#language-processing — Public Fediverse posts

DATE: June 30, 2026 at 02:00PM
SOURCE: PSYPOST.ORG

** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------

TITLE: Bilingual brains use a shared neural map to translate meaning across languages

URL: https://www.psypost.org/bilingual-brains-use-a-shared-neural-map-to-translate-meaning-across-languages/

A recent study published in the journal Cell provides evidence that the human brain uses a shared organizational map, or geometry, to represent word meanings across different languages. By recording individual brain cells in bilingual individuals, scientists found that while each language relies on distinct cellular activity patterns, the overall structural relationship between word meanings remains consistent. This suggests that the brain maintains a universal, language-independent internal model for meaning.

Human beings possess the unique ability to comprehend and express identical thoughts in multiple languages without confusing them. Previous brain imaging research indicates that bilingual speakers rely on overlapping brain regions when processing their different languages. Regions traditionally associated with language, such as the inferior frontal gyrus and posterior temporal cortex, show similar activation patterns whether a person is speaking English or Spanish.

However, these broad brain scans do not capture how the brain matches equivalent concepts across languages while keeping the languages functionally separate. A collaborative research team from Baylor College of Medicine, Rice University, and Sungkyunkwan University sought to understand this phenomenon at the level of individual brain cells.

The research team proposed that the bilingual brain might organize meaning by using a shared neural geometry. In this context, neural geometry refers to the mathematical distances and relationships between words represented in a high-dimensional space within the brain.

“Our findings suggest that the brain may store meaning in a language-independent format,” said Dr. Sameer Sheth, a professor of neurosurgery, McNair Scholar, and Cullen Foundation Endowed Chair at Baylor College of Medicine, and co-senior author of the study. “Different languages appear to access a shared conceptual map rather than creating entirely separate representations of the world.”

The research team specifically focused on the hippocampus, a brain region known to play a central role in memory and the linking of concepts. Because the hippocampus is buried deep within the brain, it is typically difficult to study during active language processing.

To observe these deep brain structures, the scientists recruited four fully balanced bilingual patients who spoke both English and Spanish. These patients were already undergoing surgical procedures for treatment-resistant epilepsy. This medical situation provided a rare opportunity to implant high-density microelectrodes directly into the hippocampus. Three patients received standard microelectrodes, while one patient received a highly advanced Neuropixels probe, allowing the scientists to record the electrical spikes of individual neurons.

The scientists designed three distinct tasks for the participants to perform. In the first task, all four patients spent about 120 minutes passively listening to matched stories and podcasts in both English and Spanish. The audio content included educational science podcasts from a creator called Kurzgesagt and excerpts from the audiobook “Eat, Pray, Love.” This provided thousands of spoken words for the researchers to analyze across multiple sessions.

In the second task, two of the patients read 99 matched short phrases on a computer screen and spoke them out loud. Finally, these same two patients participated in unstructured, naturalistic conversations. They spoke with native speakers of each language for periods ranging from 32 to 99 minutes. The scientists then aligned the spoken audio with the recorded neural activity to track how the brain responded to specific words.

The scientists closely analyzed the firing rates of the recorded neurons in response to equivalent words across languages. They first looked for cross-language neurons, which are individual brain cells that respond identically to translated pairs like “earth” and “tierra.” They identified a small subset of these neurons, providing evidence that a few isolated cells do handle direct translation.

However, these specific cells were rare, meaning they could not entirely explain how the brain processes two languages seamlessly. The findings suggest that translation is not driven primarily by specialized dictionary neurons, but instead emerges from coordinated activity across large neural populations.

“Our results show that bilingual meaning is an emergent property of neural populations,” said Xinyuan Yan, a postdoctoral scholar at Baylor College of Medicine and lead author of the study. “The brain does not appear to rely on one-to-one translation cells. Instead, it preserves patterns of relationships among concepts across languages.”

