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Re: [nexa] Can Large Language Models reason?
by maurizio lana Oct. 13, 2023

Oct. 13, 2023

solo a me i msg di Giuseppe Attardi compaiono /talvolta/ così? con il corpo del messaggio messo in attachment htm linkato Maurizio Il 13/10/23 09:21, nexa-request(a)server-nexa.polito.it ha scritto: > Message: 4 Date: Fri, 13 Oct 2023 09:21:12 +0200 > From: Giuseppe Attardi <attardi(a)di.unipi.it> > To: Daniela Tafani <daniela.tafani(a)unipi.it> > Cc: nexa <nexa(a)server-nexa.polito.it> > Subject: Re: [nexa] Can Large Language Models reason? > Message-ID: <F38BCF6D-716C-423D-8A9D-5AB64995EFE8(a)di.unipi.it> > Content-Type: text/plain; charset="utf-8" > An HTML attachment was scrubbed... > URL: > <http://server-nexa.polito.it/pipermail/nexa/attachments/20231013/26c59651/a…> > > ------------------------------ > > Subject: Digest Footer > _______________________________________________ > nexa mailing list > nexa(a)server-nexa.polito.it > https://server-nexa.polito.it/cgi-bin/mailman/listinfo/nexa > ------------------------------ ------------------------------------------------------------------------ roughneck and rudeness we should be using, on the ones who practice wicked charms for the sword and the stone, bad to the bone battle's not over even when it's won youssou n'dour & nene cherry, 7 seconds ------------------------------------------------------------------------ Maurizio Lana Università del Piemonte Orientale Dipartimento di Studi Umanistici Piazza Roma 36 - 13100 Vercelli

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se lo dice lui..
by Stefano Quintarelli Oct. 13, 2023

Oct. 13, 2023

User what is understanding ? ChatGPT Understanding is the ability to comprehend or grasp the meaning of something, typically through cognitive processes like reasoning, analysis, and the assimilation of information. It involves making sense of information, concepts, or situations, often by connecting new information to existing knowledge or experiences. Understanding can manifest in various forms, including: Conceptual understanding: This is the ability to grasp the underlying principles or ideas related to a subject or topic. Contextual understanding: Understanding how something fits into a broader context or how it relates to other concepts or elements. Practical understanding: The ability to apply knowledge and concepts effectively in real-world situations. Emotional understanding: This involves empathizing with the feelings and perspectives of others, which is often important for interpersonal relationships and communication. Understanding is a fundamental aspect of human cognition, and it plays a crucial role in learning, problem-solving, decision-making, and effective communication. It involves more than just memorizing facts; it's about making sense of information and being able to use that understanding to navigate the world. User do you understand ? ChatGPT I can process and analyze information based on the text input you provide, but I don't have emotions or consciousness like humans do. So, while I can provide information and explanations, I don't have the capacity for personal understanding or comprehension in the way humans do. My responses are generated based on patterns in the data I was trained on and the text input I receive. If you have a specific question or need information on a topic, please feel free to ask, and I'll do my best to provide a helpful response.

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Can Large Language Models reason?
by Giuseppe Attardi Oct. 13, 2023

Oct. 13, 2023

Secondo Peter Norvig stanno addirittura raggiungendo la AGI: https://www.noemamag.com/artificial-general-intelligence-is-already-here/ — Beppe > On 12 Oct 2023, at 15:00, nexa-request(a)server-nexa.polito.it wrote: > > From: Daniela Tafani <daniela.tafani(a)unipi.it <mailto:daniela.tafani@unipi.it>> > To: "nexa(a)server-nexa.polito.it <mailto:nexa@server-nexa.polito.it>" <nexa(a)server-nexa.polito.it <mailto:nexa@server-nexa.polito.it>> > Subject: [nexa] Can Large Language Models reason? > Message-ID: <c57ae4ebaa76494ea2f7ec1ef19b3646(a)unipi.it <mailto:c57ae4ebaa76494ea2f7ec1ef19b3646@unipi.it>> > Content-Type: text/plain; charset="iso-8859-1" > > Melanie Mitchell, Can Large Language Models reason? > > https://aiguide.substack.com/p/can-large-language-models-reason > > (non lo copio di seguito perchè immagini e formattazione servono) >

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Re: [nexa] Can Large Language Models reason?
by Giuseppe Attardi Oct. 13, 2023

Oct. 13, 2023

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Can Large Language Models reason?
by Daniela Tafani Oct. 13, 2023

Oct. 13, 2023

Melanie Mitchell, Can Large Language Models reason? https://aiguide.substack.com/p/can-large-language-models-reason (non lo copio di seguito perchè immagini e formattazione servono)

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Even Google Insiders Are Questioning Bard AI Chatbot’s Usefulness (una soluzione in cerca di un problema)
by Daniela Tafani Oct. 12, 2023

Oct. 12, 2023

https://www.bloomberg.com/news/articles/2023-10-11/google-insiders-question… Domanda: qual è la sfida più grande per la vostra azienda, riguardo a questo prodotto? Risposta: capire a cosa serva "can you tell us whats one of the biggest challenges the team is trying to tackle? perhaps a feature that you want to roll out some" CathyfromGoogle: “I think form the biggest challenge I’m still thinking of: what are LLMs truly useful for, in terms of helpfulness? Like really making a difference. TBD!” J. Weizenbaum, 1985: "the computer has almost since its beginning been basically a solution looking for a problem".

