Large language models (LLMs) act as powerful tools for numerous tasks but their utilization as general-purpose decision-making agents poses unique challenges. In order to function effectively as agents, LLMs not only need to generate plausible text completions but they also need to show interaction and goal-directed behaviour to complete specific tasks. Two critical abilities required…
Neural Magic, an AI solutions provider, has recently announced a breakthrough in AI model compression with the introduction of a fully quantized FP8 version of Meta's Llama 3.1 405B model. This achievement is significant in the field of AI as it allows this massive model to fit on any 8xH100 or 8xA100 system without the…
Artificial Intelligence (AI) and Machine Learning (ML) technologies have shown significant advancements, particularly via their application in various industries. Autonomous agents, a unique subset of AI, have the capacity to function independently, make decisions, and adapt to changing circumstances. These agents are vital for jobs requiring long-term planning and interaction with complex, unpredictable environments. A…
The increased use and reliance on artificial intelligence (AI) systems have come with its share of benefits and risks. More specifically, AI systems are considered vulnerable to cyber-attacks, often resulting in harmful repercussions. This is mainly because their construction is complex, their internal processes are not transparent, and they are regularly targeted by adversarial attacks…
Theorem proving is an indispensable component in the realms of formal mathematics and computer science. Despite its significance, constructing proofs is a demanding task that is not just time-consuming but also liable to errors due to its complex nature. Mathematicians and researchers, therefore, end up investing substantial amounts of time and energy in this process.…
Theorem proving is an essential process in formal mathematics and computer science, involving the verification of mathematical theorems by deriving logical inferences. However, it is also a notoriously complicated and laborious process, often fraught with errors. There have been several attempts to develop tools to streamline the theorem proving process, but most tools currently available…
Researchers at MIT and the University of Washington have created a model that considers the computational constraints whilst predicting human behavior, which in turn could potentially make AI more efficient collaborators. These constraints can affect an individual or system's problem-solving abilities. The model can automatically infer these constraints by observing only a few prior actions…
MIT and University of Washington researchers have developed a model to understand and predict human behavior, which could improve the effectiveness of AI systems in collaboration with humans. Recognizing the suboptimal nature of human decision-making often due to computational constraints, the researchers created a model that factors in these constraints observed from an agent's previous…
Researchers from MIT and MIT-IBM Watson AI Lab have developed a machine-learning accelerator chip with enhanced security to guard against the two most common types of cyber attacks. The chip is designed to perform computations within a device, keeping crucial data like health records, financial information, or other sensitive information private. While this added security…
