“Real #AI isn't about giving the right answers to our questions, its about answering the questions we don't know to ask.” VisionArtificial IntelligenceMetaverseGenerative AiThings To Think On Author:Tom Golway
“Saw 2 articles, one says we are in the "golden age of #AI", the other says "Demand for data scientists is booming and will only increase". If we really were in a golden age of #AI, then there would be no need for #DataScientists.” Artificial IntelligenceData Scientist Book:Hybrid IT and Intelligent Edge Solutions Source: Hybrid IT and Intelligent Edge Solutions
“True progress in AI will come not from amassing more data, but from building smarter systems that understand the boundaries of their knowledge.” Artificial IntelligenceKnowledge QuotesEmerging Technologies Book:Entropy Reimagined: Order, Complexity, and Transformation Source: Entropy Reimagined: Order, Complexity, and Transformation
“The question is no longer what technology can do, but whether we can adapt fast enough to shape its trajectory before it shapes us beyond recognition. - Tom Golway” TechnologyTransformationArtificial IntelligenceEmerging Technologies Book:Epidemiology in a Hyperconnected World Source: Epidemiology in a Hyperconnected World
“Unleashing Reliable Insights from Generative AI by Disentangling Language Fluency and Knowledge Acquisition Generative AI carries immense potential but also comes with significant risks. One of these risks of Generative AI lies in its limited ability to identify misinformation and inaccuracies within the contextual framework. This deficiency can lead to mistakenly associating correlation with causation, reliance on incomplete or inaccurate data, and a lack of awareness regarding sensitive dependencies between information sets. With society’s increasing fascination with and dependence on Generative AI, there is a concern that the unintended consequence that it will have an unhealthy influence on shaping societal views on politics, culture, and science. Humans acquire language and communication skills from a diverse range of sources, including raw, unfiltered, and unstructured content. However, when it comes to knowledge acquisition, humans typically rely on transparent, trusted, and structured sources. In contrast, large language models (LLMs) such as ChatGPT draw from an array of opaque, unattested sources of raw, unfiltered, and unstructured content for language and communication training. LLMs treat this information as the absolute source of truth used in their responses. While this approach has demonstrated effectiveness in generating natural language, it also introduces inconsistencies and deficiencies in response integrity. While Generative AI can provide information it does not inherently yield knowledge. To unlock the true value of generative AI, it is crucial to disaggregate the process of language fluency training from the acquisition of knowledge used in responses. This disaggregation enables LLMs to not only generate coherent and fluent language but also deliver accurate and reliable information. However, in a culture that obsesses over information from self-proclaimed influencers and prioritizes virality over transparency and accuracy, distinguishing reliable information from misinformation and knowledge from ignorance has become increasingly challenging. This presents a significant obstacle for AI algorithms striving to provide accurate and trustworthy responses. Generative AI shows great promise, but addressing the issue of ensuring information integrity is crucial for ensuring accurate and reliable responses. By disaggregating language fluency training from knowledge acquisition, large language models can offer valuable insights. However, overcoming the prevailing challenges of identifying reliable information and distinguishing knowledge from ignorance remains a critical endeavour for advancing AI algorithms. It is essential to acknowledge that resolving this is an immediate challenge that needs open dialogue that includes a broad set of disciplines, not just technologists Technology alone cannot provide a complete solution.” TechnologyInnovationArtificial IntelligenceGenerative AiLarge Language Models Author:Tom Golway