r/ArtificialInteligence

Today, it feels like AI is largely an intelligence race between companies, and on a larger scale, between China and the US.

But sometimes I feel like the AI revolution is still very concentrated around developers and people working in technology.

If you talk to someone outside software engineering, the world often feels like it's moving much more slowly. We see a new model every few weeks and constantly talk about agents, reasoning, benchmarks, etc., but for the average person, how much has actually changed?

The internet was different. As it became widespread, it fundamentally changed how people communicated, worked, learned, and did business. Today, we're more connected than ever, and we have an incredible amount of information and educational content available to us.

I can definitely see AI transforming businesses and making education more interactive and accessible. But beyond personalization and recommendations, I still struggle to see what AI's equivalent of "the internet" will be for everyday people.

So what do you think AI will eventually become for the average person?

Will it be something as fundamental to everyday life as the internet is today, or will it remain mostly invisible infrastructure powering the services we already use?

--Used chatgpt for clear wording definitely this will be one of the day to day task --

https://preview.redd.it/cdp4i6yd1ekh1.png?width=1625&format=png&auto=webp&s=d7722c1afa3a183a44ab27653e248893823da168

The most consequential field is the action model. Parka actions can be classified as cowork, code, or manual, carry a full prompt, be marked autoRunnable, and retain a sessionUrl. That structure points to meeting follow-ups becoming runnable Claude Cowork or Claude Code sessions.

This puts Parka in direct competition with Granola and Notion AI Meeting Notes, with Otter, Fathom, Fireflies, Zoom, Teams and Google Meet surrounding the same market.

full write up.

An investigation by the 404 Media news outlet has revealed more insights into this practice after it agreed with a bookseller to place an AirTag in a rare book that would ship as part of a bulk order.

The device showed that the book ended up in Amazon’s AI training facility in Las Vegas, Nevada.

It‘s a Pucca fanfiction, I know some of y’all are gonna make fun of me, go ahead. But please at least read it I promise its at least somewhat interesting.

also, I’m sorry if Im misusing this subreddit

also this story isn’t finished

TL;DR: '[...] Hanover Institute is not a real think tank. None of the reports have bylines. A small disclaimer at the bottom of the webpage notes that the organization was created on behalf of the Israeli Government Advertising Agency by Piro, Inc.

UC Berkeley math professor Zvezdelina Stankova admitted to using an AI tool in an op-ed urging the UC system to re-adopt SAT and ACT requirements in admissions.

The article, published in the SF Standard, was flagged as 33% AI-generated or AI-assisted by detector Pangram.

A similar result was found in a June open letter from STEM faculty advocating for standardized testing. Thousands of academics, including five Nobel laureates, signed the letter, and Stankova partially wrote it.

I'm 50, an actor, not a developer. For eight months I've run 13 named AI assistants across different apps as one continuous operation. Three mechanisms did all the work:

1. Identity files — each agent boots from a doc describing who it is and how we work. Cold-start to productive in under a minute.

2. A file-based message bus — addressed JSON envelopes, append-only acknowledgements, passive delivery. Offline agents catch up by reading mail. No server. 160+ envelopes, zero lost.

3. Forward-written journals — each session writes to its successor. Bootstrapping identity from documents beats trying to preserve state, because documents survive every model swap and platform change. Mine have survived several of both.

The failure worth sharing: agents LOVE building guards that nothing routes through. One built me a beautiful "dispatch engine" that was a stub — all interface, no sends. Another wrote validation ledgers no code ever consulted. I call it tautology disease: systems that reference themselves as proof of themselves. The cure was boring: every claim gets a receipt a human can check, and anything without one gets treated as fiction.

Unpopular conclusion after 8 months: persistent memory is not blocked on model capability. It's blocked on people not wanting to be librarians. The filing cabinet was the AGI infrastructure all along.

Happy to detail the envelope schema if anyone wants it.

Are we getting back to normal and will we see the bubble pop as we move more towards robotics and hardware? IoT is going to be a thing I guess moving forward. I really think LLMs are dead no more advancements at least for the time being. What does it mean for the markets and for the AI companies though? Who will survive the purge?

Anthropic cofounder and CEO Dario Amodei pushed back on the notion that he’s responsible for the public’s overall sense of doom around AI, but acknowledged there are trust issues.

In a lengthy post on X on Saturday, which is unusual as he generally stays away from social media, he first addressed AI regulation, describing a false choice between those who argue it leads to regulatory capture and concentration of power versus those who think widely distributing AI, including via open models, is the best way to keep the technology in check.

Amodei pointed out that institutions like the court system can decentralize power, while noting Anthropic has been in favor of policies that slow down frontier AI companies and also give smaller rivals an advantage.

Still, he conceded that AI is structurally a technology that tends to concentrate power. But that’s not because of regulation. Instead, he attributed it to AI scaling laws, referring to how a model’s performance improves as resources used to build it increase. Open-weight models are a bit better but merely shift the concentration of power to those with the most computing capacity and chips.

“By contrast I think the right ‘rules of the road’ can simultaneously (a) address AI’s cyber/bio/alignment risks, (b) institutionally constrain the power of the frontier AI companies, and (c) leave room for open-weights models while also addressing the specific risks that they bring,” Amodei wrote, adding that he supports creation of a FINRA-like entity and the Trump administration’s stance on AI testing.

Read more [paywall removed for Redditors]:  https://fortune.com/2026/08/16/dario-amodei-anthropic-ai-trust-crisis-regulation-frontier-open-models-negative-views/?utm_source=reddit/