In October 2025, a storm brewed over the Caribbean Sea. Weather models differed on its trajectory. Would it remain weak and end up in Haiti, or would it intensify and head to Jamaica? Artificial intelligence model WeatherNext, developed by Google’s DeepMind and Google Research, went with the latter. Five days before landfall, it predicted with 80 percent confidence that the storm system would hit Jamaica as a Category 5 hurricane.
Hurricane Melissa was catastrophic, causing flooding and landslides across Jamaica. But the AI model helped forecasters give an earlier warning to communities in its path, so they could better prepare.
In a paper published on Thursday in Nature, researchers show that the WeatherNext AI model can predict cyclones with unprecedented accuracy. On average, it gives forecasters a day more lead time than existing models; this means its predictions three days out are as accurate as previous models’ predictions two days out. On the ground, that extra day can mean a lot.
In October 2025, a storm brewed over the Caribbean Sea. Weather models differed on its trajectory. Would it remain weak and end up in Haiti, or would it intensify and head to Jamaica? Artificial intelligence model WeatherNext, developed by Google’s DeepMind and Google Research, went with the latter. Five days before landfall, it predicted with 80 percent confidence that the storm system would hit Jamaica as a Category 5 hurricane.
Hurricane Melissa was catastrophic, causing flooding and landslides across Jamaica. But the AI model helped forecasters give an earlier warning to communities in its path, so they could better prepare.
In a paper published on Thursday in Nature, researchers show that the WeatherNext AI model can predict cyclones with unprecedented accuracy. On average, it gives forecasters a day more lead time than existing models; this means its predictions three days out are as accurate as previous models’ predictions two days out. On the ground, that extra day can mean a lot.
Kenny still appreciated a good church service and even did readings from the breviary. Unusually, he argued there was no reason why an agnostic shouldn't pray.
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Hassabis was one of the founders of DeepMind, and he maintained a key leadership role after Google acquired it. As the generative AI boom took off, Hassabis has been one of the loudest voices predicting the impending creation of artificial general intelligence (AGI), which is typically described as an AI with human-like capabilities and intelligence.
In his memo announcing his decision to leave DeepMind, Hassabis again leans on the promise of AGI. "I've been working towards AGI my whole life and now, like many of you, I feel it is close at hand," said Hassabis.
The biblical definitions of heart, mind, intellect, body and soul are discussed. I expand the discussion to the immortality of the soul and whether or not an AI machine can ever have or possess a soul.
Além de três modelos para programação, cibersegurança e agentes de IA, a Google revelou a mais recente versão da plataforma Gemini Robotics, que permite controlar o corpo inteiro dos robots e coordenar tarefas de forma mais autónoma.
Dr. Michael Egnor explores the existence and immortality of the soul, challenging materialist views by analyzing brain injuries, free will, and near-death experiences. He concludes that while the brain handles physical functions, the soul embodies abstract thought and consciousness, remaining independent and everlasting.
Author: Marta Sánchez López, Postdoctoral researcher at Research Centre for Basque Language and Texts (CNRS-IKER) – Université Bordeaux Montaigne. She also collaborates with the The Bilingual Mind Research Group (Gogo Elebiduna), University of the Basque Country.
In our daily life, we perceive many different events around us with different participants involved, such as a woman dancing in a theater, or a man enjoying an ice cream. To produce and understand the sentences that express these events, it is crucial to identify the number of participants involved and the role that each one plays. As in a drama, we have to identify the role that each character has to understand the story.
Agents, patients and experiencers
In some events, there are two characters involved, as in the girl kicks the ball, with the girl and the ball; in others, instead, there is only one, as in the woman dances or the man falls down, with the woman or the man. Each of these participants has a different role. For example, the woman is an agent, because she is doing the action, just the opposite of the man, who is a patient, because he is the one affected. In the case of the girl has fun, this participant has the role of experiencer, the one who experiences the enjoyment.
In psycholinguistics, the mechanisms involved in the processing of agent, patient, and experiencer roles have been investigated through different experiments such as reading sentences while participants’ brain activity or eye-movements are recorded. In these studies, it has been found that agent and patient categories play a crucial role in language comprehension and production. These two roles are used when reading, listening to, and producing sentences, and different mechanisms are involved in their processing (e.g., 12345). Therefore, they form two different categories within the event role repertoire 6. They are two different characters within the drama. However, as I will discuss, there is no experimental evidence for a third character, the experiencer role.