To understand the bigger picture, the authors compared the patients’ neural activity to an artificial intelligence tool called multilingual BERT. BERT is a large language model that learns cross-linguistic representations by processing massive amounts of text. The scientists extracted contextual word embeddings from the artificial intelligence model.

Contextual word embeddings are mathematical representations of words that capture their meaning based on surrounding text. The scientists then mapped these artificial representations alongside the actual firing rates of the human hippocampal neurons. They found notable similarities between the geometry of semantic representations in the hippocampus and the internal organization of modern artificial intelligence systems trained on multiple languages.

“Large language models and the human brain may be converging on similar computational solutions for representing meaning,” said Benjamin Hayden, an adjunct professor of electrical and computer engineering and linguistics at Rice University, professor of neurosurgery and McNair Scholar at Baylor, and co-senior author of the study. “That does not mean AI works exactly like the brain, but it suggests there may be universal principles for organizing knowledge.”

The findings revealed that the specific semantic tuning curves of most individual neurons differed substantially between English and Spanish. A semantic tuning curve is essentially a profile of how a specific neuron responds to different word meanings across a wide variety of topics. Because these profiles did not match, it indicated that the brain uses language-specific recipes to process words. An individual neuron might fire strongly for the English word “dog” but remain completely quiet for the Spanish word “perro.”

Despite this difference at the cellular level, the overall population of neurons maintained a preserved geometric organization across both languages. The researchers measured the mathematical distances between the neural responses for different words. They found that the overarching map of word meanings in English tends to mirror the map in Spanish perfectly.

The brain achieves this by using the same population of neurons but reading their activity from different angles, or axes, depending on the language being spoken. This phenomenon is similar to looking at a three-dimensional object from two different viewpoints. The object’s shape remains identical, but the visible profile changes based on your perspective.

“This helps explain how bilingual people can switch between languages so fluidly,” Hayden said. “The brain seems to maintain a common internal structure for meaning while simultaneously keeping languages distinct enough to avoid interference.”

The shared semantic structure was so robust that the researchers could use it to predict neural responses. By looking at a cluster of related words in English, the scientists could mathematically rotate the data to accurately predict how the brain would respond to a held-out Spanish word. This form of zero-shot learning demonstrates that the overall geometry provides enough information for translation, even without a direct word-to-word mapping at the individual neuron level.

Beyond the scientific arena, this discovery may be of broader interest in the humanities and social sciences. The concept of a stable, shared geometric neural map provides evidence for a structuralist view of language, an intellectual current often traced back to Swiss linguist Ferdinand de Saussure. Structuralism holds that meaning transcends individual cultural expressions and instead relies on an underlying universal structure or system.

In addition to advancing basic neuroscience, the authors note that these findings could influence the development of brain-computer interfaces. They may also inform language rehabilitation therapies and future artificial intelligence systems designed to communicate more naturally with humans.

While these findings offer deep insights into bilingualism, readers should be aware of a few limitations. One potential misinterpretation is that these results apply to all language learners. The patients in this study were all highly proficient, early-acquired bilinguals, meaning they learned both languages around age four or five. It remains unknown if individuals who learn a second language later in life share this identical neural geometry.

Additionally, the researchers caution that the study features a very small sample size of only four participants. This is due to the extreme rarity of finding balanced bilingual patients who require deep brain electrode implants for medical reasons. The authors point out that the study only examined English and Spanish. These two languages share many linguistic roots and structural similarities.

Another limitation involves the medical status of the participants. One of the patients was recorded under general anesthesia after a portion of their temporal lobe had been removed. While the data from this patient largely matched the others, the anesthesia and surgery could have altered normal brain activity patterns.

Future research could expand on these findings by testing unrelated language pairs, such as English and Mandarin, and by observing larger populations. Scientists also hope to study participants as they actively learn a new language. Tracking the brain during the learning process could reveal exactly how this shared semantic geometry forms and aligns over time.

