[LINK] Australian Government Trial of Generative AI for Law, Education, Health, and Aged Care
David
dlochrin at aussiebb.com.au
Mon Mar 11 12:18:09 AEDT 2024
On 9/03/2024 3:35 pm, Roger Clarke wrote:
> On 9/3/2024 13:33, David wrote:
>> Personally, I first came across neural networks in the late 60's when my Supervisor at the time was experimenting with them on a very slow common-or-garden engineering computer. But we could still see the model learning
> Where 'the model learning' =
> 'model-parameters being adjusted by software on the basis of pre-defined aspects of the data-inputs'
>
> I don't want to play down the significance, because it was indeed a generational change in the mode of software development. But it helps to remain balanced about artefacts' capabilities when anthropomorphic terms are avoided.
The neural-network model I'm talking about was a pretty basic one (it was the late-1960's after all!) which adapted to recognising basic shapes from "fuzzy" data. It embodied some principles of the wetware between our ears such as sensors (nerve endings) and threshold-logic (synaptic action potentials), but it had nothing to do with software development.
If anything, it may have been more akin to the small neural network in our eyes which pre-processes images, so that the number of nerve fibres going to the brain is only around 25% (from memory?) of the number of retinal sensors. I guess that improves the S/N ratio (:-).
Believe me, I'm very aware of the dangers inherent in using anthropomorphic terms in any discussion of AI. The very expression "artificial intelligence" is misleading to begin with, and probably leads many people to ascribe cognitive powers to such systems which they simply do not possess. It's easy to see how this might lead to accidents involving "self-driving" cars and more spectacular & disastrous mis-applications of AI such as the fictional one foreseen by Arthur C. Clarke.
>> I wrote in 1990-91, in 'A Contingency Approach to the Application Software Generations', in s.8 (The Application Software Generations as Levels of Abstraction), at:
>> http://www.rogerclarke.com/SOS/SwareGenns.html#ASGLA
>>
>> The shape of at least one further generation is emerging from the mists. Connectionist or neural machines, whether implemented in software or using massively parallel hardware architectures, involve a conception of knowledge yet more abstract than knowledge-bases containing production rules.
>>
>> [...]
>
> 30 years later, I say it a little differently from that. But that did manage to build in the notions of (merely) empirical, abdication of responsibility / decision factory [i.e. decision system, not decision support system], and maintenance operative not teacher.
>
> But in the late 60s, I was very prosaically writing a little Fortran (before it even had version-numbers) and was shortly going to embark on writing rather more code in that deeply intellectual language, COBOL. I don't think I heard of neural networks until a *long* time after that.
Fortunately, I was never required to write COBOL, but I did do some useful stuff in Fortran IV at dear old AWA Research Labs - my first real job. And Fortran is still going, though it's now evolved to a modern language supporting reentrant code, patterns, object-oriented code, etc.
> For Christmas, my kids, ever-desperate to avoid resorting to socks or handkerchiefs, gave me a T-shirt with these words emblazoned on it:
>
> 'I'm sorry Dave. I'm afraid I can't do that.'
I'd like to locate a more dressy T-shirt showing a "Wanted Dead & Alive" poster for Schroedinger's Cat!
_David Lochrin_
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