Christoph Drösser

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Christoph Drösser

Christoph Drösser

@chrdr

Freelance writer in San Francisco.

San Francisco Katılım Nisan 2009
192 Takip Edilen828 Takipçiler
Christoph Drösser retweetledi
Weltreporter
Weltreporter@weltreporter·
Sie haben Post! Diesmal aus San Francisco: Unser Kollege @chrdr war auf der wohl teuersten Toilette der Stadt. Wieviel sie gekostet hat? Tief Luft holen! riffreporter.de/de/internation…
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German Consulate San Francisco
German Consulate San Francisco@GermanyinSF·
🇩🇪media/correspondents in the Bay Area/Silicon Valley explain to and help 🇩🇪audiences understand what goes on in this “global” region. Great gathering at @StFYC - to look back on 2023 & forward to all that might come. @chrdr @BarbaraMunker @StephanScheuer Ana Radic
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RiffReporter
RiffReporter@riffreporter·
Popularität und wirtschaftlicher Erfolg klaffen bei #Disney extrem auseinander: Seit 2021 hat sich der Aktienkurs des Unternehmens halbiert, schon mehrfach stand der Konzern kurz vor der Pleite. Trotzdem feiert er in diesen Tagen 100-Jähriges. (€) @chrdr riffreporter.de/de/internation…
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Christoph Drösser retweetledi
Weltreporter
Weltreporter@weltreporter·
Wie divers ist Disney? Zum 100. Geburtstag des Konzerns ist #Weltreporter @chrdr losgezogen, um das zu überprüfen. Denn Disney ist aufgrund seiner Marktmacht auch ein politischer Faktor in den USA. Sein Feature läuft am Montag auf @swr2wissen #FürSieVorOrt buff.ly/3ZOIzGm
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Gašper Beguš
Gašper Beguš@begusgasper·
Linguistics is not only about understanding human language. How can generative AI & linguistics help us understand animals? Here's a great summary of the @ProjectCETI workshop on *Decoding Communication in Nonhuman Species II* @SimonsInstitute. 🐳🐘🐬 "Prior to the work of Project CETI, the common assumption in the field was that whale codas form discrete basic “building blocks” of their communication system. Some speakers cautioned that this assumption would be analogous to turning a human vocal utterance into written text. This might correctly identify some linguistic elements, but you might also lose important information in the process. Gašper Beguš from UC Berkeley, CETI’s linguistics lead, pointed this out in his talk. “Spoken language is the primary thing; written text is just a representation of spoken language. If we see a [sperm whale] click, then we immediately think: oh, that is a one/zero kind of thing.” But that’s our human (or computer scientist) bias. When we model a language from text, we can learn a lot about it, but we also lose a lot of non-textual communication. “If you're approaching something as unknown as whale communication, you don't want to be throwing away anything.” He is using a flavor of Generative AI called a General Adversarial Network (GAN). GANs have the advantage that they can work with the original audio recordings to create translations or representations. They consist of two AI players, the generator and the discriminator. The discriminator has been trained on a set of data, e.g. audio recordings. The generator, which never sees the original training set, looks at new data and tries to describe them, starting with random strings of symbols. The two parts of the algorithm play a kind of game: the generator tries to get better and better at describing the data, while the discriminator tries to get better at telling correct descriptions from false ones. As each party tries to outperform the other, the whole system gets better at interpreting the data. “GANs are also very nice because they replicate stages in the acquisition of language,” Beguš said. So scientists could use them to study how whale calves start acquiring their language in small steps, just as human children don't start talking in complex sentences. Beguš doesn’t see GANs as a competitive alternative to using LLMs, however. Rather, these different AI methods complement each other in understanding different aspects of the whales’ world. “GANs are appropriate for understanding what is meaningful at the most basic level, or how their vocalizations are learned,” he said. “Using LLMs helps us with longer conversations and more discretized representations of their vocalizations. Graph neural networks that operate with mathematical graphs can be used to model their complex social structure and behavior.”" Full article by @chrdr: simons.berkeley.edu/news/workshop-… Video: youtube.com/watch?v=jFo59f…
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Christoph Drösser retweetledi
MIP.labor
MIP.labor@MIP_labor·
Viele aktuelle Fellows nutzen das Remote-Angebot und arbeiten ortsunabhängig, mit digitaler Standleitung ins MIP.labor. Alternativ bieten wir auch einen festen Arbeitsort in ruhiger Umgebung an der @FU_Berlin nahe Botanischer Garten. ➡️ Bis 17.7. bewerben #section-fellowship" target="_blank" rel="nofollow noopener">miplabor.de/#section-fello…
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Anonymus
Anonymus@TestaRo40548188·
@zeitonline @chrdr Solche Fragen stellen sich offenbar nur "Forschende". Forscher widmen sich dagegen anderen Problemen.
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DIE ZEIT
DIE ZEIT@zeitonline·
Wie wird eigentlich ein Hühnerei gelegt? Kommt es mit der stumpfen oder der spitzen Seite zuerst aus dem #Huhn? Unser Kolumnist @chrdr ist der Frage nachgegangen, die schon viele Forschende und sogar #Aristoteles beschäftige. zeit.de/2023/22/eierpr…
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Keşfet

@StFYC @BarbaraMunker @StephanScheuer @unipotsdam @zeitonline @zeitwissen @EvanMandery @spektrum