Uploaded September 2024 | Updated September 2026, 1 week ago
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Prof. Mark Solms, a neuroscientist and psychoanalyst at the University of Cape Town, presents a radical challenge to mainstream consciousness research. Drawing on decades of clinical and experimental evidence -- from decorticated animals that retain emotional behavior to hydranencephalic children who display clear affective responses without a functional cortex -- Solms argues that consciousness originates not in the cerebral cortex but in ancient brainstem structures, particularly the reticular activating system and periaqueductal gray.
The conversation traces a sweeping intellectual arc from Spinoza's dual-aspect monism through Shannon's information theory to Karl Friston's free energy principle, building the case that feelings are the organism's fundamental means of monitoring its homeostatic state. Solms contends that the hard problem of consciousness only seems intractable because the field began with the wrong modality: vision, which is not intrinsically conscious, rather than affect, which is.
Tim Scarfe and Solms explore the implications for AI, the failures of behaviorism, the neuroscience of psychoactive substances and REM sleep, and Jaak Panksepp's SEEKING system as the dopaminergic engine of curiosity and exploration. The result is a compelling argument that understanding consciousness requires putting feelings back at the center of brain science.
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LINKS:
Full Transcript: app.rescript.info/share/e6521573ac5e4329ee715f768cf82b06
Download PDF transcript: app.rescript.info/api/public/sessions/c1459f338bba5d58/pdf
MLST is sponsored by Brave:
The Brave Search API covers over 20 billion webpages, built from scratch without Big Tech biases or the recent extortionate price hikes on search API access. Perfect for AI model training and retrieval augmentated generation. Try it now - get 2,000 free queries monthly at brave.com/api.
Prof. Mark Solms, a neuroscientist and psychoanalyst at the University of Cape Town, presents a radical challenge to mainstream consciousness research. Drawing on decades of clinical and experimental evidence -- from decorticated animals that retain emotional behavior to hydranencephalic children who display clear affective responses without a functional cortex -- Solms argues that consciousness originates not in the cerebral cortex but in ancient brainstem structures, particularly the reticular activating system and periaqueductal gray.
The conversation traces a sweeping intellectual arc from Spinoza's dual-aspect monism through Shannon's information theory to Karl Friston's free energy principle, building the case that feelings are the organism's fundamental means of monitoring its homeostatic state. Solms contends that the hard problem of consciousness only seems intractable because the field began with the wrong modality: vision, which is not intrinsically conscious, rather than affect, which is.
Tim Scarfe and Solms explore the implications for AI, the failures of behaviorism, the neuroscience of psychoactive substances and REM sleep, and Jaak Panksepp's SEEKING system as the dopaminergic engine of curiosity and exploration. The result is a compelling argument that understanding consciousness requires putting feelings back at the center of brain science.
---
LINKS:
Full Transcript: app.rescript.info/share/e6521573ac5e4329ee715f768cf82b06
Download PDF transcript: app.rescript.info/api/public/sessions/c1459f338bba5d58/pdf
![Language Models are Modelling The World [Nicholas Carlini]](https://i.ytimg.com/vi/n4ipEJ6uJ44/mqdefault.jpg "Language Models are Modelling The World [Nicholas Carlini]
Nicholas Carlini from Google DeepMind offers his view of AI security, emergent LLM capabilities, and his groundbreaking model-stealing research. He reveals how LLMs can unexpectedly excel at tasks like chess and discusses the security pitfalls of LLM-generated code.
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Transcript: https://www.dropbox.com/scl/fi/lat7sfyd4k3g5k9crjpbf/CARLINI.pdf?rlkey=b7kcqbvau17uw6rksbr8ccd8v&dl=0
TOC:
1. ML Security Fundamentals
[00:00:00] 1.1 ML Model Reasoning and Security Fundamentals
[00:03:04] 1.2 ML Security Vulnerabilities and System Design
[00:08:22] 1.3 LLM Chess Capabilities and Emergent Behavior
[00:13:20] 1.4 Model Training, RLHF, and Calibration Effects
2. Model Evaluation and Research Methods
[00:19:40] 2.1 Model Reasoning and Evaluation Metrics
[00:24:37] 2.2 Security Research Philosophy and Methodology
[00:27:50] 2.3 Security Disclosure Norms and Community Differences
3. LLM Applications and Best Practices
[00:44:29] 3.1 Practical LLM Applications and Productivity Gains
[00:49:51] 3.2 Effective LLM Usage and Prompting Strategies
[00:53:03] 3.3 Security Vulnerabilities in LLM-Generated Code
4. Advanced LLM Research and Architecture
[00:59:13] 4.1 LLM Code Generation Performance and O(1) Labs Experience
[01:03:31] 4.2 Adaptation Patterns and Benchmarking Challenges
[01:10:10] 4.3 Model Stealing Research and Production LLM Architecture Extraction
REFS:
[00:01:15] Nicholas Carlini’s personal website & research profile (Google DeepMind, ML security) - https://nicholas.carlini.com/
[00:01:50] CentML AI compute platform for language model workloads - https://centml.ai/
[00:04:30] Seminal paper on neural network robustness against adversarial examples (Carlini & Wagner, 2016) - https://arxiv.org/abs/1608.04644
[00:05:20] Computer Fraud and Abuse Act (CFAA) – primary U.S. federal law on computer hacking liability - https://www.justice.gov/jm/jm-9-48000-computer-fraud
[00:08:30] Blog post: Emergent chess capabilities in GPT-3.5-turbo-instruct (Nicholas Carlini, Sept 2023) - https://nicholas.carlini.com/writing/2023/chess-llm.html
[00:16:10] Paper: “Self-Play Preference Optimization for Language Model Alignment” (Yue Wu et al., 2024) - https://arxiv.org/abs/2405.00675
[00:18:00] GPT-4 Technical Report: development, capabilities, and calibration analysis - https://arxiv.org/abs/2303.08774
[00:22:40] Historical shift from descriptive to algebraic chess notation (FIDE) - https://en.wikipedia.org/wiki/Descriptive_notation
[00:23:55] Analysis of distribution shift in ML (Hendrycks et al.) - https://arxiv.org/abs/2006.16241
[00:27:40] Nicholas Carlini’s essay “Why I Attack” (June 2024) – motivations for security research - https://nicholas.carlini.com/writing/2024/why-i-attack.html
[00:34:05] Google Project Zero’s 90-day vulnerability disclosure policy - https://googleprojectzero.blogspot.com/p/vulnerability-disclosure-policy.html
[00:51:15] Evolution of Google search syntax & user behavior (Daniel M. Russell) - https://www.amazon.com/Joy-Search-Google-Master-Information/dp/0262042878
[01:04:05] Rust’s ownership & borrowing system for memory safety - https://doc.rust-lang.org/book/ch04-00-understanding-ownership.html
[01:10:05] Paper: “Stealing Part of a Production Language Model” (Carlini et al., March 2024) – extraction attacks on ChatGPT, PaLM-2 - https://arxiv.org/abs/2403.06634
[01:10:55] First model stealing paper (Tramèr et al., 2016) – attacking ML APIs via prediction - https://arxiv.org/abs/1609.02943")