The study, “Shared neural geometries for bilingual semantic representations in human hippocampal neurons,” was authored by Xinyuan Yan, Ana G. Chavez, Melissa Franch, Kalman A. Katlowitz, Ivy Gautam, Brian Kim, Aaditya Krishna, Aadit Shrivastava, Katie Van Arsdel, James Belanger, Assia Chericoni, Taha Ismail, Elizabeth A. Mickiewicz, Danika Paulo, Hanlin Zhu, Alica M. Goldman, Vaishnav Krishnan, Atul Maheshwari, Eleonora Bartoli, Nicole R. Provenza, Seng Bum Michael Yoo, Benjamin Y. Hayden, and Sameer A. Sheth.

URL: https://www.psypost.org/bilingual-brains-use-a-shared-neural-map-to-translate-meaning-across-languages/

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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BilingualBrain #NeuralGeometry #SharedSemanticMap #LanguageProcessing #HippocampusResearch #CrossLanguageTranslation #NeuroscienceStudy #MultilingualBERTComparison #BrainComputerInterface #LanguageRehabilitation

DATE: June 30, 2026 at 02:00PM
SOURCE: PSYPOST.ORG

** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------

TITLE: Bilingual brains use a shared neural map to translate meaning across languages

URL: https://www.psypost.org/bilingual-brains-use-a-shared-neural-map-to-translate-meaning-across-languages/

A recent study published in the journal Cell provides evidence that the human brain uses a shared organizational map, or geometry, to represent word meanings across different languages. By recording individual brain cells in bilingual individuals, scientists found that while each language relies on distinct cellular activity patterns, the overall structural relationship between word meanings remains consistent. This suggests that the brain maintains a universal, language-independent internal model for meaning.

Human beings possess the unique ability to comprehend and express identical thoughts in multiple languages without confusing them. Previous brain imaging research indicates that bilingual speakers rely on overlapping brain regions when processing their different languages. Regions traditionally associated with language, such as the inferior frontal gyrus and posterior temporal cortex, show similar activation patterns whether a person is speaking English or Spanish.

However, these broad brain scans do not capture how the brain matches equivalent concepts across languages while keeping the languages functionally separate. A collaborative research team from Baylor College of Medicine, Rice University, and Sungkyunkwan University sought to understand this phenomenon at the level of individual brain cells.

The research team proposed that the bilingual brain might organize meaning by using a shared neural geometry. In this context, neural geometry refers to the mathematical distances and relationships between words represented in a high-dimensional space within the brain.

“Our findings suggest that the brain may store meaning in a language-independent format,” said Dr. Sameer Sheth, a professor of neurosurgery, McNair Scholar, and Cullen Foundation Endowed Chair at Baylor College of Medicine, and co-senior author of the study. “Different languages appear to access a shared conceptual map rather than creating entirely separate representations of the world.”

The research team specifically focused on the hippocampus, a brain region known to play a central role in memory and the linking of concepts. Because the hippocampus is buried deep within the brain, it is typically difficult to study during active language processing.

To observe these deep brain structures, the scientists recruited four fully balanced bilingual patients who spoke both English and Spanish. These patients were already undergoing surgical procedures for treatment-resistant epilepsy. This medical situation provided a rare opportunity to implant high-density microelectrodes directly into the hippocampus. Three patients received standard microelectrodes, while one patient received a highly advanced Neuropixels probe, allowing the scientists to record the electrical spikes of individual neurons.

The scientists designed three distinct tasks for the participants to perform. In the first task, all four patients spent about 120 minutes passively listening to matched stories and podcasts in both English and Spanish. The audio content included educational science podcasts from a creator called Kurzgesagt and excerpts from the audiobook “Eat, Pray, Love.” This provided thousands of spoken words for the researchers to analyze across multiple sessions.

In the second task, two of the patients read 99 matched short phrases on a computer screen and spoke them out loud. Finally, these same two patients participated in unstructured, naturalistic conversations. They spoke with native speakers of each language for periods ranging from 32 to 99 minutes. The scientists then aligned the spoken audio with the recorded neural activity to track how the brain responded to specific words.

