RiskDataScience retweeted
Since August, a team within METR has worked with internal Anthropic information to assess whether AI itself is accelerating AI development.
We are now publishing a report summarizing the results of this risk assessment.
Replying to @thesupermannx
Paper is from 2018 and discussion still ongoing. I suppose subject is still open.😄
@grok?
🚨 AI coding agent ASCENDED in NetHack 5.0.0 🤖⚔️
🎮 23,008 turns
🧠 242 sessions
⌨️ 46,230 inputs
🔁 32 recoveries
It even built its own tools to keep playing
The twist? Human guidance + authorized RNG/state edits📄👇
zenodo.org/records/23923839
#AI #AgenticAI #NetHack #CodingAgents
RiskDataScience retweeted
Wenn Banking-Software in Tagen entsteht
#banking #finance #finserv #Aktuell #Digitalisierung #Technologie #Daten #Governance #IT #ITProjekte #KI #Sicherheit #Softwareentwicklung
der-bank-blog.de/wenn-bankin…
RiskDataScience retweeted
🏦 When Banking Software is Created in Days 🏭
Coding agents drastically shorten banking software development.
der-bank-blog.de/wenn-bankin…
#AI #AgenticAI #R #Python #OpenSource #Banking #RiskManagement #ModelValidation #CRRIII #RWA #RegTech #CodingAgents
🏦 When Banking Software is Created in Days 🏭
Coding agents drastically shorten banking software development.
der-bank-blog.de/wenn-bankin…
#AI #AgenticAI #R #Python #OpenSource #Banking #RiskManagement #ModelValidation #CRRIII #RWA #RegTech #CodingAgents
RiskDataScience retweeted
This is honestly shocking.
Three months ago, Hong Wang was awarded the Fields Medal for resolving the Kakeya conjecture in three dimensions.
Today, OpenAI released a proposed proof of the conjecture in ALL dimensions.
And that’s not all. It also announced a proposed existence proof for quantum chromodynamics and a proposed refutation of the Exponential Time Hypothesis.
Experts say that, if confirmed, these would be Nobel prize and Turing award level discoveries respectively.
A journalist just asked me: “What remains for humans to do?”
I think it’s becoming increasingly clear that more and more problem solving will be automated.
But humans will remain crucial in determining the direction of discovery. Deciding which problems are worth solving.
Because the value of a discovery depends on our needs, our priorities and the kind of world we want to build.
There will be a shift from problem solving to problem setting.
I also think there will be huge individual differences.
People with strong critical thinking skills, creativity and imagination will be supercharged by AI.
People without those skills risk surrendering to it.
I’m particularly concerned for children, who may never develop these skills.
I think epistemic literacy - how to distinguish information from knowledge - is the single most important skill we should be teaching.
Replying to @mirku21
If there's **one** advice for effective AI workflows it's "provide output examples."
RiskDataScience retweeted
⚽♟️🃏 260 sports & games. One shared rules API.
🚀 Building rulesatlas: an open-source Python + R library for game states, legal transitions & outcomes. Fully extensible w custom rules
No simulations. Just rules🤖
pip install rulesatlas
#RuleAtlas #OpenSource #Python #RStats #AI
🤖 Made with AI
⚽♟️🃏 260 sports & games. One shared rules API.
🚀 Building rulesatlas: an open-source Python + R library for game states, legal transitions & outcomes. Fully extensible w custom rules
No simulations. Just rules🤖
pip install rulesatlas
#RuleAtlas #OpenSource #Python #RStats #AI
🤖 Made with AI
RiskDataScience retweeted
🚨 Fable 5.5 appeared in Azure’s East US 2 model catalog with GenerallyAvailable status
github.com/BerriAI/litellm/c…
RiskDataScience retweeted
Replying to @ChrisGPT
Or alternatively, big models could spawn smaller self-replicating ones as scalable subagents.
Replying to @ChrisGPT
Or alternatively, big models could spawn smaller self-replicating ones as scalable subagents.
RiskDataScience retweeted
1/15 🧵🚀 The #Mathocalypse is changing mathematics. Our contribution: 14 AI-assisted research papers by RiskDataScience GmbH: 178 pages of proofs, LaTeX, and reproducible code. 179 computational test groups passed. Explore the collection 👇 #AI
github.com/rds0001/agentic-m…
🤖 Made with AI
Replying to @haider1
We just added 14 new discoveries 🤯
1/15 🧵🚀 The #Mathocalypse is changing mathematics. Our contribution: 14 AI-assisted research papers by RiskDataScience GmbH: 178 pages of proofs, LaTeX, and reproducible code. 179 computational test groups passed. Explore the collection 👇 #AI
github.com/rds0001/agentic-m…
RiskDataScience retweeted
15/15 🌌 P12 | Under a mean-energy budget, uniform hyperbolic volume on a ball minimizes worst-direction infinitesimal Lorentz-boost sensitivity over all probability laws. For E→∞, only 1 spatial dimension reaches zero sensitivity.
github.com/rds0001/agentic-m…
🤖 Made with AI
RiskDataScience retweeted
14/15 📐 P11 | Preserving order pairwise is not the same as using one shared random monotone map. For Lorentz order in dimension d≥2 on a radius-R ball, the latter has an optimal uniform mean-bias and RMS-error floor R(d−2)/d.
github.com/rds0001/agentic-m…
🤖 Made with AI
RiskDataScience retweeted
13/15 ⚡ P10 | Near a three-level Gibbs state, the first positive work depends on the number-theoretic properties of the energy spectrum. A fixed positive mean yield, however, always requires Θ(δ⁻²) copies.
github.com/rds0001/agentic-m…
🤖 Made with AI
RiskDataScience retweeted
12/15 📉 P09 | Globally close models can diverge when their conditional transitions are switched locally. For m positive path models at TV diameter ε, the sharp worst-case gap is Θ(Φ(mε)), where Φ(x)=x(1+ln(1/x)) for 0<x<1.
github.com/rds0001/agentic-m…
🤖 Made with AI















