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How AI Platforms Can Improve Accuracy



The whole world is talking about AI.

Any belief that artificial intelligence could be limited to mere particular areas of the economy has flown out the window. Over the last year practically every for-profit company, non-profit organization, and even governmental agencies are rapidly pursuing integration of AI into their workflows.


Naturally, an increase in chatter around AI brings many questions. Asking about AI platforms before integration is important. At Louder Co., we view working with clients to answer such queries a core part of our process. Example: Most business leaders, aware of the constant drumbeat of cybersecurity, want to ensure their potential AI platform is secure. Others ask in-depth questions to confirm AI will make their employees more productive.


But one question looms above them all: “Does this AI platform provide accurate answers?” Amongst AI experts, accuracy is considered a “dimension of trust” between artificial intelligence and human users. Yet for small and medium business leaders, a more practical approach makes sense. The essence of accuracy? Possessing confidence an AI tool will provide the right answer at the right time when your staff is most in need of support.


So far, tech companies introducing AI to the marketplace—both as standalone products like ChatGPT and built into existing platforms like Microsoft Copilot—have had their eyes opened to accuracy’s importance in 2023. Accuracy transformed from another performance factor to be considered the single most important metric, making or breaking any AI offering.


The best example of this transformation is one costly mistake made by Google. In February, the company released a demo for Bard AI showing off its potential to advance AI usage by pairing it with the largest internet brand. There was just one problem—sharp-eyed observers noted the AI provided an inaccurate answer to the question it was asked. (The demo included a query about discoveries made by the James Webb Space Telescope, which Bard answered by claiming the telescope took the first pictures of “exoplanets” ever captured.)


The problem? It’s an incorrect answer.


NPR noted exoplanets have been photographed from Earth since 2004. This may seem like a small inaccuracy, but in business terms, it heralds a costly mistake—like shipping the wrong product to a customer. It was also the world’s first glimpse of Bard, magnifying the situation’s gravity. The error had a big financial impact, too. The company lost $100 billion in market capitalization as its shares slid by as much as 9. More importantly, Google and every other AI developer learned a key lesson that day: Accuracy is king.


Now let’s consider how AI developers are working to improve accuracy.



Better Training Data

AI companies have already realized one of the oldest computing rules also applies to the latest innovations. “Garbage in, garbage out” or GIGO is the principle that if weak data goes into a system, weak data will come out. In the world of AI, if a system is trained poorly, it causes problems like data shift, where the info it experiences in the real world doesn’t match well with its training data. To combat this challenge, a renewed focus on excellent training data is taking place at nearly every AI developer.


In November, OpenAI announced plans on diversifying and expanding its training data sets for ChatGPT and other GPT-based AI models it develops. According to the company, “To ultimately make AI that is safe and beneficial to all of humanity, we’d like AI models to deeply understand all subject matters, industries, cultures, and languages, which requires as broad a training data set as possible.” The result of stronger training data for your business? Better answers and accuracy to assist your employees.


Curated Data from Experts

While an emphasis on larger amounts of training data is certainly beneficial to AI applications, accuracy isn’t only reliant on the amount of data. In short, we must consider if the sources an AI is trained on can correctly comprehend the information. If your business is having an electrical problem, you really aren’t interested in the advice of your plumber, carpet cleaner, or the UPS delivery person. You want answers from your electrician. AI platforms have a similar dilemma. Faced with the problem of getting specific answers to important questions, they are increasingly turning to specialized training data created by experts.


One example of an effectively curated AI tool is Thomson Reuters’ Document Intelligence. It gives lawyers an edge by speeding up tedious tasks like document review. But to be truly accurate, this AI system must think and act like a lawyer—accomplished by having lawyers train it. Thomson Reuters’ team of law editors contributed more than 15,000 hours to ensure the company’s platform would perform accurately. The result is indeed a better, more accurate AI platform. Louder Co. only expects this trend to continue.



Improved Context and Query Systems

Some things about communicating with an AI are akin to speaking with a human. The more context we can provide and the more specific our questions are with another person, the better answer we may expect. Anyone who has held a conversation with a teenager who prefers one-word answers has experienced this firsthand! Likewise, when AI platforms permit more context in queries, the system can better provide an accurate response.


This is exactly what OpenAI has done with ChatGPT Enterprise. Louder Co.’s favorite feature in the new offering is it provides business users a much larger token context window. (In the generative AI world, tokens are the “building blocks” of natural language, allowing a system to respond efficiently and accurately.) In fact, the token context window is four times larger than standard ChatGPT. This means business customers can confidently provide more information to ChatGPT Enterprise when querying the system, resulting in more accurate responses.


How to Find the Most Accurate AI for Your Business

AI for business applications is not a one-size-fits-all solution. To source the platform offering your business the best comprehensive performance, factoring in accuracy, user friendliness, compatibility with extant software, and ease of integration into your processes, our team of AI experts work diligently to compare your company and your goals to the entire universe of AI offerings.


Based on this assessment, we can then guide your decision-making process, choosing the AI platform to empower your business for future growth and profitability. To find your ideal AI offering, contact Louder Co. today.





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