The scientists closely analyzed the firing rates of the recorded neurons in response to equivalent words across languages. They first looked for cross-language neurons, which are individual brain cells that respond identically to translated pairs like “earth” and “tierra.” They identified a small subset of these neurons, providing evidence that a few isolated cells do handle direct translation.

However, these specific cells were rare, meaning they could not entirely explain how the brain processes two languages seamlessly. The findings suggest that translation is not driven primarily by specialized dictionary neurons, but instead emerges from coordinated activity across large neural populations.

“Our results show that bilingual meaning is an emergent property of neural populations,” said Xinyuan Yan, a postdoctoral scholar at Baylor College of Medicine and lead author of the study. “The brain does not appear to rely on one-to-one translation cells. Instead, it preserves patterns of relationships among concepts across languages.”

To understand the bigger picture, the authors compared the patients’ neural activity to an artificial intelligence tool called multilingual BERT. BERT is a large language model that learns cross-linguistic representations by processing massive amounts of text. The scientists extracted contextual word embeddings from the artificial intelligence model.

Contextual word embeddings are mathematical representations of words that capture their meaning based on surrounding text. The scientists then mapped these artificial representations alongside the actual firing rates of the human hippocampal neurons. They found notable similarities between the geometry of semantic representations in the hippocampus and the internal organization of modern artificial intelligence systems trained on multiple languages.

“Large language models and the human brain may be converging on similar computational solutions for representing meaning,” said Benjamin Hayden, an adjunct professor of electrical and computer engineering and linguistics at Rice University, professor of neurosurgery and McNair Scholar at Baylor, and co-senior author of the study. “That does not mean AI works exactly like the brain, but it suggests there may be universal principles for organizing knowledge.”

The findings revealed that the specific semantic tuning curves of most individual neurons differed substantially between English and Spanish. A semantic tuning curve is essentially a profile of how a specific neuron responds to different word meanings across a wide variety of topics. Because these profiles did not match, it indicated that the brain uses language-specific recipes to process words. An individual neuron might fire strongly for the English word “dog” but remain completely quiet for the Spanish word “perro.”

Despite this difference at the cellular level, the overall population of neurons maintained a preserved geometric organization across both languages. The researchers measured the mathematical distances between the neural responses for different words. They found that the overarching map of word meanings in English tends to mirror the map in Spanish perfectly.

The brain achieves this by using the same population of neurons but reading their activity from different angles, or axes, depending on the language being spoken. This phenomenon is similar to looking at a three-dimensional object from two different viewpoints. The object’s shape remains identical, but the visible profile changes based on your perspective.

“This helps explain how bilingual people can switch between languages so fluidly,” Hayden said. “The brain seems to maintain a common internal structure for meaning while simultaneously keeping languages distinct enough to avoid interference.”

The shared semantic structure was so robust that the researchers could use it to predict neural responses. By looking at a cluster of related words in English, the scientists could mathematically rotate the data to accurately predict how the brain would respond to a held-out Spanish word. This form of zero-shot learning demonstrates that the overall geometry provides enough information for translation, even without a direct word-to-word mapping at the individual neuron level.

Beyond the scientific arena, this discovery may be of broader interest in the humanities and social sciences. The concept of a stable, shared geometric neural map provides evidence for a structuralist view of language, an intellectual current often traced back to Swiss linguist Ferdinand de Saussure. Structuralism holds that meaning transcends individual cultural expressions and instead relies on an underlying universal structure or system.

In addition to advancing basic neuroscience, the authors note that these findings could influence the development of brain-computer interfaces. They may also inform language rehabilitation therapies and future artificial intelligence systems designed to communicate more naturally with humans.

While these findings offer deep insights into bilingualism, readers should be aware of a few limitations. One potential misinterpretation is that these results apply to all language learners. The patients in this study were all highly proficient, early-acquired bilinguals, meaning they learned both languages around age four or five. It remains unknown if individuals who learn a second language later in life share this identical neural geometry.

