Research

MIT-IBM Watson AI Lab Interns Working on Natural Language Improvement - PhD students interning with the MIT-IBM Watson AI Lab are focusing on enhancing natural language usage. - The interns are engaging in research projects to develop methods for transforming complex language into simplified and more accessible forms. - The aim is to address challenges in communication, making information and technology more understandable for a broader audience. - By improving natural language usage, the researchers hope to make AI systems more user-friendly and enable them to better assist and interact with users. Author's Take The PhD students interning with the MIT-IBM Watson AI Lab are targeting a crucial aspect of AI - natural language usage. By developing methods to simplify complex language and ...

Generative AI: How it could impact the 2024 US elections Summary: Generative artificial intelligence (AI) has the potential to impact the 2024 US elections. With advancements in AI, deepfake technologies using generative AI can create highly convincing fake videos and audio. Regulators, social media platforms, and the voting public are taking steps to address the challenges posed by generative AI. Companies like Facebook and Microsoft are developing tools to detect deepfake content and limit its spread. Voters are urged to be cautious and critical when evaluating content shared during election campaigns. Regulators and social media platforms tackle generative AI challenges Generative artificial intelligence (AI) is becoming more advanced, and deepfake technologies that leverage this AI a...

The Problem of Poor-Quality Data Sets in AI Training Summary: Many AI systems are being trained on poor-quality data sets. This can lead to amplification of existing inequities. Key Points: AI systems rely on data sets to learn and make decisions. However, many data sets are incomplete, biased, or reflect existing inequities. Training AIs on poor-quality data sets can result in biased decision-making. This can have negative impacts on certain groups of people. The problem highlights the need for better data collection and evaluation practices. Author's Take: The increasing use of poor-quality data sets for training AI systems raises concerns about the amplification of existing inequities. Biased decision-making by AIs can have negative consequences for certain groups of people. To en...

Olympiad-level AI system for geometry Summary: - Researchers at the Massachusetts Institute of Technology (MIT) have developed a new artificial intelligence (AI) system called AlphaGeometry, specifically designed to solve complex geometry problems. - AlphaGeometry was trained on a dataset of over 1.5 million problems from various math competitions, including the high-level International Math Olympiad. - The AI system employs a combination of pattern recognition, symbolic reasoning, and rule-based modeling to solve geometry problems. - Preliminary tests showed that AlphaGeometry performed at a similar level to human contestants in solving Olympiad-level geometry problems, sparking interest in integrating AI systems into math education. Key points: - AlphaGeometry is an AI system developed...

Advances in Personalized End-to-End Speech Recognition Main Points: The accuracy of end-to-end speech recognition has greatly improved with advancements in deep learning and automatic speech recognition. However, accurately recognizing personal content such as contact names remains a challenge. In a new study, researchers propose a personalization solution for an end-to-end system based on connectionist temporal classification. The solution utilizes a class-based language model, where a general language model provides context for named entity classes, and personal named entities are stored separately. Author's Take: Advances in deep learning and speech recognition have improved the accuracy of end-to-end speech recognition. However, recognizing personal content like contact names remains...

OpenAI Introduces Whisper: A State-of-the-Art Automatic Speech Recognition Model Main Ideas: OpenAI has released Whisper, an advanced automatic speech recognition (ASR) model that comes with an MIT license. ASR technology has various applications, including transcription services, voice assistants, and improving accessibility for people with hearing impairments. Whisper is trained on a large and diverse dataset of multilingual and multitask supervised data collected from the internet. The model achieves state-of-the-art accuracy and outperforms existing ASR systems on several benchmark datasets. By releasing Whisper, OpenAI aims to drive research and development in ASR technology and make it more accessible to the wider community. Author's Take: Whisper, OpenAI's new automatic speech rec...

OpenAI funds 10 teams to design AI governance tools Summary: OpenAI, the artificial intelligence research organization, has provided funding to 10 teams from around the world as part of their efforts to collaboratively develop tools and strategies for governing AI. The recipients of the grants include organizations focusing on areas such as policy and governance research, AI ethics, and algorithmic transparency. OpenAI hopes that these collaborations will enhance their understanding of AI's societal impact and contribute to the development of responsible AI technology. The organization also extended an invitation to researchers and engineers to join their ongoing initiatives. Key points: OpenAI has funded 10 projects aimed at collectively designing AI governance tools. Recipients...

Meta Earns $200,000 from Pro-Kremlin Ad Campaign, Research Finds Summary: Meta, the parent company of Facebook, reportedly earned over $200,000 from an ad campaign that promoted pro-Kremlin talking points and undermined local elections in Moldova. The campaign was seen by millions of users and targeted Moldovan citizens with political ads. Research reveals that the ads were part of a wider effort to influence public opinion and gain political advantage. Meta has faced criticism for its failure to prevent the spread of misinformation and political manipulation on its platforms. Author's Take: The research findings shed light on the extent of political advertising manipulation on social media platforms. Meta's significant earnings from the ad campaign reinforce concerns ab...

Smartphones versus Personal Computers: How We Process Deceptive Online Information Summary: A recent study from Pennsylvania State University reveals that the way we process deceptive online information depends on the device we are using, whether it’s a smartphone or a personal computer. The study involved participants who were shown deceptive information on both devices, and it was found that people tend to be more skeptical when viewing such content on a personal computer compared to a smartphone. The researchers suggest that this difference may stem from the different contexts and expectations associated with each device. The study highlights the need for a better understanding of how people perceive and react to online information based on the device they use. Key Points: - A study fr...

AI Language Models Take Up too Much Computing Power, Researchers Say Main Ideas: With the growing popularity of generative AI applications, there is a need to reduce the perceived latency and increase throughput. Foundation models (FMs) and large language models (LLMs) are pre-trained on massive amounts of data, which leads to high computing power requirements. Researchers argue that the power consumption and environmental impact of training and running these models at scale are substantial. Efforts are being made to improve efficiency and reduce the computing power usage of AI language models. One proposed solution is the use of smaller models that maintain good performance while reducing energy consumption. Author's Take: The rapid growth of generative AI applications has brought atten...