One well-established result regarding the processing of agents and patients comes from experiments where participants are asked to read sentences while their brain activity is recorded by means of electrodes, known as EEG studies. Results of these studies show that the processing of patients elicited an N400 component (a negative brain response that occurs around 400 milliseconds after a stimulus is processed) compared to the processing of agents. This effect is associated with the processing of unexpected elements. For example, when processing the day was breezy so the boy went outside to fly, it is expected to read next a kite based on the preceding context; hence, if an airplane is read instead, as this is unexpected, then an N400 effect appears 7. Something similar happens with the processing of agents and patients: agents are expected, whereas patients unexpected.
Across languages, speakers tend to interpret the first ambiguous noun phrase of a sentence as an agent instead of as a patient, due to the agent preference 8: agents are preferred and are cognitively more salient than patients. Imagine that someone reads the sentence Mary falls down. Before encountering the verb, the reader cannot know whether Mary is an agent or a patient. However, as agents are preferred over patients, the reader interprets that it is an agent by default. Once the verb is reached, there are two options: confirm that Mary is an agent (the expected role) or recategorize it as a patient (the unexpected role). In Mary falls down, it is the second option, Mary is categorized as a patient, because the verb selects this role. This recategorization is reflected in an N400 component. This result shows that agents and patients have different processing mechanisms and that they form two different categories. Furthermore, this effect has been largely found in different languages such as, Basque (Isasi-Isasmendi et al., 2024), Spanish 9, German (Haupt et al., 2008), Hindi (Bickel et al., 2015), or Aïwoo (Sauppe et al., 2023), supporting its robustness.
Therefore, these experimental findings show that there is a preference toward agents over patients. The agent is the protagonist of the show, while the patient plays a secondary role.
What about experiencers?
Linguists have proposed that there are other roles within the event role repertoire, for example, the experiencer role 10.This role corresponds to the participant who experiences a mental state denoted by the verb. Participants of events like loving someone or enjoying an ice cream have this role. The experiencer is the participant who loves or enjoys.
But does experimental evidence show that the experiencer role is a specific role category within the event role repertoire, as agent and patient roles do?
In Sánchez-López (2026), I addressed this question. I investigated whether speakers use a third category, the experiencer role, when processing language. In three reading eye-tracking experiments and in one EEG experiment, I asked Spanish native speakers to read sentences, while their eye-movements and their brain activity were recorded.
In the first two eye-tracking experiments, I compared de processing of sentences with two participants with different combinations of agent, experiencer, and patient roles: (i) María golpea a Juan “Mary hits John”, with an agent (María) and a patient (Juan); (ii) María asusta a Juan “Mary frightens John”, with an agent (María) and an experiencer (Juan); and (iii) María ama a Juan “Mary loves John”, with an experiencer (María) and a patient (Juan).
These two experiments revealed that Spanish native speakers produced higher fixation times on verbs selecting agent-experiencer roles (ii), than on the other two sentence types (i, iii), independently of whether the subject was animate or inanimate (e.g., María/La situación asusta a Juan “Mary/The situation frightens John”). Interestingly, no processing differences were found between sentences selecting agent-patient (i) and experiencer-patient (iii). These findings show that the combination of agent-experiencer involves higher processing cost than other combinations.
But why is the agent-experiencer combination costlier than the others?
A possible explanation could be that the experiencer role is not a specific category within the event role repertoire. As Dowty 11 proposed, agents and experiencers are both grouped within the same category, the one of the proto-agent. Based on this proposal, there are only two roles in the event role repertoire, proto-agent and proto-patient, and proto-agents always become subjects. Hence, in sentences like Mary frightens John, both participants are proto-agents. Since they are both possible candidates to become subject, a competition for subject assignment appears. This competition is reflected in higher processing cost compared to those sentences without competition, sentences with only one proto-agent participant (e.g., Mary hits John or Mary loves John).
To better understand this competition effect, imagine that the proto-agent is the hero of the story and the proto-patient is the villain. In a drama, if there is a hero, there is also a villain. If there are two heroes and no villain in the story, it would be unusual, and probably, it would take more time to understand the story, since this is not expected. Hence, the same happens with sentences like Mary frightens John, which have two proto-agents; this combination is unexpected and it entails higher processing cost than when there is only one proto-agent and one proto-patient.