Additionally, the researchers caution that the study features a very small sample size of only four participants. This is due to the extreme rarity of finding balanced bilingual patients who require deep brain electrode implants for medical reasons. The authors point out that the study only examined English and Spanish. These two languages share many linguistic roots and structural similarities.

Another limitation involves the medical status of the participants. One of the patients was recorded under general anesthesia after a portion of their temporal lobe had been removed. While the data from this patient largely matched the others, the anesthesia and surgery could have altered normal brain activity patterns.

Future research could expand on these findings by testing unrelated language pairs, such as English and Mandarin, and by observing larger populations. Scientists also hope to study participants as they actively learn a new language. Tracking the brain during the learning process could reveal exactly how this shared semantic geometry forms and aligns over time.

The study, “Shared neural geometries for bilingual semantic representations in human hippocampal neurons,” was authored by Xinyuan Yan, Ana G. Chavez, Melissa Franch, Kalman A. Katlowitz, Ivy Gautam, Brian Kim, Aaditya Krishna, Aadit Shrivastava, Katie Van Arsdel, James Belanger, Assia Chericoni, Taha Ismail, Elizabeth A. Mickiewicz, Danika Paulo, Hanlin Zhu, Alica M. Goldman, Vaishnav Krishnan, Atul Maheshwari, Eleonora Bartoli, Nicole R. Provenza, Seng Bum Michael Yoo, Benjamin Y. Hayden, and Sameer A. Sheth.

URL: https://www.psypost.org/bilingual-brains-use-a-shared-neural-map-to-translate-meaning-across-languages/

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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BilingualBrain #NeuralGeometry #SharedSemanticMap #LanguageProcessing #HippocampusResearch #CrossLanguageTranslation #NeuroscienceStudy #MultilingualBERTComparison #BrainComputerInterface #LanguageRehabilitation

DATE: June 28, 2026 at 10:55PM
SOURCE: SCIENCE DAILY MIND-BRAIN FEED

TITLE: Brain activity under anesthesia challenges what we know about consciousness

URL: https://www.sciencedaily.com/releases/2026/06/260624025514.htm

The unconscious brain appears to be far more capable than scientists once believed. Researchers found that patients under general anesthesia could still process language at a sophisticated level, distinguishing nouns, verbs, and adjectives while listening to stories. Even more remarkably, neural activity showed signs of predicting upcoming words before they were heard. The results challenge traditional ideas about consciousness and hint at new possibilities for brain-computer interfaces.

URL: https://www.sciencedaily.com/releases/2026/06/260624025514.htm

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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Consciousness #Anesthesia #BrainActivity #UnconsciousMind #LanguageProcessing #Neuroscience #BrainComputerInterface #NeuralPrediction #CognitiveScience #MindScience

DATE: June 28, 2026 at 10:55PM
SOURCE: SCIENCE DAILY MIND-BRAIN FEED

TITLE: Brain activity under anesthesia challenges what we know about consciousness

URL: https://www.sciencedaily.com/releases/2026/06/260624025514.htm

The unconscious brain appears to be far more capable than scientists once believed. Researchers found that patients under general anesthesia could still process language at a sophisticated level, distinguishing nouns, verbs, and adjectives while listening to stories. Even more remarkably, neural activity showed signs of predicting upcoming words before they were heard. The results challenge traditional ideas about consciousness and hint at new possibilities for brain-computer interfaces.

URL: https://www.sciencedaily.com/releases/2026/06/260624025514.htm

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Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org

Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Consciousness #Anesthesia #BrainActivity #UnconsciousMind #LanguageProcessing #Neuroscience #BrainComputerInterface #NeuralPrediction #CognitiveScience #MindScience

Just what does it take to #read? And to read #online?

