{"id":6437,"date":"2024-01-26T17:07:55","date_gmt":"2024-01-26T22:07:55","guid":{"rendered":"https:\/\/solutionsreview.com\/data-management\/?p=6437"},"modified":"2024-01-29T10:06:53","modified_gmt":"2024-01-29T15:06:53","slug":"achieving-the-ai-moonshot-will-lead-to-next-generation-of-apps","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-management\/achieving-the-ai-moonshot-will-lead-to-next-generation-of-apps\/","title":{"rendered":"Achieving the AI Moonshot Will Lead to Next Generation of Apps"},"content":{"rendered":"

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Solutions Review\u2019s Contributed Content Series<\/u><\/a> is a collection of contributed articles written by thought leaders in enterprise tech<\/a>. In this feature, Couchbase<\/a> VP of Product Marketing Jeff Morris offers commentary on how achieving the AI moonshot will lead to the next generation of apps.<\/strong><\/i><\/span><\/p>\n

\"\"<\/a><\/span>AI is going mainstream. Industry-wide, the power and advantage of AI is undeniable \u2014 from government and law to marketing and sales, every business sector is trying to identify their own \u201cmoonshot\u201d opportunity.<\/p>\n

The original moonshot was made possible by the Saturn-V rocket, for which my dad made the space suits worn by the Apollo program\u2019s astronauts and which demanded a similar scale of resources to today\u2019s AI solutions. AI needs humans, plans, and other foundational technology underpinning the system in order to \u201creach the moon.\u201d Saturn-V made it to the moon because of engineers\u2019 intense work, massive funding and energy. AI-powered applications will rely on the same focus and attention to detail \u2014 complex algorithms, raw data, massive compute power, energy for data centers, legions of users and consideration of not only costs, but also impact and viability including–socially, economically, ethically and and environmentally.<\/p>\n

If organizations want to accomplish their own AI moonshot, it\u2019s important they utilize their required resources responsibly, efficiently and effectively.<\/p>\n

Stay on Course\u00a0<\/b><\/h3>\n

When implementing AI into an organization\u2019s tech stack, businesses must establish clear, concise goals. How will AI solutions benefit teams? Saturn-V\u2019s objective was clear: take astronauts to the moon. And even after the moon landings, the rocket was only used for launches in which its power was massive. This same level of intention and targeted ambitions should be applied to AI initiatives.<\/p>\n

AI\u2019s novelty can be challenging to avoid; while fun to experiment with, in most cases, project leaders need to take a honed-in approach to ensure the resources powering it aren\u2019t wasted on futile plans. It\u2019s also paramount that organizations lead AI advancements responsibly \u2014 from the underlying data to the privacy and security measures in place. Two potential negative outcomes can include AI hallucinations \u2014 which can produce inaccurate information \u2014 and the exposure of private, sensitive information if the right protocols are not taken.<\/p>\n

For example, suppose an AI model is trained on a dataset that contains limited information from a niche topic, such as zoo animals. If a user asks the model a question about a general topic, like astronomy, the system could hallucinate. When queried about what stars are made out of, it might respond with something like: \u201cTigers make stars out of sugar and space dust.\u201d This generated response is both scientifically incorrect and nonsensical, exposing the model\u2019s lack of understanding of astronomy.<\/p>\n

It would be in parallel with the Saturn-V landing on Mars instead of the moon. The time, money, and brain power were still spent on building the rocket to launch in space, but the end result did not go according to plan. Recognizing that the integrity of the information ingredients being fed to AI models must be considered as early in the development cycle as possible.<\/p>\n

Minimize Losses With Flexibility and Agility<\/b><\/h3>\n

For project leaders to stay on course and minimize losses (financially, strategically and environmentally) with their AI models and solutions, the foundational infrastructure beneath the system must be built with the utmost efficiency in mind. The computing power and datasets the model is pulling from should be physically positioned as close as possible \u2014 enter edge computing. Intelligently utilizing distributed computing resources and the cloud makes it possible to garner the following benefits:<\/p>\n