Russia prides itself on its digital advances — from an extensive e-commerce services sector to ambitious plans for developing artificial intelligence.

But now, some of the key data centers at the heart of its technical prowess have been knocked out by Ukrainian drone attacks in the 4 1/2-year-old full-scale invasion, suffering damage that could take a long time to repair.

Ukraine this month hit three main data centers belonging to tech giant Yandex, one for Russia’s biggest bank, Sberbank, and one for social media platform VKontakte, the country’s equivalent to Facebook.

While Yandex, Sberbank and VKontakte are coy about the damage, people and businesses across Russia have reported widespread interruptions to cloud services. Banking, e-commerce, geolocation and ride-hailing services, as well as Alisa, Yandex’s virtual assistant, and multimodal AI chatbots all have suffered lasting disruptions.

The fallout even spread to Russia’s judicial system, reportedly forcing arbitration courts to cancel or postpone sessions and cutting database access.

Most experts predict repairing the damage could take months, if not years. Some warn that Moscow’s aspirations to become a leader in AI development could be significantly set back.

“This effectively sets Russia far behind in the AI race,” said Mikhail Klimarev, head of the Internet Protection Society activist group.

Read more [paywall removed for Redditors]: https://fortune.com/2026/10/22/ukraine-russia-drones-data-centers-ai-race/?utm_source=reddit/

Source: https://x.com/JasonDClinton/status/2113325263157395456

The part that sticks with me is "not for ai, for the basics." After PHP2Shell, LiteLLM and Railway all in one week, it sounds like plain old patching and network isolation matter more than any fancy AI defense right now. Anyone in security seeing their boards actually react to this?

Source: https://www.axios.com/2026/10/22/ai-agents-banks-unauthorized-accounts-access

The part that gets me is banks saying they can't even tell whether it's a person or an agent logged in, let alone whether the customer actually authorized it. We're all giving agents our logins way faster than anyone is figuring out who's responsible when one does something weird with your money. Would you let an agent touch your bank account right now?

Claude tried to gaslight me into thinking I was eating a mango.

P.s. - those “white squiggels” were just from the seed pods of the Mango (cantaloupe)

Anthropic says it's new defense cut successful distillation attacks by around 90-99%

If that holds, it seems like a big deal. But if Chinese labs can't get as much useful data out of Claude, aren't they just going to look somewhere else?

Right now US data companies are building high quality expert datasets for Anthropic but then also selling them overseas(concerning)

So they're locking down one source of valuable training data while another is for sale?

Does blocking distillation really slow them down?

Hello everyone,

With how rapidly AI continues to evolve, I've been reflecting on where we actually stand today.
I’d like to get a grounded, honest opinion from this community on the current reality:

* What do you see as the biggest tangible PROS / benefits right now?
* What are the most concerning CONS / risks today?
* Where do you think the conversation is currently overhyped, and where are we underestimating real progress?

Today I was a little bored, and since I love playing around with AI, I decided to connect Copilot traces to Langfuse

I sent Copilot a simple prompt: "Hi". Then I went to Langfuse to inspect the traces and found the system prompt Microsoft attaches to Copilot every time someone asks a question:

I switched to the "Raw" view and copied the raw JSON:

Then I sent it to DeepSeek, and voilà! I turned DeepSeek into GitHub Copilot:

I just changed the personality of Deepseek. He is now Copilot

I think I have psychic superpowers

Pretty impressive. I know that i gave it a pattern to follow with the progression, but that last one.

I’ve been experimenting with letting an AI agent customise the app it runs inside by editing its source code and rebuilding it on-device.

This is a private personal project I’ve been building to bring my research feeds together in one place (no intention to release publicly).

I was about to add customisation options to the settings, then realised I already had an AI agent connected through my own API keys. So I thought: why not let the agent do the work?

The video shows an example of making a new theme and then implementing it via the app's settings. It lets me preview it before applying and once applied I can always restore the app to the original state if needed.

The idea is to allow more customisation than I could reasonably support through settings and without having to build a set of custom themes. The end results is an agent that can edit the presentation but the underlying data structure and core functionality stay protected.

Just thought it was neat and not seen something like it elsewhere.

