Technology

PRETTY FANCY SHOWER CURTAIN RINGS:

Counter-drone tech is gaining major traction (Stephen Bryen, June 15, 2026, Asia Times)

The Ukrainian solution that has gained the most attention is called Sting. It was developed in Ukraine by a volunteer engineering group called Wild Hornets.

It is a bullet-shaped 3-D printed aerodynamic frame featuring a pursuit speed of 213 mph (343 km/h) and a service ceiling of around 10,000 feet (3,000 meters). Its operational radius is about 20 kilometers (12.4 miles). It is equipped with a home-built thermal imaging camera so it can take down enemy drones at night.

The Sting interceptor costs US$2,100. Ukraine has developed several specialized interceptor brigades (e.g., the 412th Nemesis Brigade), which claim a 95% success rate. The system is operated by a pilot, but the latest versions feature autonomous interception using an automation layer in the Sting software.

The AI computer vision module can lock onto the silhouette of an enemy drone, such as the Geran 2, and navigate autonomously relieving the pilot of target responsibility.

Ukraine uses a system called Hornet Vision, a remote control architecture, meaning the pilot/operators can be far away from the front line, so the Russians cannot target them easily.

Ukraine has a number of advantages over the Russians. It has remote operators/pilots who are good at what they do. It can locally source important drone components, especially thermal imagers. It has talented software engineers with high motivation. And it has considerable battlefield experience.

PAYING NO COST TO BE THE BOSS:

Autonomous Corsair maritime drone rescues US military pilots after crash near Oman (Brandi Vincent, June 9, 2026, Defense Scoop)

“The surface drone that assisted in last night’s rescue of the Apache crew off the coast of Oman was a U.S. Navy Corsair unmanned surface vessel operated by U.S. 5th Fleet’s Task Force 59,” Hawkins said.

In that rescue operation, he told DefenseScoop, the maritime drone picked the two pilots up “and transported them to another location on the water where they were then hoisted up to a helicopter for further transport.”

The Corsair is a 24-foot autonomous surface vessel (ASV) that’s designed for rugged, long-duration missions. The drones can operate at speeds greater than 35 knots and carry up to 1,000 lbs over 1,000 nautical miles, according to Saronic’s product specifications.

ABOVE AVERAGE IS OVER:

A Florida hospital is using Palantir to catch sepsis earlier, it’s saved 866 lives so far (Skye Jacobs, June 10, 2026, Techspot)

The system is estimated to have helped save 886 lives since August 2022. Sepsis is notoriously difficult to catch early. It can begin with small shifts in vital signs that do not immediately stand out – slight increases in heart rate, minor temperature changes, subtle indicators that can easily be lost in the noise of a busy hospital floor. Once it takes hold, though, it can escalate quickly, triggering organ failure and, in many cases, death. Roughly one in five patients diagnosed with sepsis does not survive.

The approach at Tampa General is built around catching early signals before they develop into a crisis. The hospital partnered with Palantir to use its Foundry platform alongside existing clinical systems.

The result is a continuous stream of aggregated data pulled from electronic health records, lab results, clinician notes and bedside monitors. Instead of sitting in separate systems, that data is unified and presented in real time through a centralized dashboard that tracks roughly 1,000 patients at once.

ABOVE AVERAGE IS OVER:

LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation of Likert Ratings (Benjamin F. Maier, Ulf Aslak, Luca Fiaschi, Nina Rismal, Kemble Fletcher, Christian C. Luhmann, Robbie Dow, Kli Pappas, Thomas V. Wiecki, 10/27/25, arxiv)

Consumer research costs companies billions annually yet suffers from panel biases and limited scale. Large language models (LLMs) offer an alternative by simulating synthetic consumers, but produce unrealistic response distributions when asked directly for numerical ratings. We present semantic similarity rating (SSR), a method that elicits textual responses from LLMs and maps these to Likert distributions using embedding similarity to reference statements. Testing on an extensive dataset comprising 57 personal care product surveys conducted by a leading corporation in that market (9,300 human responses), SSR achieves 90% of human test-retest reliability while maintaining realistic response distributions (KS similarity > 0.85). Additionally, these synthetic respondents provide rich qualitative feedback explaining their ratings. This framework enables scalable consumer research simulations while preserving traditional survey metrics and interpretability.

It’s not that AI, robotics, etc. will replace a few jobs but that it will make entire classes of employment superfluous.