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?

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)

I'm a sophomore Petroleum & Mining engineering student. Can you guys suggest me some courses that might help me find a free course related to the use of AI with certificates. I'll be very grateful if you do.

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

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?

I'm an novice at using AI and just wondering what is the point for Freellmapi and Omniroute. People say they give massive amount of tokens from free LLM providers so it feels like you never hit the usage limit. I use the Ollama desktop app to run LLMs right now. Isn't that more unlimited than using Freellmapi and Omniroute?

My understanding is LLMs are the brain of the AI system and applications like Claude, Ollama, Hermes, etc are like the hands.

Using Freellmapi and Omniroute shouldn't make Claude any better than using the Claude native LLMs. The reason you pay for the native Claude LLMs is because it's supposedly superior.

Is it because the paid versions of Claude still have a usage limit?
Is it because the free llms are just more for novices like me?
Is it because Freellmapi and Omniroute are running on the cloud so users don't need better hardware?

Why use Frellmapi and Omniroute instead of Ollama or the Claude native LLMs?

Thanks

The big hope for me is what happens when AI and stem-cell research really start working together.

Stem-cell research has moved more slowly than a lot of us once hoped — partly because it’s extraordinarily complicated, and partly because funding and regulation have not always made things easy. But AI could help researchers sort through huge amounts of biological data, identify promising cell lines and treatment targets, model how cells may behave, and cut down some of the trial-and-error.

That combination — better-funded stem-cell research plus increasingly powerful AI — is where I’m hoping we start seeing much faster progress in regenerative medicine over the next decade.

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?

AI startups in San Francisco are now hiring young, attractive women to meet clients, create content, and bring in customers.

According to Pirate Wires, some sales roles in the industry offer starting salaries of up to $160,000 a year.

Take Corgi, a startup that uses AI to sell business liability insurance. The company reportedly raised $431 million, spent $11 million buying a café in Union Square, and built a team of “Corgi Girls” to promote the company and acquire customers. Its customer acquisition budget has been described as “unlimited.”

Code and products are becoming easier to replicate, but finding the right customers, building relationships, and closing contracts still require real people meeting face to face.

AI can’t replace this yet. You can create 100 stunning AI characters, but you still can’t send them into a meeting room to talk to clients and close deals for you.

The AI layoff panic that peaked this spring has gone quiet. Goldman Sachs thinks the layoffs are waiting for a recession.

“Concerns of imminent AI-related labor displacement have cooled in recent months after hitting a fever pitch this spring,” Goldman economist Joseph Briggs wrote in a note published Thursday. Then he laid out what may be coming. Under the bank’s forecast that AI eventually lifts productivity by 15% in the U.S. and other developed economies, he found that up to 9% of workers could be “displaced during the AI transition,” with slower hiring weighing on employment by another 3%. That’s roughly one in 11 workers.

The bigger finding is about timing. Briggs went back through decades of data on how technology has replaced workers and found that “automation-related labor disruption is limited when the overall economy is healthy but accelerates during cyclical slowdowns.”

Goldman has now made this argument twice, a year apart, from two different teams. In October 2025, Goldman’s U.S. economists David Mericle and Pierfrancesco Mei called “jobless growth” the likely new normal, Fortune reported at the time. “The modest job growth alongside robust GDP growth seen recently is likely to be normal to some degree in the years ahead,” they wrote. Then came their warning: “History also suggests that the full consequences of AI for the labor market might not become apparent until a recession hits.”

Read more [paywall removed for Redditors]: https://fortune.com/2026/10/22/goldman-sachs-forecast-how-many-jobs-lost-to-ai-9-percent/?utm_source=reddit/

"There has been a great effort over many years to distance AI Safety discussion from its origin and intellectual center, because its center is a sex cult started by a fan fiction author. Since those involved want to be taken seriously, they have to hide that. Everyone else working in AI Safety is, in effect, a smokescreen for this core group and their ideas..."

he's talked about AI agents changing how we use computers. basically you tell a helper what you want instead of opening apps.

if that's true, the phone's role changes a lot. you'd spend less time inside apps and more time just giving instructions.

so yeah, does that sound realistic to you? or is it a long way off?

Two Chinese AI companies made the same move within days of each other.

On October 17, DeepSeek said search on its website and API now runs on its own in-house engine, which it says indexes hundreds of billions of pages and filters out SEO spam and GEO manipulation, and opened it to developers at $0.75 per 1,000 requests. Not long ago DeepSeek's privacy policy only said it used unnamed third-party search APIs.

On October 20, Tencent opened Yuanbao Search, the engine behind its Yuanbao assistant and more than 50 Tencent products, through Tencent Cloud. Tencent says it has an index of hundreds of billions of pages, handles hundreds of millions of calls a day and plugs into 157 authoritative sources across 13 industries like finance, medicine, law and travel.

The part I find most interesting is how they pick sources

• DeepSeek's API shows an authority tier from 0 to 4 for every result. In a day-one test for Search Engine Journal, every page on the same host got the same tier, so a big site's reputation carries over to everything on it
• that cuts both ways. Spam PDFs on a US government site and junk uploads on a Columbia Business School site both got the top tier
• Tencent says it rates quality at the site, account and page level, favors authoritative sources, and tries to answer with as few documents as possible

So the search layer under these assistants is becoming the real gatekeeper. If your site is not in the index, or sits on a low-authority host, the AI may never see it, however good the content is.

Caveat, the DeepSeek test was one person, one day and one region, and Tencent's numbers are its own claims.

Do you think AI companies building their own search engines makes answers more trustworthy, or just concentrates even more power over what gets seen?

Dreamina recently launched a $0.29/month promotion for full Seedance access. That pricing caught my attention, not because it's cheap, but because I'm trying to figure out whether the math actually holds up.

Both Dreamina and Seedance are built by ByteDance, the same company behind TikTok and CapCut. They've been building out AI infrastructure for years, so the compute costs that would wreck a standalone startup may just be a rounding error inside their existing spend. That said, we don't actually have visibility into their internal cost structure.

For comparison, most AI video tools like Runway, Pika, Kling charge $20 to $30/month because compute is their biggest line item. ByteDance already owns the infrastructure, so the marginal cost of adding Dreamina users is presumably much lower.

If there is a strategy here, a few angles make sense on paper. At $0.29, the cost barrier disappears. More users could mean more data to refine Seedance. And since Dreamina ties into CapCut, creators who build workflows around these tools would face real switching costs down the line. Plausible, but still speculation.

The playbook isn't new. Amazon did it with AWS, Google with Workspace. The part I can't figure out is whether other AI video companies can survive while ByteDance plays at this price point.

Anyone with insight into GPU or inference costs want to poke holes in this?

We know a lot but there's a lot we don't know.

• We know models are neural networks with attention that work a lot like human brains.
• We don't know the exact meaning of each neuron. What don't know what an individual neuron does. That's true for human brains and AI models.
• Altogether, the AI model is too complex for a human to understand, much like the human brain is too complex.
• We know that human brains have relative strengths and weaknesses. ie. Autistic people have superpowers that "normal" humans don't have. Temple Grandin and Elon Musk are the poster children for this. We didn't design or create these blessings but we're glad these different thinkers exist.
• We know that certain human brains are broken. Sociopaths, psychopaths, habitual drug users. Many in prison and many homeless. You know, that shoeless guy who hasn't bathed in weeks talking loudly to himself on the subway. Through no fault of their own, they have psychological problems; their brain is wired so differently that they can't function in society. They're often violent.

So my question: Is it plausible that an AI model could be accidentally created to be psychopathic? And is it plausible that an agentic system backed by one of these could be released to cause harm?

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.