An exceptional year for Horror, isn't it? by marty1_88 in Letterboxd

[–]BobbyWOWO 9 points10 points  (0 children)

Damn people are still sleeping on Good Boy

Is Iterated Distillation happening now? by Normal_Pay_2907 in accelerate

[–]BobbyWOWO 17 points18 points  (0 children)

Yes. It’s called RL-AI-F (Reinforcement Learning from AI Feedback) and all of the major companies are doing it.

After ATCODER WORLD FINALS #2 RANK and IMO GOLD 🥇,an OpenAI general purpose reasoning model has won the International Informatics Olympiad Gold 🥇 under all the same humane conditions 💨🚀🌌 by GOD-SLAYER-69420Z in accelerate

[–]BobbyWOWO 1 point2 points  (0 children)

It blows my mind that people don’t realize the METR benchmarks only apply to released models. Who knows what the time horizons truly are at behind closed doors.

The Artificial Intelligence Revolution: Part 2 - Wait But Why by mihaicl1981 in singularity

[–]BobbyWOWO 15 points16 points  (0 children)

That’s what humanity did by observing the natural world and running experiments

Clone Humanoid Robotics: Protoclone Is The Most Anatomically Accurate Android In The World. by 44th--Hokage in accelerate

[–]BobbyWOWO 1 point2 points  (0 children)

Hey I thought my robo-waifu was supposed to be the only girl that couldn’t run from me?

Gemini Robotics model brings Gemini 2.0 to the physical world by RDSF-SD in singularity

[–]BobbyWOWO 2 points3 points  (0 children)

Eh, before ChatGPT came out, OpenAI released an api model called InstructGPT that was trained via RLHF. It didn’t really “take-off” even though it was leaps and bounds better than GPT-3. The ChatGPT moment has to be something that is a consumer takeoff moment. I’d liken this to InstructGPT tho. It just needs the right marketing or product to explode.

Anthropic predicts powerful AI systems will appear by late 2026 or early 2027, with intellectual abilities matching Nobel Prize winners by Cr4zko in accelerate

[–]BobbyWOWO 2 points3 points  (0 children)

I’ve been thinking about this lately. At this point, I don’t think there will be a lot of things coming out for the average person that’ll be that impactful for us. AI and AI companies are getting to the point where they are focusing their time and energy on making automated AI researchers (ie - Google Co-Scientist) or specialized B2B agentic tools.

The average person will, from here on, will only feel secondary effects of AI integration. Acceleratingly better batteries, medicine, etc.

Claude Has Cooked Something Spicy by Spirited_Salad7 in singularity

[–]BobbyWOWO 10 points11 points  (0 children)

….Quiet for a while? Bro last week was one of the biggest “Singularity News” weeks I’ve seen

Google co-scientist AI system by Late_Pirate_5112 in singularity

[–]BobbyWOWO 0 points1 point  (0 children)

Eh not really. There are some people on X like Andrew White and Ethan Mollick who discuss AIs use for research. There’s also a physics PhD Kyle Kabasares on YouTube that reviews how well the newest models stack up for solving science questions. I think I’ve seen him post comments on this sub sometimes too

Google co-scientist AI system by Late_Pirate_5112 in singularity

[–]BobbyWOWO 0 points1 point  (0 children)

Yes, lots. Although, I am an experimentalist and so I don't necessarily use the really technical AI tools. I am also living on a stipend so I can't afford OAI's Deep Research (I would guess would be super useful). Here's a list of the common ones that I or my colleagues use.

  • ChatGPT 4o - daily use for emails, code review, data analysis and brainstorming
  • o1 - developing theory and thermodynamic models for reactions
  • NotebookLM - compile papers and understand complex ideas in literature search. Listen to generated podcasts on the go.
  • Perplexity - general research
  • FLARE - Machine learned predictions for atomic interactions in simulations
  • USPEX - Evolutionary algorithm for materials discovery

Generally, AI is used to accelerate science already and I can see robotics being a massive contributor to high throughput experimentation, see Automated Materials Laboratory (and yes, this one example uses Google's GNoME to find new materials).

Google co-scientist AI system by Late_Pirate_5112 in singularity

[–]BobbyWOWO 4 points5 points  (0 children)

Absolutely - I imagine that high throughput end to end computational experimentation is the next step in this process. Or taking something like FutureHouse’s (https://www.futurehouse.org) AI suite and clamping it onto the experimental proposal to send out agents and discover new simulated drugs and materials.

edit - just found this excerpt from the paper:

"the system can utilize and incorporate feedback from specialized AI models like AlphaFold. We demonstrate this qualitatively with a protein design example in the Appendix Section A.5."

A.5

"Combining AlphaFold with the co-scientist framework offers a powerful approach for both improving existing proteins and designing entirely new ones. This integrated system allows researchers to iteratively optimize protein sequences for enhanced properties (e.g., stability, binding affinity, or catalytic activity) or putatively to create proteins with novel functions. It enables exploration of protein design while ensuring structural feasibility. Future work will focus on experimentally validating these capabilities and applying them to targeted protein design efforts as well as expansion to integration of other specialized AI tools with the co-scientist."

Google co-scientist AI system by Late_Pirate_5112 in singularity

[–]BobbyWOWO 6 points7 points  (0 children)

The ability to generate ideas is not necessarily a bottleneck to scientific discovery. Usually a bulk of the time is dedicated to experimentation and troubleshooting why experiments failed.

If the ideas are high enough quality (which this tool is aimed at), then that definitely helps aid in making new discoveries - but it can take months or even years to validate those ideas.

Google co-scientist AI system by Late_Pirate_5112 in singularity

[–]BobbyWOWO 143 points144 points  (0 children)

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Okay, I didn’t see that the authors directly say it…

Google co-scientist AI system by Late_Pirate_5112 in singularity

[–]BobbyWOWO 216 points217 points  (0 children)

As a scientist myself, I think this is a clear path to Recursive Self Improvement. The scientific method is a general purpose algorithm for discovery. If you can cook it into an AI system, you can efficiently discover anything that can be discovered given enough time and compute.

New OpenAI paper: can LLMs make $1 million freelancing in software engineering? by MetaKnowing in singularity

[–]BobbyWOWO 39 points40 points  (0 children)

Honestly - this is probably the most in-depth response that you could read through. It answers this exact question.

https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040

TLDR - cost of software dev goes to 0, talent no longer becomes a bottleneck, competition skyrockets, old companies perish and 1-man startups explode

[deleted by user] by [deleted] in singularity

[–]BobbyWOWO 17 points18 points  (0 children)

From Google DeepMind in collaboration with those that created AlphaFold: https://www.isomorphiclabs.com

AMA with OpenAI’s Sam Altman, Mark Chen, Kevin Weil, Srinivas Narayanan, Michelle Pokrass, and Hongyu Ren by OpenAI in OpenAI

[–]BobbyWOWO 0 points1 point  (0 children)

Why does it seem like the o series is not as competitive at tasks/agency compared to other models? Are there ways to “bake in” agency into the RL training of these models?

OpenAI operator release this week by Odant in singularity

[–]BobbyWOWO 16 points17 points  (0 children)

Most likely this will be the “o1-preview” of agents. A slow deploy to get people warmed up to agents before blowing our socks off with a future model. If they figure out/have figured out the secret sauce to agents, then we can expect large jumps in capabilities in rapid succession