Hacker News: astrobiased

New comment by astrobiased in "Three new discoveries in mathematics, computer science, and physics"

astrobiased — Tue, 27 Oct 2026 02:33:39 +0000

This is an exciting time, but also there are very real changes at hand. Game changing discoveries will likely not happen at universities but at private AI frontier labs. Moreover, the models that are used on this are not always open to the broader community today.

What will it be like in two years? Will such models that help enable paradigm shifts in science be only accessible to employees of those private companies? Still thinking about the ramifications ... amazing and discombobulating at the same time.

New comment by astrobiased in "GPT-6 Astra"

astrobiased — Sat, 05 Sep 2026 00:49:48 +0000

Appreciate the input! Responses below to your first two items:

1) I'm leaning more into a broader sense, which is that given the priors a system already possesses, how efficient can it acquire competence on a novel task? If I'm reading the point you make, you're focussing on continual learning right? If so, I'm not necessarily restricting my statement above to that.

Here's another reframing: How much of the benchmark improvements come from overwhelmingly large training distributions vs improving the models for adapting to things genuinely outside of it?

2) Excellent points about crystalized and fluid intelligence. Wouldn't the LLM scaling gains be a representation of crystallized capabilities? In regard to Gf, that is exactly what I am asking about. That is what seems to be lacking, Gf like adaptation under genuine novelty.

My concern is that it's increasingly difficult to tell of what looks like Gf like behavior is really coming from better adaption vs. having broad priors from the model's large learned distributions.

New comment by astrobiased in "GPT-6 Astra"

astrobiased — Thu, 03 Sep 2026 22:01:34 +0000

I think the moat that China has is energy costs. It's taking learnings from the Bitter Lesson. If you role up scale and compute to the next level, it's energy resources. China has it and sharing open weight models is an effective means of removing the tech moat. This idea has been floating around for a bit now (I'm not taking credit for it).

New comment by astrobiased in "GPT-6 Astra"

astrobiased — Thu, 03 Sep 2026 21:11:23 +0000

I can’t help but notice how much this echoes Francois Chollet’s On the Measure of Intelligence: https://arxiv.org/abs/1911.01547

Most of frontier-model progress still looks like skill acquisition optimization: broader benchmark coverage and performance, more domains absorbed into the training distribution, and increasingly strong performance within that surface area.

It seems more about coverage-driven competence. Somewhat analogous to overfitting at scale.

The harder question, in Chollet’s framing, is: how efficiently can a system learn to do something genuinely new?

With our current AI architectures and training in place, I think we will only continue on skill acquisition optimization vs. truly novel intelligence.

New comment by astrobiased in "Nvidia Nemotron 3.5 Lightning and NeMo Switchyard"

astrobiased — Wed, 12 Aug 2026 00:48:23 +0000

Depends on the type of agentic task though. For simple operations, a small model can be quite beneficial.

New comment by astrobiased in "Prime Agent: A self-improving RLM agent"

astrobiased — Thu, 06 Aug 2026 07:14:02 +0000

Not RL. SFT.

New comment by astrobiased in "Prime Agent: A self-improving RLM agent"

astrobiased — Thu, 06 Aug 2026 07:09:39 +0000

Yes, used bert model with decent results.

New comment by astrobiased in "Pi's Minimalism Is Its Advantage"

astrobiased — Wed, 05 Aug 2026 03:22:59 +0000

Pi does one thing that I love, developing a tool that has minimalism where it's easily configurable with good documentation. The leads to new use cases that the the author(s) would have never dreamed of. The organic growth process of the Pi ecosystem has been fascinating to observe. It's one of the reasons why Pi has become one of my favorite coding agents to this day, flexible beyond personal uses and extensible to larger environments.

IMO, I view it more than a coding agent, it's a coding agent platform with powerful extensibility.

