Ukrainian President Volodymyr Zelenskyy weighed in Saturday on the U.S. capture of former Venezuelan leader Nicolás Maduro, telling reporters that Washington "knows what to do next."

Zelenskyy was speaking to reporters in Kyiv after meeting with national security advisors from member states of the Coalition of the Willing when he was asked about the stunning U.S. military operation that unfolded in the early morning hours in Caracas.

"Regarding Venezuela? How should we respond to this?" Zelenskyy asked in Ukrainian. "Well, what can I say is, if you can do that with dictators, then the United States knows what to do next," he said with a smile.

U.S. forces took Maduro and his wife, Cilia Flores, from their compound, where they were boarded onto the USS Iwo Jima and flown to New York to face federal charges.

TRUMP CASTS MADURO’S OUSTER AS ‘SMART’ MOVE AS RUSSIA, CHINA ENTER THE FRAY

Russia’s Ministry of Foreign Affairs denounced the capture of Maduro and his wife, urging the Trump administration to release the "legitimately elected president of a sovereign country and his spouse."

In a superseding indictment released Saturday by Attorney General Pam Bondi, Maduro is charged with leading a narco-terrorism conspiracy tied to large-scale cocaine trafficking into the United States, along with related drug importation and weapons offenses.

Flores is also charged in the same indictment with participating in a decades-long cocaine trafficking conspiracy and related firearms offenses.

The charges build on prior indictments from 2020.

NYC MAYOR STRONGLY CONDEMNS TRUMP'S CAPTURE OF VENEZUELAN LEADER MADURO AS 'ACT OF WAR'

Chairman of the Joint Chiefs Gen. Dan Caine said the mission, dubbed "Operation Absolute Resolve," involved more than 150 aircraft and a coordinated effort by the U.S. military, intelligence agencies, and law enforcement to apprehend the duo.

"This operation is a testament to the dedication and unwavering commitment to justice and our resolve to hold accountable those who threaten peace and stability," he said at a Mar-a-Lago press conference alongside President Donald Trump and other Cabinet officials.

MADURO’S FALL SPARKS SUSPICION OF BETRAYAL INSIDE VENEZUELA’S RULING ELITE

Trump told reporters he never spoke with Russian President Vladimir Putin about Maduro. 

"I'm not thrilled with Putin. He's killing too many people," the president said when asked whether he was upset at the Russian leader.

Moscow has continued pounding Kyiv with large-scale drone and missile attacks as the Trump administration works to secure a potential peace agreement to end the nearly four-year war.

"Russia has not shown a genuine willingness to pursue peace. Instead, it continues its aggressive war, violence, and destabilization, using negotiations as a tactic to buy time,"  Zelenskyy said during the Coalition of the Willing meeting, according to a statement from his office. "It employs provocations and manipulations to derail progress in the peace process,"

The Associated Press contributed to this report.

Most robot headlines follow a familiar script: a machine masters one narrow trick in a controlled lab, then comes the bold promise that everything is about to change. I usually tune those stories out. We have heard about robots taking over since science fiction began, yet real-life robots still struggle with basic flexibility. This time felt different.

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ELON MUSK TEASES A FUTURE RUN BY ROBOTS

A new report published in Science Robotics caught our attention because the results feel genuinely meaningful, impressive and a little unsettling in the best way. The research comes from a team of academic scientists working in robotics and artificial intelligence, and it tackles one of the field's biggest limitations.

The researchers taught a robot to learn 1,000 different physical tasks in a single day using just one demonstration per task. These were not small variations of the same movement. The tasks included placing, folding, inserting, gripping and manipulating everyday objects in the real world. For robotics, that is a big deal.

Until now, teaching robots physical tasks has been painfully inefficient. Even simple actions often require hundreds or thousands of demonstrations. Engineers must collect massive datasets and fine-tune systems behind the scenes. That is why most factory robots repeat one motion endlessly and fail as soon as conditions change. Humans learn differently. If someone shows you how to do something once or twice, you can usually figure it out. That gap between human learning and robot learning has held robotics back for decades. This research aims to close that gap.

THE NEW ROBOT THAT COULD MAKE CHORES A THING OF THE PAST

The breakthrough comes from a smarter way of teaching robots to learn from demonstrations. Instead of memorizing entire movements, the system breaks tasks into simpler phases. One phase focuses on aligning with the object, and the other handles the interaction itself. This method relies on artificial intelligence, specifically an AI technique called imitation learning that allows robots to learn physical tasks from human demonstrations.

The robot then reuses knowledge from previous tasks and applies it to new ones. This retrieval-based approach allows the system to generalize rather than start from scratch each time. Using this method, called Multi-Task Trajectory Transfer, the researchers trained a real robot arm on 1,000 distinct everyday tasks in under 24 hours of human demonstration time.

Importantly, this was not done in a simulation. It happened in the real world, with real objects, real mistakes and real constraints. That detail matters.

Many robotics papers look impressive on paper but fall apart outside perfect lab conditions. This one stands out because it tested the system through thousands of real-world rollouts. The robot also showed it could handle new object instances it had never seen before. That ability to generalize is what robots have been missing. It is the difference between a machine that repeats and one that adapts.

AI VIDEO TECH FAST-TRACKS HUMANOID ROBOT TRAINING

This research addresses one of the biggest bottlenecks in robotics: inefficient learning from demonstrations. By decomposing tasks and reusing knowledge, the system achieved an order of magnitude improvement in data efficiency compared to traditional approaches. That kind of leap rarely happens overnight. It suggests that the robot-filled future we have talked about for years may be nearer than it looked even a few years ago.

Faster learning changes everything. If robots need less data and less programming, they become cheaper and more flexible. That opens the door to robots working outside tightly controlled environments.

In the long run, this could enable home robots to learn new tasks from simple demonstrations instead of specialist code. It also has major implications for healthcare, logistics and manufacturing.

More broadly, it signals a shift in artificial intelligence. We are moving away from flashy tricks and toward systems that learn in more human-like ways. Not smarter than people. Just closer to how we actually operate day to day.

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Robots learning 1,000 tasks in a day does not mean your house will have a humanoid helper tomorrow. Still, it represents real progress on a problem that has limited robotics for decades. When machines start learning more like humans, the conversation changes. The question shifts from what robots can repeat to what they can adapt to next. That shift is worth paying attention to.

If robots can now learn like us, what tasks would you actually trust one to handle in your own life? Let us know by writing to us at Cyberguy.com

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