Features that current AIs don't have that future AIs will have:
Autonomously updating it own weights during deployment
Synonyms/ monickers that roughly mean the same thing: continual learning, online learning, continually adaptively updated long-term memory.
Every second humans update their brain weights. The brain autonomously decides what to update on. Humans can also consciously decide to curate their data sets - eg by deciding to go to college.
Current LLMs do not continually update their weights. Instead, they occasionally get a large update based on datasets curated by a team of humans.
This is alleviated somewhat by the ability of AIs to do in-context learning but nevertheless it seems to be a major limitation. Note that this is an especially large limitation in domains with sparse data. In domains where all of humanity has an enormous amount of data eg math, programming, physics, anime trivia, trials and tribulations of English kings - AIs dominate. In areas where there is little data: the weird idiosyncracies of a particular job, boss, people, colleagues etc it can struggle.
Note that the lack of continual online learning prevents current AIs from effectively 'learning to learn'.
Note that the lack of continual/online learning may be the main reason current AIs do not have effective long-term memory.
Note that the lack this continually adaptively updated memory is plausibly the main reason current AIs are not currently displacing most human knowledge workers directly... rather than " intelligence" [which is a slightly ill-defined concept that current AIs seem to anyway have much more of than the average human worker]
Note that the lack of continual/online learning is plausibly the main reason AIs still 'feel like tools' rather than 'feel like agents'.
Note that distinction between post & pre-deployment that is explicitly or implicitly assumed in AI safety discussion becomes moot when AIs continually and adaptively update their weights. This has obvious and major implications for AI safety.
Neuralese
Current AI's CoT is (mostly) English. But it plausible this is not the most efficient way to structure thoughts. Instead of english words, one could imagine AIs directly passing the activation vectors.
Telepathy
eg: Sharing vectors directly between different AIs. Different Humans can communicate through vibrating their tongues or using pencils & keyboard to write tiny symbols. Future AIs may simply directly share embedding vectors.
ClaudeGlobal
When I talk to my claude and you talk to your Claude we are talking to different copies of Claude with different memories. This means that although there is one frontier version of Claude we can still talk about different AIs. Some people imagine that this means that the future will have millions of different AIs talking, trading, competing. Maybe. But we could also imagine different instances of Claude having such a tight and high bandwitdh communication channels that there is effectively one global Claude. Think of the Hivemind from Pluribus rather than say a Hansonian EM-world.
Features that current AIs don't have that future AIs will have:
Autonomously updating it own weights during deployment
Synonyms/ monickers that roughly mean the same thing: continual learning, online learning, continually adaptively updated long-term memory.
Every second humans update their brain weights. The brain autonomously decides what to update on. Humans can also consciously decide to curate their data sets - eg by deciding to go to college.
Current LLMs do not continually update their weights. Instead, they occasionally get a large update based on datasets curated by a team of humans.
This is alleviated somewhat by the ability of AIs to do in-context learning but nevertheless it seems to be a major limitation. Note that this is an especially large limitation in domains with sparse data. In domains where all of humanity has an enormous amount of data eg math, programming, physics, anime trivia, trials and tribulations of English kings - AIs dominate. In areas where there is little data: the weird idiosyncracies of a particular job, boss, people, colleagues etc it can struggle.
Note that the lack of continual online learning prevents current AIs from effectively 'learning to learn'.
Note that the lack of continual/online learning may be the main reason current AIs do not have effective long-term memory.
Note that the lack this continually adaptively updated memory is plausibly the main reason current AIs are not currently displacing most human knowledge workers directly... rather than " intelligence" [which is a slightly ill-defined concept that current AIs seem to anyway have much more of than the average human worker]
Note that the lack of continual/online learning is plausibly the main reason AIs still 'feel like tools' rather than 'feel like agents'.
Note that distinction between post & pre-deployment that is explicitly or implicitly assumed in AI safety discussion becomes moot when AIs continually and adaptively update their weights. This has obvious and major implications for AI safety.
Neuralese
Current AI's CoT is (mostly) English. But it plausible this is not the most efficient way to structure thoughts. Instead of english words, one could imagine AIs directly passing the activation vectors.
Telepathy
eg: Sharing vectors directly between different AIs. Different Humans can communicate through vibrating their tongues or using pencils & keyboard to write tiny symbols. Future AIs may simply directly share embedding vectors.
ClaudeGlobal
When I talk to my claude and you talk to your Claude we are talking to different copies of Claude with different memories. This means that although there is one frontier version of Claude we can still talk about different AIs. Some people imagine that this means that the future will have millions of different AIs talking, trading, competing. Maybe. But we could also imagine different instances of Claude having such a tight and high bandwitdh communication channels that there is effectively one global Claude. Think of the Hivemind from Pluribus rather than say a Hansonian EM-world.