Do we absorb information better on paper than screens? depends on the screen
https://theconversation.com/do-we-absorb-information-better-on-paper-rather-than-screens-it-depends-on-the-screen-281849

#reading #amreading #visualprocessing #eyemovement #perceptualspan #wordidentification #languageprocessing

Just what does it take to #read? And to read #online?

Do we absorb information better on paper than screens? depends on the screen
https://theconversation.com/do-we-absorb-information-better-on-paper-rather-than-screens-it-depends-on-the-screen-281849

#reading #amreading #visualprocessing #eyemovement #perceptualspan #wordidentification #languageprocessing

🎉 Ah, yet another mind-blowing revelation: #computers don't actually read words like humans do. 🤯 Who would've guessed that "strawberry" isn't spelled with three Rs? Clearly, #tokenization is the real villain here, not your LLM's lack of eyesight. 🍓🔍
https://bearisland.dev/posts/tokens-and-tokenization/ #LLM #AI #languageprocessing #HackerNews #ngated

🎉 Ah, yet another mind-blowing revelation: #computers don't actually read words like humans do. 🤯 Who would've guessed that "strawberry" isn't spelled with three Rs? Clearly, #tokenization is the real villain here, not your LLM's lack of eyesight. 🍓🔍
https://bearisland.dev/posts/tokens-and-tokenization/ #LLM #AI #languageprocessing #HackerNews #ngated

Researchers discover advanced language processing in the unconscious human brain

https://www.bcm.edu/news/researchers-discover-advanced-language-processing-in-the-unconscious-human-brain

#HackerNews #languageprocessing #neuroscience #research #brainunconscious #cognition

Researchers discover advanced language processing in the unconscious human brain

https://www.bcm.edu/news/researchers-discover-advanced-language-processing-in-the-unconscious-human-brain

#HackerNews #languageprocessing #neuroscience #research #brainunconscious #cognition

#Neuroscience #LanguageProcessing #Cerebellum #ScienceNews

https://www.sciencenews.org/article/cerebellum-brain-role-language

#Neuroscience #LanguageProcessing #Cerebellum #ScienceNews

https://www.sciencenews.org/article/cerebellum-brain-role-language

Speech and Language Processing (3rd ed. draft)

https://web.stanford.edu/~jurafsky/slp3/

#HackerNews #SpeechProcessing #LanguageProcessing #NLP #StanfordJurafsky #DraftEdition

Speech and Language Processing (3rd ed. draft)

https://web.stanford.edu/~jurafsky/slp3/

#HackerNews #SpeechProcessing #LanguageProcessing #NLP #StanfordJurafsky #DraftEdition

A survey of 1,004 #UK #journalists reveals that over half use #AI professionally at least weekly, primarily for #languageprocessing tasks like transcription and translation. However, AI is also used for substantive tasks such as #storyresearch and #ideageneration. AI use is more common among younger, male journalists. https://reutersinstitute.politics.ox.ac.uk/ai-adoption-uk-journalists-and-their-newsrooms-surveying-applications-approaches-and-attitudes?eicker.news #tech #media #news

A survey of 1,004 #UK #journalists reveals that over half use #AI professionally at least weekly, primarily for #languageprocessing tasks like transcription and translation. However, AI is also used for substantive tasks such as #storyresearch and #ideageneration. AI use is more common among younger, male journalists. https://reutersinstitute.politics.ox.ac.uk/ai-adoption-uk-journalists-and-their-newsrooms-surveying-applications-approaches-and-attitudes?eicker.news #tech #media #news

Deciphering language processing in the human brain through LLM representations

https://research.google/blog/deciphering-language-processing-in-the-human-brain-through-llm-representations/

#HackerNews #Deciphering #language #processing #in #the #human #brain #through #LLM #representations #LLMs #Neuroscience #LanguageProcessing #AIResearch

Deciphering language processing in the human brain through LLM representations

https://research.google/blog/deciphering-language-processing-in-the-human-brain-through-llm-representations/

#HackerNews #Deciphering #language #processing #in #the #human #brain #through #LLM #representations #LLMs #Neuroscience #LanguageProcessing #AIResearch

