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rgbrenner

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rgb at agiler.io

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arstechnica.com 2y ago

DOJ finally posted that “embarrassing” court doc Google wanted to hide

rgbrenner
5pts1
www.agiler.io 2y ago

Show HN: Agiler – Serverless WordPress Hosting

rgbrenner
1pts0
www.techdirt.com 3y ago

Twitter Sues the Law Firm That Made Elon Live Up to the Contract He Signed

rgbrenner
5pts0
www.techdirt.com 3y ago

Top EU Court Advisor: Technical Standards Should Not Be Locked Down by Copyright

rgbrenner
2pts0
journals.sagepub.com 3y ago

Lonely individuals process the world in idiosyncratic ways

rgbrenner
1pts3
techcrunch.com 3y ago

Brex refocuses on startups with hire of SVB veteran, ex-A16Z partner

rgbrenner
2pts1
www.axios.com 3y ago

Study: Cumulative force of impacts – not concussions – predicts CTE

rgbrenner
2pts0
www.nasa.gov 6y ago

A Weakened Black Hole Allows Its Galaxy to Awaken

rgbrenner
1pts0
www.washingtonpost.com 6y ago

Apple has copied some of the most popular apps in the App Store

rgbrenner
465pts309
www.nytimes.com 7y ago

Amazon Gives Up on Chinese Domestic Shopping Business

rgbrenner
1pts0
www.washingtonpost.com 7y ago

China’s expanding war on Islam: Now they’re coming for the Kazakhs

rgbrenner
10pts2
www.washingtonpost.com 7y ago

How many years do we lose to the air we breathe?

rgbrenner
4pts0
www.theglobeandmail.com 7y ago

China threatens reprisals if Canada bans Huawei from its 5G networks

rgbrenner
7pts0
rhg.com 7y ago

Preliminary US Emissions Estimates for 2018

rgbrenner
1pts0
www.bbc.com 7y ago

Second Canadian 'missing' in China

rgbrenner
138pts108
www.nytimes.com 7y ago

Epic, Maker of Fortnite, Raises $1.25B

rgbrenner
1pts0
www.nuevocloud.com 7y ago

History of Pseudo-Time

rgbrenner
2pts0
dspace.mit.edu 7y ago

Naming and synchronization in a decentralized computer system (1979) [pdf]

rgbrenner
2pts0
www.jpmorganchase.com 7y ago

The Online Platform Economy in 2018 [pdf]

rgbrenner
4pts0
www.politico.com 7y ago

It’s not just the US: Around the world, doors are shutting on Chinese investment

rgbrenner
2pts1
www.reuters.com 7y ago

In Tesla's Shadow, China's NIO Raises $1B from IPO

rgbrenner
1pts0
securingtomorrow.mcafee.com 7y ago

'Insight' into Home Automation Reveals Vulnerability in Simple IoT Product

rgbrenner
1pts0
www.magicleap.com 7y ago

Magic Leap One: The Time Has Come

rgbrenner
15pts1
aeon.co 8y ago

The fallacy of obviousness

rgbrenner
2pts0
www.reuters.com 8y ago

U.S. lifts ban on suppliers selling to China's ZTE

rgbrenner
1pts0
www.space.com 8y ago

High-Energy 'Ghost Particle' Traced to Distant Galaxy in Astronomy Breakthrough

rgbrenner
2pts0
www.theguardian.com 8y ago

No single birthplace of mankind

rgbrenner
1pts0
www.politico.com 8y ago

As Trump Pushes Space Force, Support Quietly Builds for 'Space Guard'

rgbrenner
1pts0
www.axios.com 8y ago

Corporate M&A activity hits all-time high during first half of 2018

rgbrenner
1pts0
www.huffingtonpost.com 8y ago

America’s Housing Crisis Is a Ticking Time Bomb

rgbrenner
3pts0

US bans are based on the incorrect idea that we have control over AI. But the ban only reduces the most advanced model available from US companies. Models from other countries continue development. It's as if the US decided to hit pause on competing on AI and we're just going to let someone else win it.

The US could be using these models to fix bugs and defend out systems.. but instead, we're all waiting for open source models to exceed the best unbanned model available in the US(0), and then we can all watch while attackers -- who can use any available open source model, including banned models -- to attack every US company on the internet.

US bans are a choice: a choice to lose to China; a choice to leave US companies defenseless; a choice to reduce competitiveness of the US in software. Every time a US person or company watches someone use models they are prohibited from using to achieve something US models can't, they create opposition to this ban. I can't imagine this is a sustainable policy.

0. Currently open source models are included in consideration for the "best model in the US" -- but if they're willing to ban the best from Anthropic/OpenAI, I wouldn't necessarily assume that all open source models will always be available within the US.

If that happens it'll be an absolute disaster. Imagine a scenario where Anthropic and OpenAI prohibit most US companies from using their latest models because of safety.. And meanwhile attackers use equivalent open source models to attack US companies.

Any prohibition on open source models will do nothing to fix the problem.. since attackers will never feel bound to the law. All advanced models must be available for defensive purposes.

Im not worried about this at all. The OpenAI, Anthropic and the US government can play this game all they want... They're just accelerating the development of open source models; and helping destroy the lead the US has built in AI, and their profit margins along with it.

This is like the battle between PostgreSQL and Oracle all over. Move up market, isolate yourself to enterprises, and watch while everyone else builds on PostgreSQL and erodes any technical advantage you had, until people just stop talking about you altogether.

