As xAI announced a massive $6 Billion fundraising round at a whopping $24 Billion valuation, Elon Musk has spoken publicly about the need for massive amounts of data to train models that are echoed in his comments from a month ago “The two sources of unlimited data are synthetic data and real-world video,” and that “Tesla has a pretty big advantage in real-world video.”
As we all wade through the incredible era of life dominated by Artificial Intelligence (AI), we can’t help but notice that not everything is perfect. In particular, it is not difficult to notice that bias is inherent in the datasets that we rely on so much for making AI transform everything, but often result in upending our lives. AI models in general and Generative AI (GenAI) models in particular are trained with available datasets. If this data turns out to be biased, then every aspect of the model and its prediction or classification or recommendation could be biased and could also have a massive bullwhip effect. Data remains a fundamental bottleneck in our ability to let businesses and consumers realize the full potential of the expected and associated benefits
Dr MuckAI Girish writes: A majority of enterprises are now working with genAI projects, albeit, at varying levels. AI practitioners realize that creating scenarios and training their models across these and measuring the outcome to tweak the models are necessary to realize effective value from these models. One of the biggest hurdles in scenario analysis is the lack of access to relevant data.
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