New paper in #Constructions: "Constructional #LanguageProcessing and #LanguageLearning starting from unsegmented linguistic #input" by Veronica Juliana Schmalz, Lara Verheyen & Jens Nevens https://doi.org/10.24338/cons-684

This is how I usually read. I rarely read word-by-word.

https://www.theguardian.com/science/2024/oct/23/human-brain-can-process-certain-sentences-in-blink-of-an-eye-says-study

#Literacy #Reading #Neuroscience #SpeedReading #LanguageProcessing #Linguistics

This is how I usually read. I rarely read word-by-word.

https://www.theguardian.com/science/2024/oct/23/human-brain-can-process-certain-sentences-in-blink-of-an-eye-says-study

#Literacy #Reading #Neuroscience #SpeedReading #LanguageProcessing #Linguistics

timing of brain waves shapes the words we hear #LanguageProcessing #neuroscience #entrainment https://medicalxpress.com/news/2024-06-brain-words.html

According to a recent study, dogs may possess a mental representation of words that correspond to specific objects. This means that when dogs hear a word that they have learned is associated with a particular object, their brain activity suggests that they are not merely reacting to the sound of the word, but are actually recalling a mental image of that object.

#Dogs #MentalRepresentation #LanguageProcessing

https://www.technologynetworks.com/neuroscience/news/brain-activity-study-finds-dogs-understand-words-for-objects-385055

According to a recent study, dogs may possess a mental representation of words that correspond to specific objects. This means that when dogs hear a word that they have learned is associated with a particular object, their brain activity suggests that they are not merely reacting to the sound of the word, but are actually recalling a mental image of that object.

#Dogs #MentalRepresentation #LanguageProcessing

https://www.technologynetworks.com/neuroscience/news/brain-activity-study-finds-dogs-understand-words-for-objects-385055

ICALP - International Conference on #Arabic #LanguageProcessing will be held on April 19-20, 2024, in Rabat, Morocco.

Paper Submission Deadline:
February 4th, 2024

For more details:
https://alesm.ma/icalp2023/

Self-Operating Computer with ChatGPT 4V – impressive and scary

#ArtificialIntelligence #Technology #FutureOfComputing #Robotarm #HumanoidRobot #MachineLearning #LanguageProcessing #AutonomousSystems #InnovativeTechnology #DigitalTransformation #AI

https://kinews24.de/self-operating-computer-mit-chatgpt-4v/

Uri Hasson will talk about "#DeepLanguageModels as a #cognitive model for natural #LanguageProcessing in the human brain" 👌

⏰ Dec 7 at 4.15pm CET:
🌍 http://bit.ly/2TPjNZ1

#Neuroscience #deeplearning #CompNeuro

@kgajos

Cool & non #aiHype ending by @NancyKanwisher @neuranna Joshua B Tenenbaum et al:

» Finally, to those who are looking to language models as a route to #AGI
we suggest that, instead of or in addition to scaling up the size of the models [Kaplan et al 2020],
more promising solutions will come in the form of modular
architectures—pre-specified or emergent—that, like the human #brain integrate #languageProcessing with additional systems that carry out #perception #reasoning and #planning «

@kgajos

Cool & non #aiHype ending by @NancyKanwisher @neuranna Joshua B Tenenbaum et al:

» Finally, to those who are looking to language models as a route to #AGI
we suggest that, instead of or in addition to scaling up the size of the models [Kaplan et al 2020],
more promising solutions will come in the form of modular
architectures—pre-specified or emergent—that, like the human #brain integrate #languageProcessing with additional systems that carry out #perception #reasoning and #planning «

#psycholinguistics #linguistics
#LanguageProcessing #EyeTracking

Is there any reason why it should be more difficulty to comprehend noun phrases with 'this' or 'that' type deictic determiners instead of generic 'the'? Can anyone point me to some relevant literature?

