share.google/aimode/Y1ymWuwr…
Ukraine’s recent drone attacks deep inside Russia: Were the drones secretly prepared and hidden ahead of the attacks or flew from Ukraine at the time of the attacks?
ahead of time and launched them from within the country. Other attacks have been carried out by new Ukrainian-made long-range drones flying directly from Ukrainian territory.
For some drone attacks deep inside Russia,
Ukraine secretly smuggled the drones into Russia
Drones launched from within Russia
In a major, coordinated attack on Russian airbases on June 1, 2025, Ukraine used drones that had been pre-staged inside Russian territory.
Operation Spiderweb: This covert operation, conducted by Ukraine’s Security Service (SBU), involved secretly moving drones into Russia over several months.
Method of transport: The drones were concealed in special wooden containers with remotely controlled lids and transported on trucks.
Launch and targets: When the time came, the trucks parked near Russian airbases. The lids of the containers opened remotely, and the drones were launched for short-distance strikes. This allowed strikes on targets in Siberia and the Arctic region, thousands of kilometers from the Ukrainian border.
Long-range drones flying from Ukraine
Ukraine has also developed a range of drones capable of reaching targets deep inside Russia without needing to be hidden beforehand. A key figure in Ukraine’s drone program stated in October 2025 that their drones are flying distances of up to 2,000 kilometers (1,242 miles) to strike Russian oil facilities.
Examples of long-range drones flying from Ukraine:
FP-1: This drone, developed by a Ukrainian startup, can reportedly travel up to 1,600 kilometers (994 miles) and is credited with 60% of Ukraine’s deep strikes inside Russia as of August 2025.
“Beaver” drones: This model has a reported range of 1,000 kilometers (620 miles) and has been used to attack Moscow and other locations.
AI-powered drone: In October 2025, reports indicated that Ukraine was using an AI-powered strike drone called the ARM 20, capable of flying 1,600 kilometers to its target.
Why Ukraine uses both methods
These two different approaches are used to overcome different challenges and exploit vulnerabilities in Russia’s defense systems.
Internal launches: By launching from inside Russia, drones can evade long-range radar detection and other air defense systems. This tactic relies on secrecy and surprise to attack targets that would otherwise be out of reach.
External long-range launches: By advancing drone technology, Ukraine can hit strategic targets from its own territory. This approach is more sustainable and avoids the complex logistics of smuggling materials and operatives across enemy lines.— Michael Novakhov (@mikenov) Oct 25, 2025
Day: October 25, 2025
share.google/aimode/Y1ymWuwr…
Ukraine’s recent drone attacks deep inside Russia: Were the drones secretly prepared and hidden ahead of the attacks or flew from Ukraine at the time of the attacks?
ahead of time and launched them from within the country. Other attacks have been carried out by new Ukrainian-made long-range drones flying directly from Ukrainian territory.
For some drone attacks deep inside Russia,
Ukraine secretly smuggled the drones into Russia
Drones launched from within Russia
In a major, coordinated attack on Russian airbases on June 1, 2025, Ukraine used drones that had been pre-staged inside Russian territory.
Operation Spiderweb: This covert operation, conducted by Ukraine’s Security Service (SBU), involved secretly moving drones into Russia over several months.
Method of transport: The drones were concealed in special wooden containers with remotely controlled lids and transported on trucks.
Launch and targets: When the time came, the trucks parked near Russian airbases. The lids of the containers opened remotely, and the drones were launched for short-distance strikes. This allowed strikes on targets in Siberia and the Arctic region, thousands of kilometers from the Ukrainian border.
Long-range drones flying from Ukraine
Ukraine has also developed a range of drones capable of reaching targets deep inside Russia without needing to be hidden beforehand. A key figure in Ukraine’s drone program stated in October 2025 that their drones are flying distances of up to 2,000 kilometers (1,242 miles) to strike Russian oil facilities.
Examples of long-range drones flying from Ukraine:
FP-1: This drone, developed by a Ukrainian startup, can reportedly travel up to 1,600 kilometers (994 miles) and is credited with 60% of Ukraine’s deep strikes inside Russia as of August 2025.
“Beaver” drones: This model has a reported range of 1,000 kilometers (620 miles) and has been used to attack Moscow and other locations.
AI-powered drone: In October 2025, reports indicated that Ukraine was using an AI-powered strike drone called the ARM 20, capable of flying 1,600 kilometers to its target.
Why Ukraine uses both methods
These two different approaches are used to overcome different challenges and exploit vulnerabilities in Russia’s defense systems.
