Artificial intelligence (AI) is transforming the world in ways that we could not have imagined a few years ago. From creating new drugs and materials, to enhancing our entertainment and communication, to solving some of the most challenging problems facing humanity, AI is making a huge impact on our lives. In this blog post, we will highlight some of the most interesting and important news stories about AI from the last week.

One of the challenges of developing AI technologies is ensuring that they can understand and communicate with people from different languages and cultures. This is especially true for African languages, which are often underrepresented and underserved by existing AI tools. A team of researchers from Africa and Europe has proposed a roadmap to help AI technologies speak African languages, by creating datasets, models, and standards for natural language processing (NLP) tasks. The roadmap aims to foster collaboration and innovation among researchers, developers, and users of AI in Africa, and to promote the linguistic diversity and inclusion of African languages in the global AI landscape. Source

ChatGPT is one of the most advanced and popular AI models for generating natural language texts. It can write anything from essays and stories, to jokes and tweets, based on a given prompt or context. But can it also help with chemistry? A team of researchers from Stanford University has shown that ChatGPT can be turned into a 'chemistry assistant', by prompting it to perform tasks such as predicting chemical reactions, drawing molecular structures, and explaining chemical concepts. The researchers found that ChatGPT can generate accurate and useful responses for many chemistry-related queries, demonstrating its potential as a tool for learning and discovery in chemistry. Source

The brain is one of the most complex and powerful systems in nature, capable of processing vast amounts of information and performing sophisticated computations. How can we emulate the brain's function using artificial materials? A team of researchers from Japan has discovered a quantum material that exhibits 'non-local' behavior that mimics brain function. The material is composed of nanoscale magnets arranged in a honeycomb lattice, which can be manipulated by electrical stimuli. The researchers found that the electrical stimuli can affect not only the neighboring magnets, but also distant ones, creating complex patterns of magnetization that resemble neural activity. This discovery could pave the way for creating brain-like computers with minimal energy consumption. Source

AI systems are often used to make decisions or organize knowledge that affect people's lives, such as recommending products, diagnosing diseases, or ranking search results. However, these systems may also exhibit bias or errors that can harm or mislead users. How can we ensure that AI systems are fair, accurate, and trustworthy? A team of researchers from Canada has developed a new explainable AI model that reduces bias and enhances trust in AI decision-making and knowledge organization. The model uses a novel technique called 'contrastive explanation', which compares different scenarios or alternatives to provide clear and intuitive explanations for why an AI system made a certain decision or organized knowledge in a certain way. The model can help users understand the rationale behind AI outputs, identify potential sources of bias or error, and provide feedback or corrections to improve the system's performance.

Artificial intelligence (AI) is transforming the world in ways that we could not have imagined a few years ago. From creating new drugs and materials, to enhancing our entertainment and communication, to solving some of the most challenging problems facing humanity, AI is making a huge impact on our lives. In this blog post, we will highlight some of the most interesting and important news stories about AI from the last week.

One of the challenges of developing AI technologies is ensuring that they can understand and communicate with people from different languages and cultures. This is especially true for African languages, which are often underrepresented and underserved by existing AI tools. A team of researchers from Africa and Europe has proposed a roadmap to help AI technologies speak African languages, by creating datasets, models, and standards for natural language processing (NLP) tasks. The roadmap aims to foster collaboration and innovation among researchers, developers, and users of AI in Africa, and to promote the linguistic diversity and inclusion of African languages in the global AI landscape. Source

ChatGPT is one of the most advanced and popular AI models for generating natural language texts. It can write anything from essays and stories, to jokes and tweets, based on a given prompt or context. But can it also help with chemistry? A team of researchers from Stanford University has shown that ChatGPT can be turned into a 'chemistry assistant', by prompting it to perform tasks such as predicting chemical reactions, drawing molecular structures, and explaining chemical concepts. The researchers found that ChatGPT can generate accurate and useful responses for many chemistry-related queries, demonstrating its potential as a tool for learning and discovery in chemistry. Source

The brain is one of the most complex and powerful systems in nature, capable of processing vast amounts of information and performing sophisticated computations. How can we emulate the brain's function using artificial materials? A team of researchers from Japan has discovered a quantum material that exhibits 'non-local' behavior that mimics brain function. The material is composed of nanoscale magnets arranged in a honeycomb lattice, which can be manipulated by electrical stimuli. The researchers found that the electrical stimuli can affect not only the neighboring magnets, but also distant ones, creating complex patterns of magnetization that resemble neural activity. This discovery could pave the way for creating brain-like computers with minimal energy consumption. Source

AI systems are often used to make decisions or organize knowledge that affect people's lives, such as recommending products, diagnosing diseases, or ranking search results. However, these systems may also exhibit bias or errors that can harm or mislead users. How can we ensure that AI systems are fair, accurate, and trustworthy? A team of researchers from Canada has developed a new explainable AI model that reduces bias and enhances trust in AI decision-making and knowledge organization. The model uses a novel technique called 'contrastive explanation', which compares different scenarios or alternatives to provide clear and intuitive explanations for why an AI system made a certain decision or organized knowledge in a certain way. The model can help users understand the rationale behind AI outputs, identify potential sources of bias or error, and provide feedback or corrections to improve the system's performance.