I'm utterly flummoxed by some eye-tracking results that I keep replicating for reasons that are utterly beyond me.

#psycholinguistics #linguistics
#LanguageProcessing #EyeTracking

Is there any reason why it should be more difficulty to comprehend noun phrases with 'this' or 'that' type deictic determiners instead of generic 'the'? Can anyone point me to some relevant literature?

I'm utterly flummoxed by some eye-tracking results that I keep replicating for reasons that are utterly beyond me.

#ChatGPT with #RobMiles - #Computerphile

https://www.youtube.com/watch?v=viJt_DXTfwA&ab_channel=Computerphile

#ComputerScience #LanguageModel #LanguageModels #LanguageProcessing #TextProcessing #ComputerLearning #AI #ArtificialIntelligence #GPT #GPT3 #AILearning #AITraining #OpenAI

#ChatGPT with #RobMiles - #Computerphile

https://www.youtube.com/watch?v=viJt_DXTfwA&ab_channel=Computerphile

#ComputerScience #LanguageModel #LanguageModels #LanguageProcessing #TextProcessing #ComputerLearning #AI #ArtificialIntelligence #GPT #GPT3 #AILearning #AITraining #OpenAI

New blog post alert! Just published an article on working with ChatGPT. Tips and tricks for translation, summarization, and code gen are included. Check it out to up your GPT game!

#GPT #NLP #languageprocessing #author
https://blogthedata.com/post/optimizing-gpt-for-nlp-tips-and-tricks/

New blog post alert! Just published an article on working with ChatGPT. Tips and tricks for translation, summarization, and code gen are included. Check it out to up your GPT game!

#GPT #NLP #languageprocessing #author
https://blogthedata.com/post/optimizing-gpt-for-nlp-tips-and-tricks/

#Introduction

New to Mastodon, part of the Twitter exodus. Sometimes it takes a colossal failure of a person (Musk) to liberate us from the Tyranny of Big Tech.

#Agender, #Demisexual, recovering Catholic.

#Neurodivergent AF. #ADHD and #ActuallyAutistic with #LanguageProcessing issues.

Love #SciFi and #Fantasy.

Fan of #StarTrek, #StarWars, #Marvel but also #Farscape, #Stargate, #Babylon5, #Buffy, #LOTR.

#Queer, but is that really a surprise?

I lean left politically. How far left? 🤷

Big fan of #NKJemisin.

White, middle class, male-passing. Epitome of #Priviledge as I fight to #EndThePatriarchy and #TearDownCapitalism.

Consistent Troublemaker. Former #Flautist but I sold out to the #Pennywhistle.

(edit: modified wording to remove inappropriate reference)

#Introduction

New to Mastodon, part of the Twitter exodus. Sometimes it takes a colossal failure of a person (Musk) to liberate us from the Tyranny of Big Tech.

#Agender, #Demisexual, recovering Catholic.

#Neurodivergent AF. #ADHD and #ActuallyAutistic with #LanguageProcessing issues.

Love #SciFi and #Fantasy.

Fan of #StarTrek, #StarWars, #Marvel but also #Farscape, #Stargate, #Babylon5, #Buffy, #LOTR.

#Queer, but is that really a surprise?

I lean left politically. How far left? 🤷

Big fan of #NKJemisin.

White, middle class, male-passing. Epitome of #Priviledge as I fight to #EndThePatriarchy and #TearDownCapitalism.

Consistent Troublemaker. Former #Flautist but I sold out to the #Pennywhistle.

(edit: modified wording to remove inappropriate reference)

@kaitclark #psycholinguistics #languageProcessing #reference #eyeTracking

Hello 👋 I model human intelligence and underlying brain mechanisms using artificial neural networks. Focusing on vision and language. Incoming prof at EPFL, currently research scientist at MIT, looking to connect with people in #compneuro #neuroscience #NeuroAI #DeepLearninig #MachineLearming #vision #languageprocessing #NeuroscienceMigration #introduction