum computers are able to factorize the large prime numbers that underlie our public encryption systems, such as the ones that are supposed to protect our bank accounts, financial markets, and most vital infrastructure. That’s a feat that’s all but impossible for even the fastest supercomputers but which the unique features of quantum computers, using the physics of superpositioning and entanglement, will be able to deliver.

There’s a growing consensus that this quantum threat is real; there’s no agreement how long it will take before a quantum computer has the 4000 or so stable qubits it will need to meet the requirements of Shor’s algorithm for cracking those encryption systems.

For example, it would take a classical computer 300 trillion years to crack an RSA-2048 bit encryption key. A quantum computer can do the same job in just ten seconds with 4099 stable qubits—but getting to that number is the main problem quantum computer engineers face since the stability or coherence of qubits lasts only for microseconds. Today’s most entangled computer, Google’sGOOG +0.4% Bristlecone, has just 72 stable qubits.

Space Technologies

Machine learning helps find other Earths

Source: SciWorthy

Astronomers used an algorithm on stars with known exoplanets to identify 44 systems with potential Earth-like planets, 8 of which they considered highly probable.

Astronomers are interested in finding planets of a similar size, composition, and temperature to Earth, also called Earth-like planets. However, there are challenges in this endeavor. Small, rocky planets are difficult to find because current planet-hunting methods are biased towards gas giants. Also, for a planet to be similar in temperature to Earth, it has to orbit a comparable distance from its host star, similar to Earth orbiting the Sun, which means it takes approximately a year to go around its star. This creates another problem for astronomers trying to find these planets, since searching for an Earth-like planet around just one star would involve dedicating a telescope to monitor it constantly for more than a year.

To save time spent operating telescopes, scientists need a new way to find stars that are good candidates for thorough searches before dedicating resources to observing them. One team of astronomers investigated whether observable properties of planetary systems could indicate the presence of Earth-like planets. They found that the arrangement of known planets in the system and the mass, radius, and distance from its closest planet to its star could be used to predict the occurrence of an Earth-like planet.

Then, the team tested how well machine learning could handle this task. They started by creating a sample set of planetary systems with and without Earth-like planets. Astronomers have only found around 5,000 stars in the sky with an orbiting exoplanet, which makes the sample size too small to train machine learning programs. So, the team generated 3 sets of planetary systems using a computational framework that simulates how planets form, called the Bern model.

Health Technologies

A historic milestone: Two people communicate in dreams

Source: Tech Explorist

Participants successfully exchanged information through lucid dreams.

Lucid dreams occur when a person is aware they are dreaming while still in the dream state. This phenomenon happens during REM sleep and has numerous potential applications, from solving physiological problems to learning new skills.

Researchers at REMspace, a startup in California, have made an important discovery: lucid dreams might help people communicate in new ways. They used special equipment to help two people enter lucid dreams and send a simple message to each other.

Earlier, REMspace showed that sensors could pick up specific sounds made during dreams. This led to the creation of Remmyo, a special dream language detected by sensitive sensors.