![]() ![]() ![]() Not every manager wants to stare at spreadsheets all day to understand what’s going on in their business. And this is essential to thriving in the hyper-speed economy. Corporations are beginning to consider AI as a “second brain” for decision making. Because AI is just a powertool and it still requires people who know how to apply its deep analysis strategically. When an organization can experiment with data and predictions, it opens up a part of the human brain that thinks in multiple scenarios and outcomes. Just as weather modeling has become a fantastically efficient and adaptive set of systems, any enterprise can take models and apply them to their business and industry for new predictions and insights. What does our data tell us over any period? We have moved beyond “data processing” data analysis Which reveals new insights. ![]() This is the initial stage of awareness and idea formation. Once data is no longer dark, but becomes accessible and able to be “mined”, it can be used in a million ways to find out how a company is doing in its industry. But here are 7 key categories that I think reflect the goals of the modern enterprise. There are many areas where machine learning and deep learning, the two primary galaxies of AI, can be applied to the dark data flood. Zacks has released a special report that uncovers stocks hiding under the Wall Street radar, plus 4 others that are must-buys. This phenomenon is already pushing the adoption rates of TikTok and Instagram by 3X and 10X respectively. This is an Internet and iPhone-scale effect.ĬhatGPT answers follow-up questions…admits mistakes…challenges erroneous grounds…and even rejects unreasonable requests. By 2030, AI could boost the global economy by $15.7T. One little-known company is at the center of a particularly talented artificial intelligence field. So what exactly is it that leading enterprises in every sector from manufacturing and energy to health care and retail want to accomplish with all their data? It was the spark that made hundreds of other global enterprises realize they needed to upgrade their datacenter infrastructure – or else. I think the biggest preview of this catalyst was that the company was also able to share in May that its first three customers were already lined up, Alphabet, Microsoft, and Meta. I told investors throughout June and July that NVIDIA would beat even their most optimistic forecasts for sales and easily top my $12 billion guidance for this current quarter, which started in August. When NVIDIA announced in May that it would not only beat its previous Q2 revenue guidance by $4 billion, but that it was launching its latest GPU system, the DGX GH200 - which was said to be 50% faster than the previous generation - the stock soared. That’s because every Global 2000 company is collecting terabytes of log files every day that most people didn’t know how to use even a year ago.īut what used to be a black hole with infinite gravity and compression has now become goldmine of possibility, It has been estimated by data-centric companies like Splunk that more than 50% of corporate data is “in the dark”. So it’s a good idea to review the key forces driving the AI tsunami that has allowed NVIDIA CEO Jensen Huang to predict a $250 billion per year transformation… as global enterprises shift accelerated hyperscale computing This only comes from the GPU (Graphics Processing Unit) system. ![]() Since then, I think it’s all just coming to a head in the huge surprise demand for AI tools that are called “massively parallel architectures.” And there’s still time to ride that wave for a ride that will last for many years. ![]()
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