Internal launches: By launching from inside Russia, drones can evade long-range radar detection and other air defense systems. This tactic relies on secrecy and surprise to attack targets that would otherwise be out of reach.
External long-range launches: By advancing drone technology, Ukraine can hit strategic targets from its own territory. This approach is more sustainable and avoids the complex logistics of smuggling materials and operatives across enemy lines.— Michael Novakhov (@mikenov) Oct 25, 2025
Ukraine’s drone attacks deep inside Russia: Were the drones secretly prepared and hidden ahead of the attacks or flew from Ukraine at the time of the attacks? – Google Search google.com/search?q=Ukraine%…
— Michael Novakhov (@mikenov) Oct 25, 2025
AI and Medicine: Doctors are beginning to use AI as a tool – Google Search google.com/search?q=AI+and+M…
Yes, doctors are increasingly using AI as a tool, with a 78% increase in AI usage by physicians between 2023 and 2024. The most common applications are to reduce administrative burdens, such as using “AI scribes” to document patient visits and create notes, and in diagnostic assistance for tasks like interpreting medical images. Other uses include generating discharge instructions and providing decision support. [1, 2, 3, 4, 5]
Key AI applications in medicineAdministrative tasks: AI is being used to automate paperwork, which saves physicians time and helps prevent burnout.
AI scribes: These tools listen to patient-doctor conversations, automatically transcribe them, and create draft clinical notes, freeing up doctors to focus on the patient.
Other documentation: AI also helps generate discharge instructions, care plans, and other necessary documentation.Diagnostic assistance: AI algorithms help physicians analyze medical data to improve diagnostic accuracy.
Image analysis: AI can help interpret medical images like X-rays, MRIs, EKGs, and CAT scans, and can be trained to detect anomalies, such as polyps during colonoscopies.
Decision support: AI provides physicians with more information to help them make informed decisions.
Treatment recommendations: AI can help identify the best medicine for a specific patient’s case.
Risk prediction: AI can predict adverse clinical outcomes.Patient communication: AI can improve the patient experience.
Personalized communication: Doctors can use AI to write letters to patients.
Translation services: AI can also be used for translation during appointments. [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]Benefits and concerns
Benefits:
Reduced administrative burden: Frees up significant time for physicians.
Improved patient interaction: Allows doctors to have more face-to-face time with patients.
Enhanced accuracy: Supports diagnostic accuracy and decision-making.
Reduced burnout: Mitigates the cognitive and manual burden on clinicians.Concerns:
Reliability and accuracy: Some worry about the potential for AI to make mistakes or provide incorrect conclusions.
Privacy and security: Confidentiality of patient data is a concern.
Skill degradation: Some studies suggest that over-reliance on AI could lead to a decline in certain clinical skills.
Bias: There are concerns that AI could exacerbate existing biases. [1, 4, 5, 6, 7, 8, 9, 10]AI responses may include mistakes.
[1] youtube.com/watch?v=cdiD5Hkz…
[2] youtube.com/watch?v=rfMr35T4…
[3] ama-assn.org/practice-manage…
[4] ama-assn.org/practice-manage…
[5] learn.hms.harvard.edu/insigh…
[6] npr.org/sections/shots-healt…
[7] ama-assn.org/practice-manage…
[8] ama-assn.org/practice-manage…
[9] cedars-sinai.org/blog/what-y…
[10] ama-assn.org/practice-manage…
[11] ama-assn.org/practice-manage…— Michael Novakhov (@mikenov) Oct 25, 2025
AI and Medicine: Doctors are beginning to use AI as a tool – Google Search google.com/search?q=AI+and+M…
Yes, doctors are increasingly using AI as a tool, with a 78% increase in AI usage by physicians between 2023 and 2024. The most common applications are to reduce administrative burdens, such as using “AI scribes” to document patient visits and create notes, and in diagnostic assistance for tasks like interpreting medical images. Other uses include generating discharge instructions and providing decision support. [1, 2, 3, 4, 5]
Key AI applications in medicineAdministrative tasks: AI is being used to automate paperwork, which saves physicians time and helps prevent burnout.
AI scribes: These tools listen to patient-doctor conversations, automatically transcribe them, and create draft clinical notes, freeing up doctors to focus on the patient.
Other documentation: AI also helps generate discharge instructions, care plans, and other necessary documentation.Diagnostic assistance: AI algorithms help physicians analyze medical data to improve diagnostic accuracy.
Image analysis: AI can help interpret medical images like X-rays, MRIs, EKGs, and CAT scans, and can be trained to detect anomalies, such as polyps during colonoscopies.
Decision support: AI provides physicians with more information to help them make informed decisions.