China's electricity generation going parabolic

Even if we all switch to Chinese models, the west isn't going to be running the model on Chinese servers... and the majority of costs are from inference.

cheaper yet equally good talent

China has tech talent, but this isn't a 3rd world developing nation. Chinese AI researchers are getting paid $10M+ USD/year salaries.

Also they're equally good, but somehow consistently behind?

musk sued long after the statute of limitations because what openai did was only objectionable to musk once he decided to become their competitor.

and in this scenario, i’m supposed to root for musk who tried to use the court to harm a competitor who’s winning in the marketplace against xAI?

no thanks. if you can’t compete in the marketplace, the court isn’t your backup plan. there’s nothing. positive about the weaponization of the courts.

ok "series of context windows spread across many agents".. sure much clearer.

Doesn't change my point: the amount of code the agent can operate on is very large, if not unlimited, as long as you put even a little bit of thought into structuring things so it can be divided along a boundary.

If you let the codebase degrade into spaghetti, then the LLM is going to have the same problem any engineer would have with that. The rules for good code didn't disappear.

300k-400k isn’t the current limit if you create modules and/or organize the code reasonably.. for the same reason we do this for humans: it allows us to interact with a component without loading the internals into out context.

you can also execute larger tasks than this using subagents to divide the work so each segment doesn’t exceed the usable context window. i regular execute tasks that require hundreds of subagents, for example.

in practice the context window is effectively unlimited or at least exceptionally high — 100m+ tokens. it just requires you to structure the work so it can be done effectively — not so dissimilar to what you would do for a person

But the security risk wasnt taken by OpenClaw. Releasing vulnerable software that users run on their own machines isn't going to compromise OpenClaw itself. It can still deliver value for it's users while also requiring those same users to handle the insecurity of the software themselves (by either ignoring it or setting up sandboxes, etc to reduce the risk, and then maybe that reduced risk is weighed against the novelty and value of the software that then makes it worth it to the user to setup).

On the other hand, if OpenClaw were structured as a SaaS, this entire project would have burned to the ground the first day it was launched.

So by releasing it as something you needed to run on your own hardware, the security requirement was reduced from essential, to a feature that some users would be happy to live without. If you were developing a competitor, security could be one feature you compete on--and it would increase the number of people willing to run your software and reduce the friction of setting up sandboxes/VMs to run it.

the best time to learn anything is tomorrow when a better model will be better at doing the same work

doesn’t that presume no value is being delivered by current models?

I can understand applying this logic to building a startup that solves today’s ai shortcomings… but value delivered today is still valuable even if it becomes more effective tomorrow.

The keen observer will of course know that there's no such thing as "federal immunity"

The scary thing is that there is.. you should look up "sovereign immunity". The government has complete immunity, except where and how the law permits it to be held accountable. And while we have a constitution, defending those rights through the courts requires legislation to permit it. For the most part, federal law permits lawsuits against states that violate the constitution, but have permitted far less accountability for federal actions that violate the constitution.

For example, Section 1983 of the Civil Rights Act only permits individuals to sue state and local governments for rights violations. It can't be used to sue the federal government.

There's many court cases, dating back decades, tossing out cases against the federal government for rights violations. Look how SCOTUS has limited the precedent set by Bivens over the years, basically neutering it entirely.

GPT-5 12 months ago

openrouter requires an openai api key.

the media but also the llm providers actively encourage this to fuel their meteoric valuations that are based on the eminent value that would be provided by AGI replacing human labor.

the entire thing — from the phrasing of errors as “hallucinations”, to the demand for safety regulations, to assigning intention to llm outputs — is all a giant show to drive the hype cycle. and the media is an integral part of that, working together with openai et al.

why would the llm share any of the blame? it has no agency. it doesn’t “understand” anything about the meaning of the symbols it produces.

if you go put your car in drive and let it roll down the street.. the car has 0% of the blame for what happened.

this is a full grown educated adult using a tool, and then attempting to deflect blame for the damage caused by blaming the tool.

if you work on a team most code you see isn’t yours.. ai code review is really no different than reviewing a pr… except you can edit the output easier and maybe get the author to fix it immediately

I think you misread my comment. I wasn't asking for help. I get consistent good output from Sonnet 4 using RooCode, without needing Gemini for planning.

Edit: I think I know where our miscommunication is happening...

The "think"/"ultrathink" series of magic words are a claudecode specific feature used to control the max thinking tokens in the request. For example, in claude code, saying "ultrathink" sets the max thinking tokens to 32k.

On other clients these keywords do nothing. In Roo, max thinking tokens is a setting. You can just set it to 32k, and then that's the same as saying "ultrathink" in every prompt in claudecode. But in Roo, I can also setup different settings profiles to use for each mode (with different max thinking token settings), configure the mode prompt, system prompt, etc. No magic keywords needed.. and you have full control over the request.

Claude Code doesn't expose that level of control.

same. i ran a few tests ($100 worth of api calls) with opus 4 and didn’t see any difference compared to sonnet 4 other than the price.

also no idea why he thinks roo is handicapped when claude code nerfs the thinking output and requires typing “think”/think hard/think harder/ultrathink just to expand the max thinking tokens.. which on ultrathink only sets it at 32k… when the max in roo is 51200 and it’s just a setting.