Je ne m'étais pas vraiment penchée sur le thème " #ChatGPT " avant de pouvoir m'y connecter sans compte. Depuis que c'est possible j'ai testé quelques fois.
En fait c'est vraiment très très limité. En gros, c'est un moteur de recherche qui papote avec vous et qui n'est pas fiable.
C'est marrant au début. Après, c'est comme les jeux vidéos on voit très vite les limites, les répétitions syntaxiques, les techniques de contournement des problèmes etc.
There was a time I was not happy about #GDPR but by now I consider those who made this law to be visionaries: #ChatGPT provides false information about people, and #OpenAI can’t correct it
Nachdem mir #ChatGPT kürzlich ein äußerst merkwürdiges #Schachbrett zeichnete, bat ich um ein Bild, wo bereits ein Zug gemacht wurde. Das Ergebnis beschreibt die KI so:
»Das Bild des Schachbretts zeigt nun den weißen Bauern, der von e2 nach e4 gezogen wurde, mit einer dezenten Leuchteffekt hervorgehoben, um seine Position zu betonen.«
Somebody has filed a #GDPR complaint about #OpenAI, because they are unable to correct false personal data that is produced by #ChatGPT.
This should be interesting to watch.
#openAI « refused to correct or delete wrong answers, and won't disclose any information about the data processed, its sources or recipients. »
"If a system cannot produce accurate and transparent results, it cannot be used to generate data about individuals. The technology has to follow the legal requirements, not the other way around" #chatgpt#gdpr@lamdba
Europäische Datenschützer reichen Beschwerde gegen OpenAI ein
Das KI-Programm ChatGPT veröffentlicht Daten über Privatpersonen, deren Herkunft unklar sei. Das werfen Datenschützer dem Anbieter OpenAI vor. Zudem ließen sich falsche Angaben nicht korrigieren.
#EU#AI#GenerativeAI#GDPR#OpenAI#ChatGPT: "In the EU, the GDPR requires that information about individuals is accurate and that they have full access to the information stored, as well as information about the source. Surprisingly, however, OpenAI openly admits that it is unable to correct incorrect information on ChatGPT. Furthermore, the company cannot say where the data comes from or what data ChatGPT stores about individual people. The company is well aware of this problem, but doesn’t seem to care. Instead, OpenAI simply argues that “factual accuracy in large language models remains an area of active research”. Therefore, noyb today filed a complaint against OpenAI with the Austrian DPA."
#Noyb reicht Beschwerde gegen #OpenAi wegen schweren #Verstößen des Produkt #ChatGPT gegen die Europäische Datenschutz-Grundverordnung (#DSGVO) ein.
"Es scheint, dass mit jeder ‚Innovation‘ eine andere Gruppe von Unternehmen meint, dass ihre Produkte nicht mit dem Gesetz übereinstimmen müssen.“, sagt
Maartje de Graaf, Datenschutzjuristin bei Noyb
"This is another variation of the High-Tech Illusion: the belief that software developers do easily automated work. Their principal work is human communication to organize the user's expressions of needs into formal procedure. That work will be necessary no matter how we change the life cycle."
"There has been a shift in the #AI space: some models, like #ChatGPT & #Gemini, have evolved into entire web platforms spanning multiple use cases & access points. Other large language models like #LLaMa or #OLMo, though technically speaking they share a basic architecture, don’t actually fill the same role. They are intended to live in the background as a service or component, not in the foreground as a name brand." https://techcrunch.com/2024/04/19/too-many-models/
With all the valid concern around #llm and #genai power and water usage, I thought I'd start a blog series on tiny LLMs. Let's see what they can do on real tasks on very power efficient hardware.
I've had occasion to ask an AI about a thing twice lately (a recent online phenomenon, and a book recommendation). Both times I asked both Gemini and ChatGPT, and both times one gave a reasonable if bland answer, and the other (a different one each time) gave a plausible but completely fictional ("hallucinated") answer.
When do we acknowledge that LLMs, and "AI" in general, aren't quite ready to revolutionize the world?
When we teach WW1 history and show photographs of men in the trenches, and no one knows if they are real or midjourney fake then we are in deep trouble. Or teach scientific principles through research papers and don't know if the text is authentic human created or response engine output, we are in deep trouble. Imagine a hundred other contexts and you understand why gen ai is such a massive problem.
I had a corridor chat about with two designer friends about the enshittification of the internet yesterday, with me, 20+ years their senior, waxing lyrical about the good old days of the World Wide Web. One of them forwarded me the long form piece 'Are We Watching The Internet Die?' by Ed Zitron's. It confirms all of what worries me about generative AI. Here's hoping there's a way to step back from the edge.
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