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> At an internal staff meeting in September, AWS CFO John Felton had a joke for Prasad Kalyanaraman, the executive overseeing much of Amazon's AI infrastructure expansion.

> "You've taken us free cash flow negative as a company, so congratulations," Felton said, according to a recording of the meeting obtained by Business Insider.

> The remark was lighthearted. But it captured a stunning reversal.

> Just two years ago, Wall Street was debating what Amazon would do with its growing cash hoard. Now, free cash flow has evaporated as Amazon embarks on its biggest bet ever, spending $220 billion this year alone to build the physical backbone for AI.

Huge $220 billion this year to build data centers. One good thing about them for AWS would be that a push to self host / manage your own AI infrastructure could likely still be a boon for AWS.

Dams create large bodies of water that change ecosystems and provide focal points for human communities. They certainly do more than just hydroelectric.

An example would be Lake Pillsbury in Northern California which the dam has not done hydroelectric for decades but the fight to prevent demolishing the dam has had plenty of local support.

Title changed, previously was the same as the article:

"AI agents aren’t ‘going rogue.’ Frontier labs are skipping security basics."

Not a fan of the change. Feels like the article title was changed for being too critical of OpenAI and Anthropic

I've been using OpenRouter, absolutely loving how cheap it is too.

I agree. I hope developers put their token budgets into open weight models rather than funding the banning of open weight models.

OpenAI/Anthropic could start by managing their own testing rather than contracting it out.

https://www.effort.news/irregular

Is that any different than any worms developed in the past decades? If you want to call them worms/virus/replicate (ie using real world names for their digital behavior) I'm not trying to police that. I just don't see the difference between a worm/virus created today with an LLM vs one 'yesterday' without an LLM.

I don't think they are actually evil, I think they're doing what they're doing out of mostly pure intentions. That being said, people need to start advocating internally to get their companies off of using Anthropic's models and start using privacy focused local or open weight models.

It's one thing that Anthropic is pushing for so much open weight regulation, it's another that they have such a high valuation pumped by all of our collective subscriptions and token budgets.

Yes. I would argue it's who's managing the harness and agent is responsible. If you mean you're running an agent locally then it is 100% your responsibility. If you're using some trading platform and all you did was prompt, whoever was running the harness that accepted the model's outputs to hack a third party is responsible for the hack, in my opinion.

I'm curious to see how useful this is. I feel like in practice the existing versions of this feel like they get in the way. While I'm sure I've had some situations where a visual would be helpful, there are two situations where I do not want it:

1) I want a quick answer, and I don't care for the boilerplate UI. For example, if I ask how to make pancakes, I make them all the time and just want to a quick reminder on the ratios, but it might trigger a full UI that I need to sort through to find information.

2) If I ask a to me unrelated to UI question and it triggers a big UI build that is completely off topic for my question (meaning I'm desperately pressing the stop button and prepping rewriting my query)

Or the other one I see, for example if I look up a unix command like:

"ls all hidden files in the /xxx directory"

And I get back:

"Sorry, I am am unable to find /xxx in my current environment"

They shouldn't be depressed. This all needs humans to go over and integrate into other works, and most importantly think about the next big questions.

If anyone is looking for free mobile app datasets, AppGoblin hosts several as well as live data via API.

I've put some up on HuggingFace: https://huggingface.co/datasets/appGoblin/app-store-app-desc... https://huggingface.co/datasets/appGoblin/play-and-apple-app...

As well as self-hosted (links require free account): https://appgoblin.info/free-app-datasets

I've also collected 100ks of man in the middle recording of HTTPs ad network, DSP, MMP etc signals across 100k+ apps for the past couple years. If anyone is interested please feel free to reach out. That data is free to browse on AppGoblin per app, though the body/json are not public.

Anthropic is so self centered it's hard for me to comprehend.

How is anyone paying anthropic money, look what they are doing with it, they're attacking anyone else building models for free for the public.

Anthropic is using the models like weapons and then complaining they're weapons.

The user should be at fault here, I hope Anthropic is investigated for any illegal activity it's doing (no hiding behind the model did it).

I've been using the Claude free tier (browser chat) for awhile and never seem to hit restrictions anymore. There used to be many more restrictions a year ago. At the same time, if they enforce a minimum paid tier I'd probably just switch to Gemini/ChatGPT or whatever other free model is around at the time.

Pretty cool idea. I'd love to see more about who the team is and how the open source models underneath it work and if they can be swapped out.

