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Sheryl Crow blasts Drake for using AI to replicate Tupac Shakur's voice: 'It's hateful' - Fox News: Sheryl Crow blasts Drake for using AI to replicate Tupac Shakur's voice: 'It's hateful'  Fox News http://dlvr.it/T8tdJX #ai #artificialintelligence

Today, most people are still trying to understand what Generative AI can do. Perhaps we should consider it from another angle—what Generative AI cannot do. This approach will help you comprehend, locate, and master the AI tools that are truly suitable for your team.

So important to understand. #retail must develop a comprehensive strategy that includes a variety of #AI techniques. #retailtech #genai

AI implementation in AEC can be more intensive, but this article raises important considerations. While the potential of GenAI to revolutionize design, documentation, and knowledge management is huge, we can't treat it as a magic wand. For each use case, we need to objectively assess if GenAI is truly the best fit, or if established AI techniques like ML, simulation, and knowledge graphs might deliver better results with lower risk and complexity. Where GenAI aligns well, such as generating design options, we should explore combining it with other AI methods to offset limitations and create robust hybrid solutions. For example, using GenAI to propose design alternatives but ML to validate and rank them, or leveraging knowledge graphs to feed GenAI with AEC domain expertise. It seems finding the right tool for the job, rather than just jumping on the GenAI bandwagon, could lead to more effective solutions in the long run. As an industry, cultivating a deeper understanding of the full AI spectrum and ideal applications is critical. Curious to hear others' perspectives - how is your firm thinking about matching the right AI approaches to each AEC use case? #AI #AEC #GenAI #MachineLearning #Innovation #CautiousOptimism

Choose your Gen AI use cases wisely!! In the seemingly congested .AI world, not all are really Gen AI enabled & not all business problems require hitting LLMs, LAMs & SLMs. knowledge discovery, deep conversational interfaces, speedy & accurate content generation etc. will require Gen AI based approach. let's look through the .AI smokescreen for fit proper solutions in the space.

Key thoughts around the GenAI hype: 1, The hype surrounding generative AI can lead to use of the technology where it is not a good fit, increasing the risk of higher complexity and failure of projects. 2, Overfocusing on GenAI can lead to ignoring the broader set of alternative and more established AI techniques 3, Combine AI techniques to create more robust systems in which varying techniques can mitigate others’ weaknesses.

GenAI is at times amazing, at times hallucinating, at times somewhere in between. However, it is only one tool in the AI toolbox. To succeed with AI, first one needs is a use case suitable to AI, a problem an AI system can solve. Next one needs to select the most suitable AI method to solve that problem irrespective of bias against or for any particular AI technique. Gartner wrote a good short read about this:

Important insight💡 for all #AI enthusiasts: #GenAI is just one of many AI capabilities. Let's not get caught up in the hype and miss out on tapping into the full range of AI capabilities. #GenerativeAI

Generative AI (GenAI) is making impact with its ability to craft realistic text, images, and videos. But it's important to remember: GenAI is just one facet of the vast and ever-evolving world of Artificial Intelligence. AI algorithms can crunch massive datasets to find the most efficient solutions to complex problems, from logistics planning to financial modeling. AI can create virtual worlds that mimic real-world scenarios, allowing us to test and refine processes before real-world implementation. AI can learn and apply specific rules or decision-making frameworks (heuristics) to tackle tasks like game playing, medical diagnosis, or fraud detection. "but that is not ALL I can do! said the cat... "