I sat down with Teresa Tung to be taught extra in regards to the altering nature of information and its worth to an AI technique.
AI success relies on a number of elements, however the important thing to innovation is the standard and accessibility of a company’s proprietary information.
I sat down with Teresa Tung to debate the alternatives of proprietary information and why it’s so important to worth creation with AI. Tung is a researcher whose work spans breakthrough cloud applied sciences, together with the convergence of AI, information and computing capability. She’s a prolific inventor, holding over 225 patents and purposes. And as Accenture’s International Lead of Information Functionality, Tung leads the imaginative and prescient and technique that ensures the corporate is ready for ever-changing information developments.
We mentioned a number of subjects, together with Teresa’s six insights.
Lastly, we concluded with Teresa’s Recommendation for enterprise leaders utilizing or inquisitive about AI
Susan Etlinger (SE): In your latest article, “The brand new information necessities,” you laid out the notion that proprietary information is a corporation’s aggressive benefit. Would you elaborate?
Teresa Tung (TT): Till now, information has been handled as a undertaking. When new insights are wanted, it could possibly take months to supply the info, entry it, analyze it, and publish insights. If these insights spur new questions, that course of should be repeated. And if the info workforce has bandwidth limitations or funds constraints, much more time is required.
“As an alternative of treating it as a undertaking—an afterthought—proprietary information ought to be handled as a core aggressive benefit.”
Generative AI fashions are pre-trained on an present corpus of internet-scale information, which makes it straightforward to start on day one. However they don’t know your enterprise, individuals, merchandise or processes and, with out that proprietary information, fashions will ship the identical outcomes to you as they do your rivals.
Corporations make investments day-after-day in merchandise primarily based solely on their alternative. We all know the chance of information and AI—improved determination making, decreased threat, new paths to monetization—so shouldn’t we take into consideration investing in information equally?
SE: Since a lot of an organization’s proprietary data sits inside unstructured information, are you able to speak about its significance?
TT: Sure, most companies run on structured information—information in tabular kind. However most information is unstructured. From voice messages to pictures to video, unstructured information is excessive constancy. It captures nuance. Right here’s an instance: if a buyer calls buyer assist and leaves a product evaluate, that information may very well be extracted by its parts and transferred to a desk. However with out nuanced inputs just like the buyer’s tone of voice and even curse phrases, there isn’t an entire and correct image of that transaction.
Unstructured information has traditionally been difficult to work with, however generative AI excels at it. It truly wants unstructured information’s wealthy context to be educated. It’s so necessary within the age of generative AI.
SE: We hear loads about artificial information nowadays. How do you concentrate on it?
TT: Artificial information is important to fill in information gaps. It permits firms to discover a number of eventualities with out the intensive prices or dangers related to actual information assortment.
Promoting companies can run varied marketing campaign photos to forecast viewers reactions, for instance. For automotive producers coaching self-driving vehicles, pushing vehicles into harmful conditions isn’t an choice. Artificial information teaches AI—and due to this fact the automobile—what to do in edge conditions, together with heavy rain or a shock pedestrian crossing.
Then there’s the concept of data distillation. In the event you’re utilizing the approach to create information with a bigger language mannequin—let’s say, a 13-billion-parameter mannequin—that information can be utilized to wonderful tune a smaller mannequin, making the smaller mannequin extra environment friendly, value efficient, or deployable to a smaller system.
AI is so hungry. It wants consultant information units of fine eventualities, edge circumstances, and every little thing in between to be related. That’s the potential of artificial information.
SE: Unstructured information is usually information that human beings generate, so it’s usually case-specific. Are you able to share extra about why context is so necessary?
TT: Context is vital. We are able to seize it in a semantic layer or a website data graph. It’s the that means behind the info.
Take into consideration each area knowledgeable in a office. If an organization runs a 360-degree buyer information report that spans domains and even techniques, one area knowledgeable will analyze it for potential clients, one other for customer support and assist, and one other for buyer billing. Every of those consultants needs to see all the info however for their very own function. Realizing developments inside buyer assist might affect a advertising and marketing marketing campaign method, for instance.
Phrases usually have totally different meanings, as nicely. If I say, “that’s sizzling for summer season,” context will decide whether or not I used to be implying temperature or pattern.
Generative AI helps floor the appropriate info on the proper time to the appropriate area knowledgeable.
SE: Given the tempo and energy of clever applied sciences, information and AI governance and safety are high of thoughts. What developments are you noticing or forecasting?
TT: New alternatives include new dangers. Generative AI is really easy to make use of, it makes everyone an information employee. That’s the chance and the danger.
As a result of it’s straightforward, generative AI embedded in apps can result in unintended information leakage. Because of this, it’s important to assume via all of the implications of generative AI apps to cut back the danger that they inadvertently reveal confidential info.
We have to rethink information governance and safety. Everybody in a company wants to concentrate on the dangers and of what they’re doing. We additionally want to consider new tooling like watermarking and confidential compute, the place generative AI algorithms may be run inside a safe enclave.
SE: You’ve mentioned generative AI can jumpstart information readiness. Are you able to elaborate on that?
TT: Positive. Generative AI wants your information, however it could possibly additionally assist your information.
By making use of it to your present information and processes, generative AI can construct a extra dynamic information provide chain, from seize and curation to consumption. It might classify and tag metadata, and it could possibly generate design paperwork and deployment scripts.
It might additionally assist the reverse engineering of an present system previous to migration and modernization. It’s widespread to assume information can’t be used as a result of it’s in an outdated system that isn’t but cloud enabled. However generative AI can jumpstart the method; it could possibly assist you to perceive information, map relationships throughout information and ideas, and even write this system together with the testing and documentation.
Generative AI modifications what we do with information. It might simplify and pace up the method by changing one-off dashboards with interactivity, like a chat interface. We must always spend much less time wrangling information into structured codecs by doing extra with unstructured information.
SE: Lastly, what recommendation would you give to enterprise and expertise leaders who wish to construct aggressive benefit with information?
TT: Begin now or get left behind.
We’ve woken as much as the potential AI can convey, however its potential can solely be reached together with your group’s proprietary information. With out that enter, your end result would be the identical as everybody else’s or, worse, inaccurate.
I encourage organizations to concentrate on getting their digital core AI-ready. A trendy digital core is the expertise functionality to drive information in AI-led reinvention. It’s your group’s mixture of cloud infrastructure, information and AI capabilities, and purposes and platforms, with safety designed into each degree. Your information basis—as a part of your digital core—is crucial for housing, cleaning and securing your information, guaranteeing it’s prime quality, ruled and prepared for AI.
And not using a robust digital core, you don’t have the proverbial eyes to see, mind to assume, or arms to behave.
Your information is your aggressive differentiator within the period of generative AI.
Teresa Tung, Ph.D. is International Information Functionality Lead at Accenture. A prolific inventor with over 225 patents, Tung focuses on bridging enterprise wants with breakthrough applied sciences.
Study extra about get your information AI-ready:
- Discover ways to develop an clever information technique that endures within the period of AI with the downloadable e-book.
- Watch this on-demand webinar to listen to Susan and Teresa go deeper on extract probably the most worth from information to distinguish from competitors. Study new methods of defining information that may assist drive your AI technique, the significance of getting ready your “digital core” prematurely of AI, and rethink information governance and safety within the AI period.
Go to Azure Innovation Insights for extra govt perspective and steering on rework your enterprise with cloud.