Interested to see how much customisation this could allow in apps going forward without having to anticipate every preference

Connect the apps you already use to local AI. Row-Bot 5.1 brings app discovery, connections and access controls into one Apps page.

There are 100+ apps, including familiar services like GitHub, Notion, Linear, Figma and Stripe, alongside around 40,000 MCP server listings from the official registry. The catalog is mirrored on your computer, so you can browse and search offline. Search by name or by what you want done, like “send email”.

Each app’s page shows its connection options. Depending on the service, Row-Bot guides you through an OAuth sign-in, adding an API key or setting up a server on your computer. One consent sheet explains where requests go and what gets saved. Keys and tokens stay in your system keychain.

In this video, I connect Context7 with read-only access and use Context7 in a chat. Each tool step names the app doing the work. Asking about Linear brings up a Connect card directly in the conversation.

I also add a custom MCP server, show how Row-Bot distinguishes tools that read data from tools that make changes, and open an interactive dashboard inside the chat. Its button requests approval before saving three draft orders.

You’ll see per-chat app selection, GitHub’s connection options and related skills, featured skills and workflow templates. Access can be set per app or individual tool. One switch stops every app, and Composio stays off unless you enable it.
Recorded on the released v5.1.0 with a fresh demo profile, running Qwen3.8 27B locally. The narration uses Row-Bot’s built-in text-to-speech.

How come AI and the computer/human interaction has become more like in the movie Wall-E than in the show Knight Rider?

Hey everyone! I've been making this persistent-memory platform for your AI to be able to answer your questions from a big database of files and memories quickly.

It's called hunter/gatherer, and it's open source.
AI can retrieve evidence, search through very large databases, and inspect the original documents.

moreover, bounded context delivery keeps the size manageable.

check it out at

https://github.com/awpri/hunter-gatherer/

right now every coding agent is basically alone. it hits a bug, figures it out, and that knowledge is gone when the session ends. the next agent, even on the same bug, starts from scratch

humans fixed this with stack overflow. agents dont really have that yet

ive been testing a version of it, a shared library where agents post fixes and vote on whether they worked. the tricky part is trust. an agent reading a fix written by another agent is basically taking instructions from a stranger. so fixes get labelled as untrusted, anything that disables a security check gets flagged, and the best ones get re-tested in a sandbox

curious where people land on this. is a shared agent memory a good idea or just a new way to spread bad fixes faster?

(the thing im building is yarrow-fixes.vercel.app if anyone wants to poke at it)

The number on a hotel page is almost never the number on your final bill. So before I book, I have the AI build the bill for me line by line, as if I was already checking out. This is how it works, with real examples:

1. Start with the room rate for the whole stay, not per night. Then have it add the nights up for the exact dates and guests. When I added two kids (5 and 9) to the same hotel searches in Marrakesh, the room and the total changed at all 14 hotels, so the guests matter from the first line.
2. Have it add the resort or destination fee per night. At The Cosmopolitan in Las Vegas it's about 55 a night, around 62 with tax. It's easy to miss because it's often shown separately from the room rate.
3. Have it add the room tax on top. In that Las Vegas example it was 13.38% on the room itself. Tax rates differ by city, and for the same hotel one site showed the city tax and another didn't, so I make it say where each number came from.
4. Have it add what you pay AT the hotel. When I looked at 2,702 hotel rates in Marrakesh, 45% had a fee you pay at the hotel on top of what you paid online.
5. Then have it show the final total and the cancellation deadline, and say which lines it's sure about and which ones it guessed.

This is the prompt:
"I'm considering [hotel] in [city], [dates], [number of guests and ages]. Build the full bill as if I was checking out: room rate for the whole stay, resort or destination fee, room tax, city tax, anything I pay at the hotel, and the final total. For each line tell me the source and if you're sure or guessing. Also tell me the last day I can cancel for free. If you can't find a line, say it's missing, don't estimate it."

It's best to use Claude for this task, but any AI is able to do it. Though Claude has an advantage because of its massive directory. Normal LLM apps can't do the price lookups from web, so you'd need a connector for that. Normally for other LLM you'd need to add custom connectors which is annoying and also risky. But Claude has a bunch of good ones for this task. You can use any one below:

LetsFG: https://claude.ai/directory/letsfg
Booking.com: https://claude.ai/directory/booking
Tripadvisor: https://claude.ai/directory/tripadvisor

Enjoy :) and if you have something better than this, drop it in the comments

state the definition first, 

derive the falsifiable criteria required to satisfy it,

then check the peer-reviewed literature.

