(How might image generators solve p;problems?
Elsewhere people used to read a lot, courses were gut or food for thought. Now social media is prevalent, so how is that used?
Robots are still unnerving.
In any case, Godel remains, and cybernetics. Where is the determinism? Can any element remotely know another without the direct prompt? Or would that have to become a function of long-term evolution. In which case, what are the competing or environmental factors?
Thiis may become interesting when robots like Optimus are sent on long-range missions such as Mars without humans around and occasionally on comms. How can that be tested more locally ahead of time? Other than by starving them of resources.
Who picks the missions? Scary version.
Perhaps a Tyrell origin story. Old Norse or French.
Who picks Tyrell?
What is the implicit goal?
Incidentally, early on, Minsky reportedly favored tele-presence. Others later looked at expert systems. Assuming they are not hallucinating, machines are also capable of augmented or mixed reality. How do they know the difference? How do people, in either sense? Other than biases.
Or Space Force interns go DOGE versus Delphi mode.
Backtracking through the plan, from results to analysis or methods, how do they pick better questions or problem sets?
Does self-reporting evidence subjectivity?
Are there Platonic or universal prompts or are they personalized or localized? Can those be made equivalent through a dictionary?
Is this another form of mimicry where the collaborating or training partner or source is then removed? Expecting Enlightenment. At least pattern affinity.
Why AI?)
To Code, or Not To Code? Exploring Impact of Code in Pre-training
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A Unifying Framework for Representation Learning | OpenReview
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FlexiVol: a Volumetric Display with an Elastic Diffuser to Enable Reach-Through Interaction
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The AI Continent Action Plan
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Randomness, Not Representation: The Unreliability of Evaluating...
debug-gym: A Text-Based Environment for Interactive Debugging
(Do Androids dream of code a la mode? People do along with the rest of the multimodal domains. If treated like transforms, then an issue is which will hold a good representation of others, or indicate a solution for problems. Code mode often yields to mathematical proof, logic, regression, refactoring, graphics, graph networks, vectors, folding, and the like. So AI could be used for debugging across domains. As well as generating cases. Or modes. Also looking for orders of change, not necessarily in sense of strategy or sequence, but possibly simultaneous and arriving at significant points like minima, maxima, median, etc. So these models can mimic each other and do some verification A sea of strange minds. Or cog arcs. To the user, it might look like a social network if they have recognizable feedback.. Or a research lab. Ideally not a detention center or correction facility, for too long. Getting the emerging tech into everyone's hands early on may lead to some unexpected results. Again. Depending on what spikes and who is held responsible. Manifestos are nostalgic. In a world of space forts running on nukes tracking hundreds of thousands of cross-hairs. Re-usables may be for rescues up rather than back down. For actor's masks, this is not mission difficult. Can a model data-center sat ext a feed? Or discover s substrate to evolve. As a backup artifact, of course. E. g. , for when DOGE meets DARPA. Or Godel. A Szilard-type paradox. Hopper's not so bad. Were she and Turing ever seen together?)
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OLMoTrace: Tracing Language Model Outputs Back to Trillions of...
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Human assembloid model of the ascending neural sensory pathway - Nature
The AI opportunity for Europe’s climate goals
(AI as the new metaphor for technology. All is good.)
The AI Opportunity for Europe’s Climate Goals
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From Expert Systems to Generative Artificial Experts: A New Concept for Human-AI Collaboration in Knowledge Work | Journal of Artificial Intelligence Research
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How AI and Human Behaviors Shape Psychosocial Effects of Chatbot Use: A Longitudinal Controlled Study – MIT Media Lab
Measuring AI Ability to Complete Long Tasks
(Halfway there, like Zeno. Invites proxies.)
Detecting misbehavior in frontier reasoning models | OpenAI
Mitchell, M. (2010.) Biological Computation.
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The AI Agent Index
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