New comment by astrobiased in "Show HN: Cactus Hybrid: We taught Gemma 4 to know when it's wrong"

astrobiased — Wed, 22 Jul 2026 23:28:19 +0000

Is this in any way similar to Goodfire's work? https://www.goodfire.ai/research/rlfr#

New comment by astrobiased in "Who's afraid of Chinese models?"

astrobiased — Tue, 21 Jul 2026 10:40:21 +0000

The post hits it spot on with unequal access to the models in terms of security. I'm developing OSS where security is important for the user ... but the frontier models like GPT 5.6 and Fable flake out and state that I cannot get the info/access.

This is extremely lopsided I'll have to resort to GLM 5.2/K3 to ensure that those security issues (hopefully) are resolved properly.

For OSS, this is one of the most counterintuitive experiences I have ever had. More than ever I'm convinced that open weight and open pipelines models are 100% critical for progress on the AI and societal fronts.

New comment by astrobiased in "Real-Time LuaTeX: Recompiling Large Documents in 1ms [pdf]"

astrobiased — Sun, 19 Jul 2026 02:20:10 +0000

Same, so much in fact that I have used it for my website now and it works beautifully for graphics and formulas.

World Models and Interpretability Are Two Sides of the Same Coin

astrobiased — Mon, 22 Jun 2026 15:35:03 +0000

Article URL: https://twitter.com/soniajoseph_/status/2067402054092628379

Comments URL: https://news.ycombinator.com/item?id=48631689

Points: 3

# Comments: 0

New comment by astrobiased in "Agents need control flow, not more prompts"

astrobiased — Thu, 07 May 2026 17:26:42 +0000

It's the right direction, but control flow introduces limitations within a system that is quite adaptable to dynamic situations. The more control flow you try to do, the more buggy edge cases that pop up if done poorly.

Still have yet to see a universal treatment that tackles this well.

New comment by astrobiased in "What is an elliptic curve? (2019)"

astrobiased — Thu, 18 Dec 2025 15:56:21 +0000

John is not only smart and knowledgeable, but an incredibly great person to know in general. I worked with him on a project briefly back in 2012 and he stood out as a champion for science, coding, and education. His posts clearly reflect him well.

New comment by astrobiased in "Toucan Wireless Split Keyboard with Touchpad"

astrobiased — Tue, 11 Nov 2025 04:42:08 +0000

Absolutely love these type of keyboards. But ... with how much security I work with for logins, etc, the fingerprint button on my Mac keyboards are amazing time savers that I don't want to live without. Has anyone found a workaround?

New comment by astrobiased in "19% of California houses are owned by investors"

astrobiased — Wed, 06 Aug 2025 22:08:44 +0000

What I find odd is that definition of "investor" is not that clear. When you click through the links you get blocked at the data provider with no context. There's also a link to another post by the same news provider. When clicking through reference to the data source, the link doesn't work.

A foundation model to predict and capture human cognition

astrobiased — Thu, 17 Jul 2025 15:53:01 +0000

Article URL: https://www.nature.com/articles/s41586-025-09215-4

Comments URL: https://news.ycombinator.com/item?id=44594707

Points: 1

# Comments: 0

New comment by astrobiased in "Define policy forbidding use of AI code generators"

astrobiased — Thu, 26 Jun 2025 01:13:47 +0000

It would need to be more than that. A prompt for one model can have different results vs another. Even when the model has different treatment for inference, eg quantization, the same prompt for the unquantized and quantized model could differ.

The Power of Bayesian A/B Testing

astrobiased — Tue, 23 Jan 2018 17:30:53 +0000

Article URL: https://medium.com/convoy-tech/the-power-of-bayesian-a-b-testing-f859d2219d5

Comments URL: https://news.ycombinator.com/item?id=16215356

Points: 10

# Comments: 0

The Postmodern Tailor: Size Personalization Beyond Labels

astrobiased — Thu, 03 Mar 2016 22:00:21 +0000

Article URL: http://multithreaded.stitchfix.com/blog/2016/03/03/size-personalization/

Comments URL: https://news.ycombinator.com/item?id=11220389

Points: 1

# Comments: 0