In another reading experiment using both eye-tracking and EEG techniques, I compared the processing of the three roles, agent, experiencer, and patient again to determine whether this experiencer role behaves like the agent role or not. In these experiments, I used sentences with only one participant involved: (iv) María baila “Mary dances” with an agent, (v) María disfruta “Mary has fun” with an experiencer, and (vi) María se cae “Mary falls down” with a patient. The use of these sentences allowed a more direct comparison of the processing of these roles, since the three roles are subjects. The structure of all sentences is the same (one participant and the verb), and only the event role category changes.
Results revealed that participant looked more at sentences with agents and experiencers than at sentences with patients. Moreover, I found that participants exhibited a preference to interpret the first ambiguous noun phrase (i.e., María) as an agent/experiencer; hence, when they realized that it was a patient instead, an N400 component appeared. But this effect only appeared with patients, not with experiencers, showing that participants processed similarly agents and experiencers, and both different from patients.
What does this evidence show?
These results align with the hypothesis that there are only two role categories within the event role repertoire (Dowty, 1991): proto-agent and proto-patient. Therefore, when the sentences Mary dances or Mary has fun are processed, in both cases, Mary is interpreted as a proto-agent, whereas in Mary falls down, she is interpreted as a patient instead.
All in all, this evidence suggests that agents and experiencers belong to the same role category, the one of the proto-agent. Therefore, when we process language, it seems that we do not differentiate between agents and experiencers, rather we process them similarly. Experiencers are grouped together with agents, being the same character in the event, both proto-agents.
So, proto-agents are the protagonists of the story, the ones that spectators prefer to pay attention to, whereas proto-patients are the secondary characters who complement the story. Regarding experiencers, they do not play a different character in the story, instead, they are also the protagonists.
References
Bickel, B., Witzlack-Makarevich, A., Choudhary, K. K., Schlesewsky, M., & Bornkessel-Schlesewsky, I. (2015). The neurophysiology of language processing shapes the evolution of grammar: Evidence from case marking. PLOS ONE, 10(8), e0132819. https://doi.org/10.1371/journal.pone.0132819 ↩
Gómez-Vidal, B., Arantzeta, M., Laka, J. P., & Laka, I. (2022). Subjects are not all alike: Eye-tracking the agent preference in Spanish. PLOS ONE, 17(8). doi: 10.1371/journal.pone.0272211↩
Haupt, F. S., Schlesewsky, M., Roehm, D., Friederici, A. D., & Bornkessel-Schlesewsky, I. (2008). The status of subject–object reanalyses in the language comprehension architecture. Journal of Memory and Language, 59(1), 54–96. https://doi.org/10.1016/j.jml.2008.02.003 ↩
Isasi-Isasmendi, A., Sauppe, S., Andrews, C., Laka, I., Meyer, M., & Bickel, B. (2024). Incremental sentence processing is guided by a preference for agents: EEG evidence from Basque. Language, Cognition and Neuroscience, 39(1), 76–97. https://doi.org/10.1080/23273798.2023.2250023 ↩
Sauppe, S., Næss, Å., Roversi, G., Meyer, M., Bornkessel-Schlesewsky, I., & Bickel, B. (2023). An agent-first preference in a patient-first language during sentence comprehension. Cognitive Science, 47(9), Article 9. https://doi.org/10.1111/cogs.13340 ↩
Rissman, L., & Majid, A. (2019). Thematic roles: Core knowledge or linguistic construct? Psychonomic Bulletin & Review, 26(6), 1850–1869. https://doi.org/10.3758/s13423-019-01634-5 ↩
DeLong, K. A., Urbach, T. P., & Kutas, M. (2005). Probabilistic word pre-activation during language comprehension inferred from electrical brain activity. Nature Neuroscience, 8(8), 1117–1121. https://doi.org/10.1038/nn1504 ↩
Bornkessel‐Schlesewsky, I., & Schlesewsky, M. (2009). The role of prominence information in the real‐time comprehension of transitive constructions: A cross‐linguistic approach. Language and Linguistics Compass, 3(1), 19–58. https://doi.org/10.1111/j.1749-818X.2008.00099.x ↩
Sánchez-López, M. (2026). Processing proto-agents and proto-patients: Eye-tracking and EEG evidence in Spanish [University of the Basque Country]. 10.17605/OSF.IO/WNAR8↩
Fillmore, C. J. (1971). Some problems for case grammar. In R. J. O’Brien (Ed.), Report of the 22nd annual round table meeting on linguistics and language studies (pp. 35–56). Georgetown University Press. ↩
Dowty, D. (1991). Thematic proto-roles and argument selection. Language, 67(3), 547–619. https://doi.org/10.1353/lan.1991.0021 ↩
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