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DTSTART;TZID=Europe/Berlin:20250410T100000
DTEND;TZID=Europe/Berlin:20250410T110000
DTSTAMP:20260407T234834
CREATED:20250317T104720Z
LAST-MODIFIED:20250603T124113Z
UID:23728-1744279200-1744282800@www.scienceofintelligence.de
SUMMARY:Bojana Grujičić (Science of Intelligence)\, "Artificial Possibilities"
DESCRIPTION:Science often deals with issues pertaining to possibilities\, contingencies and necessities\, by engaging in thought experiments and modeling. This talk discusses how much deep learning can be helpful for navigating the possibility space for intelligence\, adding to our scientific understanding of possibilities. One epistemically useful feature of neural networks is their runnability – they can be trained to perform a cognitive task and can run when given novel stimuli\, demonstrating possibilities of cognitive phenomena based on sets of inductive biases. I focus on the problem of justification of neural network-based inferences about possibilities and outline a plausible justificatory strategy. I consider a number of reasons for taking neural network-demonstrated possibilities to be technological\, rather than biological possibilities. Despite this\, I argue that they add to our scientific understanding of possibilities related to intelligence. \n  \nPhoto by Joakim Honkasalo on Unsplash.
URL:https://www.scienceofintelligence.de/event/bojana-grucic-science-of-intelligence-artificial-possibilities/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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DTSTART;TZID=Europe/Berlin:20250417T100000
DTEND;TZID=Europe/Berlin:20250417T113000
DTSTAMP:20260407T234834
CREATED:20250317T105203Z
LAST-MODIFIED:20250603T124106Z
UID:23733-1744884000-1744889400@www.scienceofintelligence.de
SUMMARY:Tamal Roy & Valentin Lecheval (Science of Intelligence)\, “Evolution of Collective Cognition Through Individual-Level Selection”
DESCRIPTION:More details to follow. \nPhoto created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/tamal-roy-valentin-lechecal-science-of-intelligence-evolution-of-collective-cognition-through-individual-level-selection/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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DTSTART;TZID=Europe/Berlin:20250424T100000
DTEND;TZID=Europe/Berlin:20250424T110000
DTSTAMP:20260407T234834
CREATED:20250317T105402Z
LAST-MODIFIED:20250603T124043Z
UID:23736-1745488800-1745492400@www.scienceofintelligence.de
SUMMARY:Adrien Doerig (Freie Universität)\, “High-Level Visual Representations in the Human Brain Are Aligned With Large Language Models”
DESCRIPTION:The human brain extracts complex information from visual inputs\, including objects\, their spatial and semantic interrelations\, and their interactions with the environment. However\, a quantitative approach to capture this information remains elusive. I will present work where we show that LLM embeddings of scene captions successfully characterise brain activity evoked by viewing the natural scenes. This mapping captures selectivities of different brain areas\, and is sufficiently robust that accurate scene captions can be reconstructed from brain activity. Further\, we show that neural networks trained to transform image inputs into LLM representations are better aligned with brain representations than a large number of state-of-the-art alternative models\, despite being trained on orders-of-magnitude less data. Overall\, these results suggest that LLM embeddings of scene captions provide a representational format that accounts for complex information extracted by the brain from visual inputs. \nPhoto created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/adrien-doerig-freie-universitat-high-level-visual-representations-in-the-human-brain-are-aligned-with-large-language-models/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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