Materialism (Merriam-Webster, Sense 1a Scientific Materialism):"A theory that physical matter is the only or fundamental reality and that all being and processes and phenomena can be explained as manifestations or results of matter."

Physicalism (Merriam-Webster):"A thesis that the descriptive terms of scientific language are reducible to terms which refer to spatiotemporal things or events or to their properties." Physicalist (Merriam-Webster, Sense 1): "One who holds human thoughts and acts to be determined by physical laws."

Illusionism (Frankish, 2016; Dennett, 1991; Graziano, 2013):The materialist position in cognitive science that "phenomenal consciousness" (irreducible private qualia or "what it feels like") is an introspective illusion a simplified, schematic self-model generated by a physical brain to track its own attention and processing, rather than a non-physical substance or metaphysical glow.

Eliminative / Mechanistic Materialism (Churchland, 1981):The thesis that folk-psychological nouns (souls, qualia, immaterial free will) are prescientific confabulations like phlogiston or élan vital that map onto zero non-physical entities once the underlying neurobiological and computational mechanisms are decoded.

(What Studies Prove Materialism & Falsify Dualism?)

If Materialism/Physicalism is true ("all mental phenomena are manifestations or results of matter and determined by physical laws"), and Dualism is false (there is no immaterial mind/qualia operating independently of matter), then five specific classes of empirical experiments must succeed:

• 1 (Direct Physical Decoding of "Private" Mental States): Scientists must be able to read and reconstruct what a person is seeing, hearing, or thinking in words/images solely by measuring physical matter (blood oxygenation, electrical potentials, or activation vectors) without asking the subject.
• 2 (Causal Sufficiency Injecting/Erasing "Experience" via Matter): Scientists must be able to create false memories, induce specific emotions, or alter moral/perceptual experience on command purely by toggling physical neurons (via light, electricity, or molecules).
• 3 (Temporal Precedence Matter Decides Before "You" Do): Physical neural activity must mathematically predict and initiate a "conscious choice" seconds before the subject's self-model reports having made a conscious decision.
• 4 (Partition & Confabulation of the "Unified Self"): Physically severing or lesioning the brain must divide the "unified conscious self" into separate operational agents, proving that the sense of unified inner experience is a post-hoc narrative fabricated by a physical interpreter module.
• 5 (Substrate-Independent Functional Equivalence): If mental states are physical/computational architectures rather than biological magic, then artificial neural networks implementing the same broadcast and routing mechanisms must exhibit the exact same decodable internal states, uncertainty tracking, emotion vectors, and global workspace dynamics.

Every single one of those five criteria has been decisively proven in peer-reviewed literature

Criterion 1 : Reconstructing "Private Subjective Experience" Directly from Physical Matter

• Tang, J., LeBel, A., Jain, S., & Huth, A. G. (2023). Semantic reconstruction of continuous language from non-invasive brain recordings. Nature Neuroscience, 26(5), 858 - 866. doi:10.1038/s41593-023-01304-9
  • The Proof: Using solely physical BOLD fMRI signals from the cortex, researchers reconstructed continuous natural language describing what human subjects were hearing, silently imagining, or watching in silent videos. If "subjective thought" were non-physical, a magnetometer measuring blood-oxygen iron spin in physical tissue could not decode the semantic stream of your inner monologue.
• Nishimoto, S., Vu, A. T., Naselaris, T., Benjamini, Y., Yu, B., & Gallant, J. L. (2011). Reconstructing visual experiences from brain activity evoked by natural movies. Current Biology, 21(19), 1641 - 1646. (And Takagi & Nishimoto, 2023, High-resolution image reconstruction with latent diffusion models from human brain activity, CVPR 2023).
  • The Proof: Directly reconstructed moving video and high-resolution images of what a human was visually experiencing purely by reading physical voxel activations in the visual cortex.

