Can #AI ascertain our personality traits from our ChatGPT history?
by Ingrid Fadelli @TechXplore_com Learn more: https://
bit.ly/4f8EiqI #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning #ML
RESEARCH
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Can AI determine personality traits from ChatGPT interaction history?
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The Shift from Deep Learning to Neurosymbolic AI
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Deep learning hit a wall. Neurosymbolic AI rescued it.
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Historical Research on LSTMs for Music Improvisation
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The agent also reimplemented the “Blues Improvisation” experiment by @douglas_eck and @SchmidhuberAI in 2002 which show that LSTMs can learn temporal structure in music.
— hardmaru (@hardmaru) 12 mai 2026
Finding temporal structure in music: Blues improvisation with LSTM recurrent networkshttps://t.co/2oU4iIcJEr pic.twitter.com/o4Eq4KqSGqThe agent also reimplemented the “Blues Improvisation” experiment by @douglas_eck and @SchmidhuberAI in 2002 which show that LSTMs can learn temporal structure in music. Finding temporal structure in music: Blues improvisation with LSTM recurrent networks https://
sferics.idsia.ch/pub/juergen/20
02_ieee.pdf
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The necessity of world models in AI systems
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might be the other way around. and it’s not totally clear what the term means. but you need a world model for any of these things.
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Recursion as the Next Scaling Law in AI
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Recursion Is The Next Scaling Law In AI! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
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Essential Research Papers for Mastering Transformers and LLMs
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Top 26 Essential Papers for Mastering LLMs and Transformers Implement those and you’ve captured ~90% of the alpha behind modern LLMs. Everything else is garnish. This list bridges the Transformer foundations with the reasoning, MoE, and agentic shift Recommended Reading
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Agentic Context Engineering: Evolving AI Context Over Time
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Instead of treating prompts as static, Agentic Context Engineering (ACE) explores how context can evolve over time through generation, reflection, and curation. Read the paper
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Can unreliable AI systems achieve AGI-level economic output?
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that’s actually part of the question – can you make a couple trillion with something unreliable/something short of AGI
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TorchLean Framework Released for Verified Neural Network Software
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TorchLean codebase is now available! TorchLean is a Lean 4 framework for verified neural-network software. It supports typed tensors, runnable training, graph IRs, verified autograd, Float32/IEEE semantics, CROWN / IBP-style verification, certificate checking, PyTorch interop,
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Research Preview of Real-Time Voice Interaction Models Announced
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THINKING MACHINES : Research preview of a new family of realtime voice models have been announced! > Today, we’re announcing a research preview of interaction models: models that handle interaction natively rather than through external scaffolding. > Our research preview