Don't believe the AI doom hype - researchers understand and steer models more than ever before using techniques like reinforcement learning from human feedback.

Human intelligence is a quality of mind with functions for memory and qualifiers. It exceeds LLMs. It also refutes panpsychism that that everything is mind-like

Discover insights into how AI compares to human emotions and memory functions in Long Language Models (LLMs).

Discover innovative approaches to enhance large language models by incorporating new mathematical functions and correction layers, inspired by human cognition.

Penalty-tuning for LLMs: Where they can be penalized for misuses or negative outputs, within their awareness, as another channel for AI safety and alignment.

AI doomerism is a religion, both millenarianism apocalypticism, to fill the god-sized gap in AI researchers.

Questions that may be essential to AI regulation for now may include current and potential misuses, sources of those misuses, and why they are possible

What can LLMs do for prompt and quality sleep, writing with the non-dominant hand, retention when learning a new language and for new marketplaces for commerce?

One easy-to-identify issue, especially with the internet—in recent decades—is that development has been ahead of safety.

What are all the combinations of successful jailbreaks and prompt injection attacks against AI chabots that were different from what it would normally expect?

What can be done about bias—technically—that can be made available on a list, for those interested to go at it, could be a more important open source path.

it is theorized here that electrical and chemical signals are the fundamental unit of the nervous system, in contrast to the neuron, declared by Nature.

Geoffrey Hinton's Cambridge lecture explores digital vs. biological intelligence and his evolving views on AI's future and ethical implications.

Discussing the concept of Human In The Loop.

How is human intelligence safe? Or what is the safety of human intelligence, before thinking of AI safety? Human intelligence is safe by human affect.

How can AI have affect? How can this affect become the basis for AI alignment, such that whenever it is misused, it can know that there is a penalty for it?

Examining AI safety like peeling layers off an onion.

Anthropic CEO, Dario Amodei talked about his predictions with Lex Fridman: Expect AGI by 2027, Scaling works, AI safety, Mechanistic Interprability (mind of AI

How the mind works [of human and of AI] is not by labels, like induction or deduction, but by components, their interactions, and features.