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#ais

1 post1 participant0 posts today

Me to local-run exaone3.5:32b "write a #QuickBasic program to animate a white square moving from left to right repeatedly"

Most #coding #AIs fuck up #QBASIC code pretty bad. This one did better than most I've tried. On the Left is what it spat out, and on the Right is how I fixed it.

Some shit code nonetheless.

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...
Replied in thread

@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)

Replied in thread

@MattMcNeilShow @mnreformer
#Minnesota needs to know that Governor #TimWalz's budget for next year includes a 50% cut in aid to counties for #AquaticInvasiveSpecies prevention.
This is huge, with a devastating impact to #Minnesotans.
Counties account for 90% of the actual work in preventing the spread of #AIS. This will torpedo decades of effort. Minnesota has been a leader in preventing the spread of #InvasiveSpecies and this is a step back when we need to lean in.
dl-online.com/news/local/count.

Detroit Lakes Tribune · Counties alarmed about potential 50% state cut to aquatic invasive species preventionBy Nathan Bowe

It's really effing obvious LLMs are a con trick:

If LLMs were actually intelligent, they would be able to just learn from each other and would get better all the time. But what actually happens if LLMs only learn from each other is their models collapse and they start spouting gibberish.

LLMs depend entirely on copying what humans write because they have no ability to create anything themselves. That's why they collapse when you remove their access to humans.

There is no intelligence in LLMs, it's just repackaging what humans have written without their permission. It's stolen human labour.

#LLM#LLMs#AI

We don't get much traffic that uses #ais in the Gloucester docks, but there also isn't any coverage, vessels show some of the way up the canal then just stop updating.

Anyone else deployed an ais receiver?

Any good services to feed? All the ones I've looked at so far have got pretty aggressive tracking (vesselFinder has 135 vendors and 63 partners, marine tracker has 689 vendors and 635 partners!) and I'd rather not support a service like that.

In this paper researchers attempt to get LLM #AIs to correctly answer the question "Alice has N brothers and she also has M sisters. How many sisters does Alice’s brother have?"

Can confirm that "Notable exceptions are Claude 3 Opus and GPT-4 that occasionally manage to provide correct responses backed up with correct reasoning as evident in structured step by step explanations those models deliver together with solution."

arxiv.org/pdf/2406.02061

Had not seen this one:
"AI’s Ostensible Emergent Abilities Are a Mirage"

with the whole "#AIs will magically become more competent with more data because emergence" thing coming up now that the capabilities of AI systems are mediocre for most real world cases this is good to have as a link.

hai.stanford.edu/news/ais-oste

Stanford HAIAI’s Ostensible Emergent Abilities Are a MirageAccording to Stanford researchers, large language models are not greater than the sum of their parts.