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Most businesses agree that AI is vital to staying competitive in today’s market. Per a Deloitte “State of AI in the Enterprise” study, 83% of companies that have adopted AI have reaped notable benefits. According to a Forbes article, adopting AI is also a way to impress consumers eager to work with companies prioritizing customer service. Some of the most common areas for corporations to apply AI are:
A notable minority of companies are also afraid of employing AI, and this caution is warranted. While it’s still a vastly beneficial step to take, there are considerable initial costs and weighty risks for incorrectly implementing AI tools in workflows. These are three leading risks of forgoing AI training and attempting to train your own LLM without expert AI services or proper data collection and annotation.
This risk is the most immediately painful to any business. Implementing AI solutions is currently a notoriously costly step. However, the risk is worth it when AI-generated content, AI translation, improved customer service, etc., brings in a substantial ROI and/or savings in operations costs. If a business leaves its AI development to people unprepared to handle it, the LLM may perform poorly or won’t help the company reach desired goals. Then, the initial funds for implementing the AI will become a financial loss. Additionally, so will the time and labor spent on (nonoptimally) implementing the LLM.
Work with AI training experts like Lionbridge. We’ve assisted many customers, including industry giants, in training their LLM to optimal performance. These customers can now use their LLMs to handle tasks such as:
A crucial step in training an LLM is ensuring the training data reflects diversity and tolerant viewpoints. With inadequate data collection, an AI system is more likely to share output that is biased, racist, misogynistic, discriminatory, etc. This scenario could spell out painful consequences for a company, whether its LLM assists with AI content generation, providing customer service, translating, etc. With poor data annotation or data validation, a company’s LLM could:
Work with AI training experts to ensure your LLM’s data collection prepares it to operate without bias, discrimination, or hateful speech. Consider working with Lionbridge’s Aurora AI Studio™, which offers community testing from a global, diverse group of testers.
There are many reasons that AI systems “hallucinate,” or create inaccurate output. They include:
These factors are all related to AI training. Without optimal AI training, it’s challenging to build AI trust. The inadequately-trained LLM may offer your customer bad or wrong advice, misrepresent your services or products, generate incorrect marketing copy, etc. Generally, the results could be disastrous.
Work with AI training experts to collect a wide set of training data that prepares your LLM to perform in a trustworthy manner. Get assistance crafting and testing prompts that the AI system will get often. Consider continuously working with AI experts to update and refresh your LLM as needed.
Ready to start your AI training with Lionbridge’s experts? We’ve helped many clients ensure their LLM investment yielded high ROI. Trust us to ensure your LLM helps your company achieve its goals — faster. Let’s get in touch.