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Re: [nexa] IA, lavoro, immaginari
by Giuseppe Attardi Oct. 12, 2023

Oct. 12, 2023

> On 12 Oct 2023, at 12:00, <nexa-request(a)server-nexa.polito.it> <nexa-request(a)server-nexa.polito.it> wrote: > > From: "M. Fioretti" <mfioretti(a)nexaima.net <mailto:mfioretti@nexaima.net>> > To: nexa(a)server-nexa.polito.it <mailto:nexa@server-nexa.polito.it> > Subject: Re: [nexa] IA, lavoro, immaginari > Message-ID: <ZSe3bmA66wUNz5Zr(a)nexaima.net <mailto:ZSe3bmA66wUNz5Zr@nexaima.net>> > Content-Type: text/plain; charset=utf-8 > > On Thu, Oct 12, 2023 10:26:32 AM +0200, Giuseppe Attardi wrote: > >> il termine spregiativo di “stochastic parrot” che è stato affibbiato >> ai LLM da Timnit Gebru e colleghi. L’articolo è molto controverso ed >> è costato a Gebru il posto a Google. Nell’articolo si sostiene che: >> >> An LM is a system for haphazardly stitching together sequences of linguistic >> forms it has observed in its vast training data, according to probabilistic >> information about how they combine, but without any reference to meaning: a >> stochastic parrot. >> >> Questa affermazione è superficiale e inesatta, perché non tiene conto di alcune >> cose: >> >> 1. Alla base dei LLMs ci sono i word embedding, un modo per assegnare un >> significato alle parole, un problema che ha eluso la filosofia e la linguistica >> per due millenni e che il Deep Learning ha risolto. Questo è quanto afferma >> Hinton in proposito: >> “Many people who think it’s just statistics are thinking in terms of program >> models or counting the co-occurrence frequencies of words. We think this >> process of creating features of the embeddings and then interactions between >> features is actually understanding. Once you’ve taken the raw data of symbol >> strings and you can now predict the next symbol not by things like trigrams, >> but the huge number of features interacting in very complicated way to predict >> the features of the next word and from that make a prediction about the >> probability of the next word, the point is that is understanding, at least I >> believe that is understanding. I believe that is what our brains are doing. But >> that’s an issue to be discussed by the research community and it would be great >> if we could convince people that they are not just stochastic parrots.” > > questa cosa mi confonde un po': a chi/a chi sta parlando Hinton? È tratto da una conversazione con Andrew Ng, che si dichiara d’accordo. > > Perche' le critiche a certi discorsi vengono da quelli che non hanno > alcun bisogno di essere convinti di non essere semplici pappagalli, ma > sono LORO a dire di essere molto di piu'. A dire che il cervello umano > e' solo un'altra macchina sono altri. E dimostrare che gli esseri > umani non sono pappagalli stocastici mica esclude che lo siano gli > LLM. Ambiguità della lingua: “they” in “they are not just stochastic parrots” non si riferisce a “people”, ma ai LLM. — Beppe > > Sicuramente questo sara' piu' chiaro nel dibattito. Ne sara' > disponibile una trascrizione? > > Grazie, > Marco > -- > https://mfioretti.substack.com <https://mfioretti.substack.com/>

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perdere il controllo dei "propri" device [CDT:L3]
by Andrea Trentini Oct. 12, 2023

Oct. 12, 2023

1) 'I was kidnapped by my runaway electric car' - BBC News https://www.bbc.com/news/uk-scotland-67005620 2) https://www.lealternative.net/2023/10/12/il-televisore-nottambulo-una-stori… -- Andrea Trentini ⠠⠵ http://atrent.it public key ID: 0xA7A91E3B Dip.to di Informatica Università degli Studi di Milano

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Do language models have an internal world model?
by Giuseppe Futia Oct. 11, 2023

Oct. 11, 2023

Cari Nexiani, Condivido con voi un interessante e controverso articolo scritto da due ricercatori del MIT intitolato "Language Models Represent Space and Time": https://arxiv.org/abs/2310.02207. I due ricercatori sostengono che gli LLMs sono in grado di acquisire una conoscenza strutturata di dimensioni fondamentali come lo spazio e il tempo. La sintesi dell'articolo e il dibattito che ne è scaturito è disponibile in questo thread Twitter: https://twitter.com/wesg52/status/1709551516577902782 . Ad arricchire il dibattito anche la pronta replica, come al solito molto netta, di Gary Marcus: https://garymarcus.substack.com/p/muddles-about-models. Un caro saluto, Giuseppe

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Concorso in Agcm - data engineering e data science
by Luigi Scorca Oct. 11, 2023

Oct. 11, 2023

https://www.agcm.it/autorita-trasparente/dettaglio?parent=Bandi%20di%20conc…

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