New mothers working in software development are staring down an AI-pilled workplace they barely recognize. As Danielle settled into the rhythms of new motherhood, her profession underwent a drastic reinvention. Danielle, who asked to use her first name to avoid damaging her job prospects, worked as a software developer at a car company in Portland, Oregon. Before she left the workforce in mid-2024, barely anybody used AI to write code; by the time she was ready to return, a year later, it had become the expectation. Once upon a time, she had been drawn to coding for the job security it offered, but AI was threatening to upend that.

There's a mad dash to automate the world's most hated calls. You'll hear from an AI debt collector sometime soon. She introduced herself as Eve, but Ben knew right away that the voice on the other end of the line was a bot. She also knew how much money he'd owed a former landlord ($266). She didn't seem to know that he'd settled with a collection agency five months prior. Eve said she was an AI agent from ProCollect and was calling to collect a debt.

Cargo documents appear to show Sightline has shipped its technology to Elbit Systems, an Israeli arms manufacturer that provides drones to the country's military. Cargo documents appear to show Sightline has shipped its technology to Elbit Systems, an Israeli arms manufacturer that provides drones to the country's military. A nti-war activists in Portland, Oregon, are pushing city authorities to ensure no local resources, tax breaks or investments support a local company that appears to be supplying artificial intelligence software to the Israeli military. The company, Sightline Intelligence, manufactures AI-supported video technology that is used in drones to interpret target movements and make quick decisions based on the perceived threat level. Cargo documents appear to show Sightline has shipped its technology to Elbit Systems, an Israeli arms manufacturer that provides drones to that country's military and exports to others.

The dataset and the baseline code will be made publicly available in a dedicated GitHub repository upon acceptance. License TempEL is distributed under Creative Commons Attribution-ShareAlike 4.0 International license (CCBY-SA 4.0).1 Maintenance The maintenance and extension to further temporal snapshots of TempEL will be carried out by the authors of the paper. Additionally, we will make the code public to create potential new variations and extensions of TempEL using a number of hyperparameters (see Sections A.4 and A.5 for further details). A.2 Datasheet for TempEL In this section we provide a more detailed documentation of the dataset with the intended uses. We base ourselves on the datasheet proposed by [1]. A.2.1 Motivation For what purpose was the dataset created? The TempEL dataset was created to evaluate how the temporal change of anchor mentions and that of target Knowledge Base (KB; i.e., modification or creation of new entities) affects the entity linking (EL) task. This contrasts with the currently existing datasets [9, 7, 8, 6], which are associated with a single version of the target KB such as the Wikipedia 2010 for the widely adopted CoNLL-AIDA[2] dataset. We expect that TempEL will encourage research in devising new models and architectures that are robust to temporal changes both in mentions as well as in the target KBs. Who created the dataset and on behalf of which entity?

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The mysterious "golden orb" pulled from over two miles beneath the Gulf of Alaska in 2023 has been identified as a remnant of a rare giant deep-sea anemone, researchers say.

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Michael Dell and Susan Dell became the first donors to give more than $1 billion to the University of Texas at Austin, funding a massive AI-native hospital and research campus.

How do you go about integrating causal knowledge into decision systems or agents? We sat down with Matteo Ceriscioli to find out about his research in this space. This interview is the latest in our series featuring the AAAI/SIGAI Doctoral Consortium participants. Could you start by telling us a bit about your PhD - where are you studying, and what's the broad topic of your research? The idea is to integrate causal knowledge into agents or decision systems to make them more reliable.