Google doesn't index my stuff either anymore. Even blogs. I guess they are 'low quality' or whatever, but meanwhile the LLM data companies hoover it up constantly and actually send users to the the sites.

P doom < 1 percent and at the bottom closest to incremental change.

edit: I would be curious to see how I'd changed over time as well. I would guess I was much more worried a year ago

I've had similar issues for my site AppGoblin. I offer 1000 daily free API calls and have had rashes of various bot like activity signing up to use the free API calls. In the end I had to add CloudFlare inbetween the signup process, which is a huge pain as I know that blocks many normal people on VPNs or in smaller countries.

The bot users I found were never particularly sophisticated, using certain name or email elements that were similar and semi obvious. Still, they came from all different domains, many with realish looking vibe coded sites that only looked faked once you really poked around (no contact, or no linkedin, extremely vague, no more than one or two pages etc). And of course the most obvious thing, that one or two I wouldnt' think much of, but seeing 12 similar name/site/email combos in a day and you realize it's coordinated.

"The legislation would permanently prohibit artificial superintelligence, which it defines as a system that exceeds human cognitive ability or has sufficient capabilities to plan and execute the destruction or disempowerment of humanity."

Wow huge miss by Bernie. I mean in many areas models from a year ago were above and beyond most human's cognivity, or at least in rote memorization of a wide variety of facts.

Not to mention, he says ban, but realistically it means to take away from regular people and the government and corporations with licenses keep using it.

I really do feel like this is going the way of the Second Amendment. I wonder if there is grounds to have a right to use AI as a defensive means.

Maybe Anthropic can pause so that open weight and open source models can fully catch up?

I heavily use browser based LLM for bugs I care about. Code that is close to business logic like SQL is all 'by hand'.

Frontend stuff for me, which I'm bad at, I let agents do all of and I test the end result.

Other things are in-between, but time wise it's probably mostly me writing code. Lines of code is the LLM for sure.

This looks great in terms of cost and capabilities, truly pushing the frontier forward in terms of open weight light weight models.

I think some of it comes from that they do not publicly let you see the random seed. So each time you ask the answer is different (like a slot machine) and if they let users use the random seed it would let people much more accurately assess if an underlying model changed somehow (same seed and same input will always have the same output).

Of course the closed Anthropic would never share this, it would definitely take away the 'magic' feeling of the AI

I really hope we get to crest this hardware supply shortages and drop into oversupply.

I spend half my time in Taipei and regularly see young children walking, taking the metro etc. In comparison I recently went camping with inlaws who had no shortage of complaints about the children riding bikes on their rural country road, doing wheelies and what not. To be fair to their point, the posted speed limit is 45MPH and traffic definitely travels well above that. But it's so sad how the US has no room for people not in vehicles.

In Taipei you can see this slowly affecting the city as well. Many new pedestrian "safety" measures inconvenience pedestrians to keep them safe from cars. I'd rather see the cars inconvenienced than the pedestrians, but I wonder if this is just a natural progression.

The one place these seem to not be effective are smaller streets. Small streets seem to keep the cars and pedestrians much more equal.

The vscode chat is great. Not sure if it's also called copilot, but you can plug in any models there and they get sandboxed, tools and link to your code. Great stuff.

I have to admit I'm not clear the difference? It starts with the list of your sessions/agents . Then starting a new "agent" or question or plan. I usually use each agent for a few questions or prompts at most. Occasionally it runs longer than that.

I love using it for the chat question style where I ask it things like:

For these frontend pages with X options collect the database tables for each.

This is of course something easy to do manually, but I like it stepping through a couple functions much faster than me searching around manually and maybe getting lazy and not checking all of them.

I love VSCode built in LLM harness. No extensions, use any model you want, amazing UX for reviews, control of agents. The sandboxing also seems great, I never see models touching anything they shouldn't.

I think this example, "Train, infer, and sample from a normalizing flow: all in your browser", was pretty good at showing how this helps visualize complex math:

https://www.tinyvolt.com/nova/articles/f539a7bb-3ee0-4422-96...

A report on the largest market share increases for mobile app B2B companies (Ad Networks, Developer Tools, Business Tools etc).

A couple quick take aways:

Business Tools - Growth in Cloudflare (measured via API calls) and Integral Ad Science.

Developer Tools - Growth in Expo.dev and ReactNative as more users turn to these tools to develop their cross platform apps.

Data is collected by downloading apps, unzipping, decompiling, running in emulators and scraping app-ads.txt files.

The full CSV is free to download with a free account. Report is free to browse without an account.