Treatment recommendations: AI can help identify the best medicine for a specific patient’s case.
Risk prediction: AI can predict adverse clinical outcomes.Patient communication: AI can improve the patient experience.
Personalized communication: Doctors can use AI to write letters to patients.
Translation services: AI can also be used for translation during appointments. [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]Benefits and concerns
Benefits:
Reduced administrative burden: Frees up significant time for physicians.
Improved patient interaction: Allows doctors to have more face-to-face time with patients.
Enhanced accuracy: Supports diagnostic accuracy and decision-making.
Reduced burnout: Mitigates the cognitive and manual burden on clinicians.Concerns:
Reliability and accuracy: Some worry about the potential for AI to make mistakes or provide incorrect conclusions.
Privacy and security: Confidentiality of patient data is a concern.
Skill degradation: Some studies suggest that over-reliance on AI could lead to a decline in certain clinical skills.
Bias: There are concerns that AI could exacerbate existing biases. [1, 4, 5, 6, 7, 8, 9, 10]AI responses may include mistakes.
[1] youtube.com/watch?v=cdiD5Hkz…
[2] youtube.com/watch?v=rfMr35T4…
[3] ama-assn.org/practice-manage…
[4] ama-assn.org/practice-manage…
[5] learn.hms.harvard.edu/insigh…
[6] npr.org/sections/shots-healt…
[7] ama-assn.org/practice-manage…
[8] ama-assn.org/practice-manage…
[9] cedars-sinai.org/blog/what-y…
[10] ama-assn.org/practice-manage…
[11] ama-assn.org/practice-manage…— Michael Novakhov (@mikenov) Oct 25, 2025
The Brooklyn Nets fell 131-124 to Cleveland despite a late fourth-quarter surge on Friday night in what was their home opener of the 2025-26 season at Barclays Center.
Cam Thomas led the Nets (0-2) with 33 points and nine assists, just one shy of tying his career high. Michael Porter Jr. settled in quickly, pouring in 31 points on 5-of-10 shooting from three. Ziaire Williams caught fire from beyond the arc, hitting six threes on his way to 25 points.
Brooklyn’s defense is raising red flags just two games into the season. It has given up 130-plus points in consecutive games while allowing both teams to shoot over 50%.
The Cavaliers jumped out early and controlled the pace from the tip, riding the frontcourt duo of Evan Mobley and former Net Jarrett Allen to a double-digit lead by the end of the opening quarter. Mobley opened the scoring with back-to-back floaters inside, taking advantage of a small-ball Brooklyn starting five. Cleveland’s spacing came alive soon after. Sam Merrill hit a pair of threes, and Donovan Mitchell connected on an alley-oop to Jaylon Tyson, pushing the Cavs to a 16–7 lead midway through the quarter.
Brooklyn’s offense struggled early with nine turnovers that led to 11 Cleveland points and several missed looks, falling behind 34-23 after the first quarter.
Porter Jr. led the charge offensively, scoring efficiently from mid-range and finishing around the rim, while Williams was 3-of-3 from deep. The Nets trimmed the deficit to single digits early in the quarter, but repeated turnovers and Cleveland’s relentless work on the glass kept Brooklyn from gaining real momentum.
Thomas provided a needed scoring punch, hitting a step-back three and drawing multiple trips to the line to help keep the offense afloat. Despite the improved energy, Brooklyn’s inability to contain Cleveland’s three-point barrage ultimately told the story. The Cavs outscored the Nets 18-8 in the paint during the frame and carried a 63-51 lead into halftime.
The second half started eerily similar to the first, as three straight Cleveland threes extended the lead to 21 and then 25, the Cavaliers’ largest of the night. After a brief back-and-forth stretch, Brooklyn started to find its footing, with Nic Claxton and Thomas finding their rhythm and trimming the deficit to 14 midway through the third quarter. But Cleveland’s offense was shooting with video game–like efficiency, barely missing a look and knocking down eight threes in the quarter. Thomas poured in 13 points in the quarter, yet the Nets still found themselves trailing 108–86 heading into the fourth.
The Nets came storming back in the fourth, outscoring the Cavaliers 34–15 and cutting the lead to just three with 3:06 remaining. The Barclays Center was rocking, filled with “Brooklyn” chants as the crowd watched their No. 8 overall pick catch fire down the stretch, knocking down multiple threes to bring the Nets right back into it. Unfortunately, it was too little too late as they just couldn’t get over the hump, as Cleveland’s size was too much to handle.
The biggest takeaway? This Nets team refuses to quit, even in the face of early-season struggles.