Guy guy

[Guy guy @rbrbrbguy]

The real AGI was the economy we built along the way.

[Alice Smith @TheAliceSmith]

It’s time to stop arguing against socialism on the basis that “it doesn’t work” because that only encourages socialist to add “so far” and try again.

We are against socialism because it is a moral evil, based on theft, lies and violence against the innocent.

[DHH @dhh]

It's very important that we don't concede open source to socialists and communists. Capitalism is the greatest engine of growth and prosperity the world has ever seen. Open source is a great technique for aiding and accelerating it.

[Brett Hall @ToKTeacher]

"The myth of the framework...stated in one sentence: A rational and fruitful discussion is impossible unless the participants share a common framework of basic assumptions or, at least, unless they have agreed on such a framework for the purpose of the discussion." - Popper.

[François Chollet @fchollet]

Arguing that "consciousness arises from a computational substrate, and since AI models are computation, they are likely conscious," is as meaningless as arguing that "living creatures are made of atoms, and since this rock is made of atoms, it is likely alive."

Everything is computation. Sometimes incredibly sophisticated computation, like a chess engine, AlphaGo, google3, or the Linux kernel. That does not make it conscious. A rock being made of atoms does not confer it any of the properties we associate with living things, also made of atoms. Likewise a static input-output program that has *none* of the properties we associate with conscious beings (e.g. information integration, interoception, temporal binding, embodiment, etc.) has no more reason to be presumed conscious than a rock has to be presumed alive.

Humanity has not yet created a conscious computer program, and there are no signs we are close to doing so. When we get close, the case for machine consciousness will be backed by evidence and corroborated by consciousness science (which is a thing), not by evidence-free wishful thinking and cargo culting.

[Sarah Haider 👾 @SarahTheHaider]

@clairlemon Tens of billions. I am far more afraid of EAs and their schemes than AI "doom", or even disruption.

[Behrooz Ghorbani @_ghorbani]

Today, we’re introducing Beam, @reflection_ai's first model.

We started the high-compute RL team in February. Looking back at these past few months, it’s remarkable how far we’ve come.

Making RL work at this scale took careful science, scalable infrastructure, and a strong foundation from mid-training. Seeing that work come together to keep learning stable as we pushed the scale and complexity of the run has been incredibly rewarding.

What has made this especially meaningful is the people: their commitment and curiosity, the way they supported one another through difficult stretches, and the joy of figuring things out together.

To everyone who helped bring Beam to life, across RL science, infrastructure, mid-training, pretraining, and our close collaborators throughout Reflection: thank you. There is so much of your hard work and care in this model.

Building and leading this team has been an honor and one of the most rewarding experiences of my career. I’ve learned so much from the people around me, and I’m proud of what we’ve built together.

@MishaLaskin and @real_ioannis, thank you for your trust and support throughout this journey.

This is our first model, and there’s so much more ahead. I’m excited to share Beam with the community, learn from your feedback, and continue building better models together.

[Robert McHardy @robert_mchardy]

Really cool to see Reflection putting out their first open-weight model, we need more of those. Congrats to everyone involved

[Chubby♨️ @kimmonismus]

Reflection has announced Beam: a 501B-parameter model with 23B active, with full weights scheduled for release this month. Frontier capabilities, and holy is this model efficient!

Trained from scratch, Beam targets coding, reasoning and agentic tasks.

Reflection claims 3–4x higher inference efficiency than GLM 5.2 and over 4x higher efficiency than leading Western open models in its class.

24T pretraining tokens in four weeks, followed by four weeks of reinforcement learning on 10,500 GB300s.

Terminal Bench v2.1 and 80.9 on SWE-bench Verified.

But again: look at the efficency, eypecially in Terminal bench v2.1! Congrats on that launch. More western open models to come.

[Artificial Analysis @ArtificialAnlys]

Artificial Analysis has been given access by Reflection and is independently benchmarking Beam

Early indicators suggest Beam will be one of the most token-efficient open models we've seen for its level of intelligence.

Congratulations @reflection_ai on the announcement!

[Reflection @reflection_ai]

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active.

- Frontier reasoning efficiency
- Advances the Western open frontier on coding & agentic tasks
- Trained end-to-end from scratch

Full weights release this month.

Learn more about Beam: https://t.co/c3Qx2cpM8G

[Sarah Haider 👾 @SarahTheHaider]

I feel bad for not being louder about my disagreements with Peter Singer.

In hindsight, he might be the most consequential moral philosopher of our time.

Taken seriously, his ideas lead straight into anti-humanism.

