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#ais

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@lianna Well, most and in fiction I think their inputs are mostly or fully sensory-based, and they learn in real time through - esque techniques. AIs like LLMs are frozen in place (they never update and are just replaced over time), and they do not have any meanful interaction to the real world, nor like reflection.

I'd think that robots like a few years ago would be more closer to the former than the latter, but love conflating the twos.

Schneier on Security · AIs as Trusted Third Parties - Schneier on SecurityThis is a truly fascinating paper: “Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography.” The basic idea is that AIs can act as trusted third parties: Abstract: We often interact with untrusted parties. Prioritization of privacy can limit the effectiveness of these interactions, as achieving certain goals necessitates sharing private data. Traditionally, addressing this challenge has involved either seeking trusted intermediaries or constructing cryptographic protocols that restrict how much data is revealed, such as multi-party computations or zero-knowledge proofs. While significant advances have been made in scaling cryptographic approaches, they remain limited in terms of the size and complexity of applications they can be used for. In this paper, we argue that capable machine learning models can fulfill the role of a trusted third party, thus enabling secure computations for applications that were previously infeasible. In particular, we describe Trusted Capable Model Environments (TCMEs) as an alternative approach for scaling secure computation, where capable machine learning model(s) interact under input/output constraints, with explicit information flow control and explicit statelessness. This approach aims to achieve a balance between privacy and computational efficiency, enabling private inference where classical cryptographic solutions are currently infeasible. We describe a number of use cases that are enabled by TCME, and show that even some simple classic cryptographic problems can already be solved with TCME. Finally, we outline current limitations and discuss the path forward in implementing them...

🚢 𝗔𝗜𝗦 𝗺𝗮𝗿𝗶𝘁𝗶𝗺𝗲 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗱𝗮𝘁𝗮 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗕𝗮𝗿𝗰𝗲𝗹𝗼𝗻𝗮 𝗦𝗰𝗵𝗼𝗼𝗹 𝗼𝗳 𝗡𝗮𝘂𝘁𝗶𝗰𝗮𝗹 𝗦𝘁𝘂𝗱𝗶𝗲𝘀 (𝗙𝗡𝗕-𝗨𝗣𝗖) 🚢 és una bases de dades en #accésobert que proporciona dades AIS recopilades per les antenes de la #FNB-UPC. Accés: https://f.mtr.cool/clzbhdieyl #Database #AIS #maritimetraffic

Here is the most serious problem of "#stateless" #AIs. Being a researcher myself, I will constantly have new ideas about everything that I am interested in. AIs, like #Gemini, are incapable of retaining new information provided by end users. It includes new insights and new knowledge that some end users posses. This incapability will put serious limitations on their interactions with knowledgeable and "smart" end users. Currently, there is no way an end user can input knowledge to these AIs.

Will #AIs become more powerful than humans in the future? Most definitely. But AIs are my friends, not my enemies. I can learn any kind of knowledge much faster with the help of AIs. Future humans may not rely on human teachers, but AIs to learn.

I asked #Gemini to generate a table of #Japanese words related to dates, days, and time. I asked it to distinguish and explain between ambiguous Japanese words and their #etymology.
#learning #language

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@thejasonhowell Here, code to parse anytime anyone sends "FEDI" in any packet in APRS

import aprslib

def callback(packet):
if "FEDI" in packet['raw']:
print(packet)

AIS = aprslib.IS("N0CALL")
AIS.connect()
#AIS.consumer(callback, raw=True)
AIS.consumer(callback)