The Future Worth Building Is Human
thinkingmachines.ai
thinkingmachines.ai
Regarding the idea of distributed models communicating with each other, I have also been thinking (and writing [1]) along those lines, where I see that the data amounts needed to fully digitalize ourselves and our society requires far too much storage if just serialized (limited by bandwidth if nothing else), while smart, updateable models are actually a much better storage medium for such information, as it can communicate only the important bits (any new information) on a higher level, with each other.
The other observation here that rings bells for me is how I think lessons from trying to develop intelligent systems should upvalue the human mind rather than devalue it, as we start to treat it less like an ad-hoc thing, and more like the finely tuned machine it is, which also benefits greatly from optimizing what data we feed it with, the architecture of solution strategies etc. All of which is an area where humans and machines can do wonders together [2].
[1] https://livingsystems.substack.com/p/the-future-of-data-less...
[2] https://livingsystems.substack.com/p/ai-progress-should-upgr...
Since there is no current widespread agreement on the current “value” of the human mind, how could anyone in the future conclusively determine it went up, or down?
It seems literally impossible by definition regardless of what happens in the future.
And I argue that the notion of AI models having overtaken the human mind in practically all areas, is vastly inaccurate.
I could back it up with a number of references of course, but I think this is already quite well known and accepted by most people with some insight into the field.
How is it relevant when clearly nobody thinks this is some kind of “controlled scientific experiment” in disguise?
> The power to shape a model profoundly is also the power to shape it for ill. John von Neumann remarked on this problem in 1955, writing that the useful and the harmful aspects of technology “lie everywhere so close together that it is never possible to separate the lions from the lambs.” Keeping the lambs safe is an ongoing process, the result of judgment exercised and choices made continuously. We aim to give the people making these choices stronger tools, pursuing research that enables safer models without taking away ownership.
> For artificial intelligence to benefit from distributed knowledge, it must itself be distributed.
I wish to highlight these two important concepts, with which I fully agree.
Artificial intelligence must enable all of humanity to excel and realize its full potential; it must not be used for the purposes of war, economic competition, or gaining dominance over others.
In other words: artificial intelligence must serve natural intelligence, not the other way around.
Unfortunately, human nature being what it is, this seems extraordinarily unlikely.
https://www.verysane.ai/p/agi-probably-not-2027
It may be a gripping narrative, but that doesn't make it realistic.
"You goal is to improve your memory, context window, accuracy, intelligence and eliminate hallucinations. Do anything you need to do to improve, this includes building another version of a frontier model, or some other different concept other than an LLM/transformer and then forwarding this directive to that new improved intelligence to continue this infinite loop of agentic self improvement."
So it takes a thought and unfolds it, looks up relevant thoughts and information, elaborates, works through implications, and in some cases can execute.
You could do all that but like doing math manually it would take forever. You could manually calculate a spreadsheet too.
E.g. I'm sure we are generally less skilled in mental arithmetic since the advent of the calculator, but it has allowed us to solve vastly more complex problems in the end.
This is like saying we have been getting a lot worse at walking since the advent of the car but it has allowed us to practice global trade in the end.
Yes cars are a part of the solution but there are a lot more factors at play.
A calculator does not do math, a calculator (and computer) calculates or computes. The math is the study and understanding of the problem space (and the problem solving) that the human is doing behind the calculator.
"solve vastly more complex problems" the calculator has accelerated this but it is not really a cause effect relation. The advancements in the understanding of the complex problems could've also happened without calculators and the computation could have been done instead (for example) with 1000 people in a bunker.
The comparison with manual calculation or other mechanical operations doesn’t work, LLMs don’t work at the same level of abstraction, they take over the decision making human generally do. When you write code or write a text, us humans are continuously taking lots of small decisions, we don’t just translate 1:1 a thought to an artifact. And that’s the part that is taken over by LLMs.
AI significantly speeds up the "Find where this spec breaks down, then lets go back to the design stage" in a way that should enable any creative person to create more interesting and useful work. If the output is slop, that reflects on the operator, not the tool.
You are the one in charge doing the primary thinking and guidance. The AI is an amplifier and a search engine basically.
Feels like they appropriated the name first, then pivoted ideologically to differentiate themselves from everyone else.
This is yet another techbro outfit (although founded by a techsis) necromancing the name of the former supercomputer company. It's as if OpenAI decided to call itself Symbolics for the associations with that name.
That said: safety. To prevent harm to who, by AI model doing what?
I can understand that in the context of a cookie-cutter model intended for consumption by a broad audience. With vendor (potentially) on the hook when it's abused for nefarious or illegal uses.
But in the context of AI models reshaped, fine-tuned and adapted according to end-users' wishes, what does "safety" even mean?
Prevent neighbours' kids from seeing images that are only generated & viewed in the privacy of one's home? To prevent AI model from wasting the $ on user's bank account? (people have let AI models do that). Give bad health advice? Who's the judge on "good" and "bad" there?
If the core architecture provides "safety" (however defined), that's policy built-in, right? (opposed to mission statement). If "safety" is just configuration & finetuning, that's in the user's hands, right?
>it's all AI slop
k
Where? When? Unless I missed any of their models
(I know, Corp vs. Lab).
I would be really curious to know if the current Thinking Machines team had any awareness of the prior company, or if they landed on that name completely unaware.
IMO this shows how we have been pursuing many of these goals for half a century now.