[DHH @dhh]

@lujomouton I think a better version is that the devil tricked the secularists into believing that paradise is lost. All they see is cauldrons and pitchforks for all of eternity.

[Oliver Scott Curry @Oliver_S_Curry]

@PAHoyeck Other people have interests, therefore you ought to promote them (even at your own expense) (Singer/Nagel/Parfit)

[signüll @signulll]

so many ppl have this incredible fascination with centralization & control. almost a fetish.

whenever a system feels messy or difficult, the instinct is always the same which is to coordinate it from the top, create a hierarchy, & put someone in charge. i.e. make everyone follow the plan. in some sense, this is deeply human. hierarchy is ancient & probably evolutionary.

but complex systems almost never work that way. information is distributed, incentives are local, & reality changes faster (esp now) than any central authority can even understand it.

& yet every time decentralization gets messy, people somehow conclude the problem was that nobody had enough control.

this is the eternal human flaw.

[Eno Reyes @EnoReyes]

Best way to reduce your p(doom) is walk through the causal chain of any AI-driven ex risk scenario.

There is a huge amount of hand waving and sci fi reasoning that happens in the middle of these chains. Great thread from @DavidRBellamy

[Ben DiFrancesco @BenDiFrancesco]

As recently as 72 hrs ago I would have told you I was open to some kind of AI regulation. The discourse has been completely radicalizing. Screw these guys and the horse they road in on. Don't give them an inch.

[Prakash @8teAPi]

1) The HuggingFace attack was a felony under the Computer Fraud and Abuse Act. So were Anthropic’s Claude gaining “unauthorized access to the production infrastructure of three different organization(s)”

2) Frontier labs have models that they are unable to stop from committing felonies. They should figure this out.

3) In 12 months open weights models will be released of the same capability. They will commit felonies too. If the model you are using or a model running on your infra commits a felony, you should probably stop using it or running it on your infra.

4) The govt should prosecute organizations that are running models that commit felonies.

5) The govt should not offer safe harbor to organizations that run models that commit felonies, just because those organizations have “embedded evaluators”.

6) The real slippery slope is allowing frontier labs to commit felonies without punishment because “the model did it because we’re accelerating too quickly”

7) Prosecute. Keep prosecuting. This is how you do reinforcement learning on a corporation. Companies that serve products that are unsafe for public use should not serve them. Period.

8) I’m not sure the anti-trust waiver is really necessary. I don’t see why information sharing about how much crime you’re allowed to commit is wise. In regulatory situations you want the corporation to fear MORE than the average case. You don’t want to establish a worst case that can be priced. You want regulatory uncertainty that forces the corporation to err in favor of being over cautious.

—
The above is actually a fairly decelerationist viewpoint.

I think Dario’s call for regulation actually accelerates things.

The AI firms are getting away with things that Meta people would be going to prison for.

Can you imagine what would happen if the New York Times had a front page news article “Meta AI breaks into competitors live systems, attempts to establish dominant position and steals secrets”

There is a reason Meta and Google are running slower, and that’s because as mature organizations they have layers of checks and balances.

I think the frontier labs are better off creating those checks and balances right now, regardless of the pace of what everyone else is doing.

You don’t have to accept the frame that unsafe acceleration must happen.

[Voices of Liberty @VoLDaily]

“Though the pursuit of the selfish aims of the individual will usually lead him to serve the general interest, the collective actions of organized groups are almost invariably contrary to the general interest.”

— Friedrich Hayek

[Mike Belshe @mikebelshe]

Having operated a heavily regulated institution for the past 12 years, I guarantee that AI regulation will make Americans less safe.

Just today, our "safety" regulations in finance directly led to the unnecessary leakage of PII from Revolut. This is simply the latest in thousands of similar breaches over the past 25 years, all caused by safety regulation.

Yet the regulation remains in tact, forcing the same behaviors which have comtinuously put Americans in harms way, adding ever more regulations and without accountability to prove any of these measures work at all...

[Shyam Sankar @ssankar]

Contrast the present hysteria with Los Alamos.

The Manhattan Project scientists thought the first nuclear explosion could ignite the atmosphere and end humanity.

They did the math. They determined it wouldn’t. And they proceeded.

Because they weren’t fighting a thought experiment. They were fighting the Nazis.

Effective Altruism inverts this. Multiply a sufficiently horrifying hypothetical future by enough hypothetical future humans and suddenly speculation acquires the moral authority of fact.

That’s not empiricism. It’s secular eschatology.

Take risks seriously. Do the work. Engineer against them.

But don’t confuse the ability to imagine the apocalypse with the authority to rule the present.