AI Challenges
Large Language Models (LLMs) rely on extensive memory to store and manipulate vast datasets, a key factor that allows them to learn from past inputs and improve their linguistic abilities over time. But what if, alongside remembering, LLMs could also benefit from adaptive forgetting? The notion of...
11 Strategies for Unifying Structured and Unstructured Data in Generative AI The convergence of structured and unstructured data represents a pivotal moment in the evolution of Generative AI
The field of Natural Language Processing (NLP) has witnessed significant advancements, yet it continues to face notable challenges and considerations. These obstacles not only highlight the complexity of human language but also underscore the need for careful and responsible development of NLP...
The rapid advancement of artificial intelligence (AI) provides unprecedented opportunity for innovation and greater productivity, but an important question remains: how do you control AI? Businesses eager to harness the power of AI know the potential of the technology, but providing AI complete...
We remain optimistic about generative artificial intelligence’s (GenAI) influence on work because we’ve seen the results of integrating AI into organizations. While there may be challenges for companies considering AI — potentially enough to suggest AI “isn’t ready” for mainstream use — we are...
The world is changing because of artificial intelligence (AI), but for many businesses it’s not clear how we get from the way things are now to the hyper-productive utopia pitched by AI solutions. For many executives and VPs tasked with integrating AI into their business, their focus is on...