John Laird, the John L. Tishman Professor of Engineering, has been awarded the 2018 Herbert A. Simon Prize for Advances in Cognitive Systems along with his collaborator Prof. Paul Rosenbloom of the University of Southern California. This award recognizes the pair's research on cognitive architectures, especially their Soar project, their applications to knowledge-based systems and models of human cognition, and their contributions to theories of representation, reasoning, problem solving, and learning. The recipients, the awarding committee writes, have been "energetic contributors to AI and cognitive science" for over 30 years. Laird's and Rosenbloom's interdisciplinary and integrative research, both jointly and individually, has addressed many facets of high-level cognition, and their contributions to Soar have helped create one of the industry's most successful tools for developing intelligent systems. Soar is a general cognitive architecture for developing systems that exhibit intelligent behavior.

This is the Proceedings of the ICML Expressive Vocalization (ExVo) Competition. The ExVo competition focuses on understanding and generating vocal bursts: laughs, gasps, cries, and other non-verbal vocalizations that are central to emotional expression and communication. ExVo 2022, included three competition tracks using a large-scale dataset of 59,201 vocalizations from 1,702 speakers. The first, ExVo-MultiTask, requires participants to train a multi-task model to recognize expressed emotions and demographic traits from vocal bursts. The second, ExVo-Generate, requires participants to train a generative model that produces vocal bursts conveying ten different emotions. The third, ExVo-FewShot, requires participants to leverage few-shot learning incorporating speaker identity to train a model for the recognition of 10 emotions conveyed by vocal bursts.

Fawkes may prevent a new facial recognition system from recognizing a person but can't change or sabotage the existing systems that have already been trained on one's unprotected images. Thus, Valeriia Cherepanova and her colleagues at the University of Maryland, one of the teams at ICLR, recently addressed this issue and developed a tool called LowKey. This tool expands on Fawkes by applying perturbations to images based on a stronger adversarial attack, which can also fool the pretrained commercial models.

Recommending priorities for future cooperation, particularly in R&D areas where each partner shares strong common interest (e.g., interdisciplinary research and intelligent systems) and brings complementary challenges, regulatory or cultural considerations, or expertise to the partnerships; Promoting research and development in AI, focusing on challenging technical issues, and protecting against efforts to adopt and apply these technologies in the service of authoritarianism and repression. We intend to establish a bilateral Government-to-Government dialogue on the areas identified in this vision and explore an AI R&D ecosystem that promotes the mutual wellbeing, prosperity, and security of present and future generations. Signed in London and Washington on 25 September 2020, in two originals, in the English language.

The following declaration was released by the Governments of the United States of America and the United Kingdom of Great Britain and Northern Ireland during the September 25 inaugural meeting of the Special Relationship Economic Working Group. We intend to establish a bilateral government-to-government dialogue on the areas identified in this vision and explore an AI R&D ecosystem that promotes the mutual wellbeing, prosperity, and security of present and future generations. Signed in London and Washington on September 25, 2020, in two originals, in the English language.

In this post, I will be showing a simple example of object recognition in images using the TensorFlow library from Smalltalk. Whenever you start entering the world of AI and Machine Learning you will notice immediately that Python has been widely accepted as the "default" programming language for these topics. I am not against Python and I believe that people are using it for a reason. However, I do believe that providing alternatives is a good thing, too. And Smalltalk could be that alternative you are looking for.

We've heard this advice when it comes to everything from what you should order at a new restaurant to who you should marry. But as you might imagine, some decisions are better not left to the gut. That's where technology comes in. Hiring managers, company executives and everyone else in an organization benefit when decisions are informed by data. Christy Pettey at Gartner, however, cautions that there is a balance: Decision-makers must allow technology to complement, rather than replace, gut feelings and natural tendencies.

We will work together to foster global economic growth, while harnessing the power of technological innovation, in particular digitalization, and its application for the benefit of all. We are resolved to build a society capable of seizing opportunities, and tackling economic, social and environmental challenges, presented today and in the future, including those of demographic change. This recovery is supported by the continuation of accommodative financial conditions and stimulus measures taking effect in some countries. However, growth remains low and risks remain tilted to the downside. Most importantly, trade and geopolitical tensions have intensified. We will continue to address these risks, and stand ready to take further action. Fiscal policy should be flexible and growth-friendly while rebuilding buffers where needed and ensuring debt as a share of GDP is on a sustainable path. Monetary policy will continue to support economic activity and ensure price stability, consistent with central banks' mandates. Central bank decisions need to remain well communicated.

A*STAR researchers working with colleagues in Japan have developed a method by which robots can automatically recognize an object as a potential tool and use it, despite never having seen it before. For humans, the ability to recognize and use tools is almost instinctive. There are also many examples in which tool use seems hardwired into the brain of animals: some birds and primates use sticks or stones to obtain food, for example. One proposed reason for this neurologically embedded ability to use tools is that the animal's brain perceives the external object as an extension of its own body. Inspired by this idea, Keng Peng Tee and his colleagues from the A*STAR Institute for Infocomm Research, along with Gowrishankar Ganesh from the CNRS-AIST Joint Robotics Laboratory located in Tsukuba, Japan developed an algorithm that enables robots to recognize, and immediately use tools that they have never seen before.

AI to advise us how to structure our days for the most fulfilling life?Depositphotos enhanced by CogWorld "What people don't realize is that we are on the verge of a paradigmatic shift in thinking on par with the Copernican Revolution," says Dr. Angel Iscovich. "The way we make our most personal decisions--from our partners, to our health choices, to yes, even our daily routines-- is going to transform due to the falling cost of data storage and rising computing power." If you only happened to glance at what Dr. Iscovich said, let me repeat the latter part as it bears further mention. According to him, in the future, AI will advise us how to structure our days for the most fulfilling life. It will literally tell us what to do for optimal living.