Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: nanotechnology – Page 2

Iron-based magnetic material achieves major reduction in core loss

A research team from NIMS, Tohoku University and AIST has developed a new technique for controlling the nanostructures and magnetic domain structures of iron-based soft amorphous ribbons, achieving more than a 50% reduction in core loss compared with the initial amorphous material.

The developed material exhibits particularly high performance in the high-frequency range of several tens of kilohertz—required for next-generation, high-frequency transformers and EV drive power supply circuits. This breakthrough is expected to contribute to the advancement of these technologies, development of more energy-efficient electric machines and progress toward carbon neutrality.

The research is published in Nature Communications.

Ultra-strong, lightweight metal composite can withstand extreme heat

University of Toronto researchers have designed a new composite material that is both very light and extremely strong—even at temperatures up to 500 Celsius.

The material, which is described in a paper published in Nature Communications, is made of various metallic alloys and nanoscale precipitates, and has a structure that mimics that of reinforced concrete—but on a microscopic scale.

These properties could make it extremely useful in aerospace and other high-performance industries.

The 2026 Timeline: AGI Arrival, Safety Concerns, Robotaxi Fleets & Hyperscaler Timelines | 221

The 2026 Timeline: AGI Arrival, Safety Concerns, Robotaxi Fleets & Hyperscaler Timelines ## The rapid advancement of AI and related technologies is expected to bring about a transformative turning point in human history by 2026, making traditional measures of economic growth, such as GDP, obsolete and requiring new metrics to track progress ## ## Questions to inspire discussion.

Measuring and Defining AGI

🤖 Q: How should we rigorously define and measure AGI capabilities? A: Use benchmarks to quantify specific capabilities rather than debating terminology, enabling clear communication about what AGI can actually do across multiple domains like marine biology, accounting, and art simultaneously.

🧠 Q: What makes AGI fundamentally different from human intelligence? A: AGI represents a complementary, orthogonal form of intelligence to human intelligence, not replicative, with potential to find cross-domain insights by combining expertise across fields humans typically can’t master simultaneously.

📊 Q: How can we measure AI self-awareness and moral status? A: Apply personhood benchmarks that quantify AI models’ self-awareness and requirements for moral treatment, with Opus 4.5 currently being state-of-the-art on these metrics for rigorous comparison across models.

AI Capabilities and Risks.

Continue reading “The 2026 Timeline: AGI Arrival, Safety Concerns, Robotaxi Fleets & Hyperscaler Timelines | 221” | >

How major nuclear protein complexes control specialized gene regulation in cancer and beyond

Precision and timing of gene expression is essential for normal biological functions and, when disrupted, can lead to many human diseases, including cancers. However, how molecular machines—protein complexes—that control gene expression locate to specific genes at specific times within the nuclei of our cells has remained a mystery.

Now, scientists at Dana-Farber Cancer Institute have discovered a new protein domain, SWIFT, found on a major chromatin remodeling complex family called mammalian SWI/SNF (mSWI/SNF or BAF) complexes, which helps these regulatory machines target particular genes to activate their expression.

The findings, published in Science, reveal how the SWIFT platform on mSWI/SNF complexes engage transcription factors (TF) to enable specialized cellular functions during both normal development and cancer. Particularly in human cancers, SWIFT-TF engagement sustains cancer-promoting gene expression and cell growth. Notably, breaking interactions with mutations halts cancer cell growth, flagging this new SWIFT-TF platform as a promising target for small molecule development.

Replication efforts suggest ‘smoking gun’ evidence isn’t enough to prove quantum computing claims

A group of scientists, including Sergey Frolov, professor of physics at the University of Pittsburgh, and co-authors from Minnesota and Grenoble have undertaken several replication studies centered around topological effects in nanoscale superconducting or semiconducting devices. This field is important because it can bring about topological quantum computing, a hypothetical way of storing and manipulating quantum information while protecting it against errors.

In all cases, they found alternative explanations of similar data. While the original papers claimed advances for quantum computing and made their way into top scientific journals, the individual follow-ups could not make it past the editors at those same journals.

Reasons given for its rejection included that, being a replication, it was not novel; that, after a couple of years, the field had moved on. But replications take time and effort and the experiments are resource-intensive and cannot happen overnight. And important science does not become irrelevant on the scale of years.

Quantum phenomenon enables a nanoscale mirror that can be switched on and off

Controlling light is an important technological challenge—not just at the large scale of optics in microscopes and telescopes, but also at the nanometer scale. Recently, physicists at the University of Amsterdam published a clever quantum trick that allows them to make a nanoscale mirror that can be turned on and off at will.

The work is published in the journal Light: Science & Applications.

Behind nature’s blueprints: Physicists create ‘theoretical rulebook’ of self-assembly

Inspired by biological systems, materials scientists have long sought to harness self-assembly to build nanomaterials. The challenge: the process seemed random and notoriously difficult to predict.

Now, researchers from the Institute of Science and Technology Austria (ISTA) and Brandeis University have uncovered geometric rules that act as a master control panel for self-assembling particles.

The results, which could find applications ranging from protein design to synthetic nanomachines, were published in Nature Physics.

AI-generated sensors open new paths for early cancer detection

Detecting cancer in the earliest stages could dramatically reduce cancer deaths because cancers are usually easier to treat when caught early. To help achieve that goal, MIT and Microsoft researchers are using artificial intelligence to design molecular sensors for early detection.

The researchers developed an AI model to design peptides (short proteins) that are targeted by enzymes called proteases, which are overactive in cancer cells. Nanoparticles coated with these peptides can act as sensors that give off a signal if cancer-linked proteases are present anywhere in the body.

Depending on which proteases are detected, doctors would be able to diagnose the particular type of cancer that is present. These signals could be detected using a simple urine test that could even be done at home.

/* */