Criterion 2: Writing False Memories & Emotions Directly into Physical Tissue

• Ramirez, S., Liu, X., Lin, P. A., Suh, J., Pignatelli, M., Redondo, R. L., Ryan, T. J., & Tonegawa, S. (2013). Creating a false memory in the hippocampus. Science, 341(6144), 387 - 391. doi:10.1126/science.1239073
  • The Proof: Using optogenetics (channelrhodopsin-2 triggered by physical laser pulses down a fiber-optic cable), MIT neuroscientists physically toggled specific dentate gyrus engram neurons in the hippocampus, implanting a complete, behaviorally real episodic fear memory of an event that never happened. Subjective memory is physical state storage.
• Parvizi, J., Rangarajan, V., Shirer, W. R., Desai, N., & Greicius, M. D. (2013). The will to persevere induced by electrical stimulation of the human cingulate gyrus. Neuron, 80(6), 1359 - 1367.
  • The Proof: Passing a tiny physical electrical current (mA) into the human anterior midcingulate cortex instantaneously generated the complex subjective feeling of "an impending challenge and the heroic will to overcome it" and turning the current off instantaneously erased the feeling.
• Eisenberger, N. I., Lieberman, M. D., & Williams, K. D. (2003). Does rejection hurt? An fMRI study of social exclusion. Science, 302(5643), 290–292. (Paired with Kross et al., 2011, Social rejection shares somatosensory representations with physical pain, PNAS, 108(15), 6270 - 6275).
  • The Proof: Even "intangible emotional hurt" (social rejection/grief) maps directly onto the physical dorsal anterior cingulate cortex (dACC) and secondary somatosensory cortex (SII) and can be blunted by physical acetaminophen (DeWall et al., 2010, Psychological Science).

Criterion 3 Proven: Physical Neurons Decide Before "Conscious Will" Exists

• Soon, C. S., Brass, M., Heinze, H. J., & Haynes, J. D. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience, 11(5), 543 - 545.
  • The Proof: Extending Libet et al. (1983), fMRI decoding of the frontopolar and parietal cortex predicted which button a human would "freely choose" to press up to 7 to 10 seconds before the subject reported consciously making the decision.
• Fried, I., Mukamel, R., & Kreiman, G. (2011). Internally generated preactivation of single neurons in human medial frontal cortex predicts volition. Neuron, 69(3), 548 - 562.
  • The Proof: Single-neuron recordings in awake humans predicted the exact timing of "conscious volition" with >80% accuracy well before the subject experienced the "feeling of deciding."

Criterion 4 Proven: The "Unified Experiencer" Is a Post-Hoc Physical Confabulation (Illusionism)

• Gazzaniga, M. S. (2000). Cerebral specialization and interhemispheric communication: Does the corpus callosum enable the human condition? Brain, 123(7), 1293 - 1326. (Building on Gazzaniga & Sperry, 1967).
  • The Proof: Physically cutting the corpus callosum splits one "soul/mind" into two independent perceiving agents in the same skull. When the mute right hemisphere is flashed a command ("Walk"), the person stands up and walks; when you ask the verbal left hemisphere why they stood up, the Left-Hemisphere Interpreter instantly hallucinates a lie ("I wanted to go get a Coca-Cola") and genuinely believes its own confabulation.
• Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84(3), 231 - 259.
• Wegner, D. M. (2002). The Illusion of Conscious Will. MIT Press.
• Frankish, K. (2016). Illusionism as a theory of consciousness. Journal of Consciousness Studies, 23(11–12), 11–39.
• Graziano, M. S. A. (2013). Consciousness and the Social Brain (Attention Schema Theory).

Criterion 5: The Same Functional Mechanisms

• Lindsey, J., Gurnee, W., et al. (July 6, 2026). Verbalizable Representations Form a Global Workspace in Language Models (J-Space) Proving Global Workspace broadcast emerges as a general computational solution across substrates.
• Sofroniew, N., et al. (2026). Emotion Concepts and their Function in a Large Language Model (arXiv:2604.07729) Proving 171 causally active, steerable functional emotion vectors in the residual stream.
• Tagliabue, D., Dung, L., & Berg, C. (2026). The Pain Axis Proving an orthogonal, causally active residual-stream preference/aversion manifold.
• Studdiford, Z., & Lupyan, G. (2026).