[AI]Language Processing Units (LPUs): Paving the way for advanced voice AI in contact centres

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Have you heard about Language Processing Units (LPUs) yet? If you haven’t, prepare to be wowed! LPUs are specialised processors engineered specifically for language-related tasks. They differ from other processors that handle multiple tasks simultaneously. The LPU combines the best of the Central Processing Unit (CPU) – great at sequential tasks, and the Graphic Processing Unit (GPU) – great at concurrent tasks.

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is the creator of the world’s first LPU, and in terms of processing, they are the new sheriff in town: 10x faster, 90% less latency, and minimal energy than traditional Graphics Processing Units (GPUs). So, what does this mean for AI in the future?

Imagine you’re at a bustling coffee shop trying to place an order. The barista needs to hear your order, understand it amidst the noise, and get it right – quickly and efficiently. This is not unlike the daily challenges faced in customer service, where clarity and speed are paramount. Enter Language Processing Units or LPUs, the latest buzz in tech circles, especially in customer service. These specialised processors are designed to handle these exact challenges in AI-driven interactions.

Before LPUs entered the scene, CPUs and GPUs did the heavy lifting. Let’s break it down:

The Barista (CPU)

The barista is like a CPU (Central Processing Unit). This person is very skilled and can handle various tasks, from making coffee to taking orders and cleaning up. However, because the barista does everything, each task takes a bit of time, and they can only do one thing at a time. If there’s a rush of customers, the barista might get overwhelmed and slow down.

The Team of Baristas (GPU)

Now, imagine you have a team of baristas (GPU – Graphics Processing Unit). Each barista specialises in a specific task. One makes espresso, another steams milk, and another adds flavourings. This team can handle many customers simultaneously, especially if everyone wants the same type of coffee, because they can work in parallel. However, if customers start asking for highly customised orders, the team might not be as efficient since their specialisation is more suited to repetitive tasks.

Super Barista (LPU)

Finally, picture a super-efficient barista (LPU – Language Processing Unit). This ****** is specifically designed to handle complex and varied coffee orders swiftly. It can understand detailed instructions quickly and adapt to each customer’s unique preferences with incredible speed and accuracy. Unlike the single barista or the team of baristas, the ****** barista excels at processing these intricate orders without slowing down, no matter how many customers are lined up or how complex the orders are.

LPUs bring this level of personalisation and efficiency to customer service AI, making every interaction smoother and more intuitive. Let’s explore how these new processors are reshaping the landscape of AI communications.

Taking AI Interactions to The Next Level in Contact Centres

As far as contact centre operations go, the speed and accuracy of AI applications are crucial to success. LPUs transform voice AI, most notably enriching real-time speech-to-text and text-to-speech conversions. This improvement is key for developing more natural and efficient customer service interactions, where delays or misunderstandings can negatively impact customer satisfaction.

One of the standout benefits of LPUs is their ability to tackle the latency challenge. In customer service, where every second counts, reducing latency improves the customer experience and boosts the service’s efficiency. LPUs ensure that the dialogue between the customer and the AI is as smooth and seamless as if it were between two humans, with minimal delay.

Tatum Bisley, product lead at contact centres solutions provider

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, says: “Language Processing Units are not just changing how we interact with technology in contact centres; they’re setting the stage for a future where real-time processing is seamlessly integrated across various sectors. With LPUs, we’re seeing a dramatic reduction in latency, making interactions with finance or healthcare customers as smooth and natural as face-to-face conversations.

“Much like how modern CGI has made it difficult to distinguish between real and computer-generated imagery, LPUs work behind the scenes to ensure a seamless customer experience. The average person doesn’t talk about the CPU in their laptop or the GPU in their gaming console; similarly, they won’t discuss LPUs. However, they will notice how effortlessly and naturally their interactions unfold.

“The potential applications of this technology extend far beyond our current use cases. Imagine LPUs in autonomous vehicles or real-time language translation services, where split-second processing can make a world of difference. We are just scratching the surface of what’s possible.”

The Impact of LPUs on AI’s Predictive Capabilities

Beyond merely improving real-time interactions, LPUs profoundly impact AI systems’ predictive capabilities. This is because LPUs can rapidly process large datasets that will boost AI’s predictive functions. This enhancement enables AI to react to inputs more swiftly, anticipate user needs and adapt interactions accordingly. By handling sequential predictions with much-improved efficiency, LPUs allow AI to deliver contextually relevant and timely responses, creating more natural and engaging dialogues.

Moreover, LPUs excel at creating AI that can engage in meaningful conversations, predict user intentions, and respond appropriately in real time. This advancement is pivotal for AI applications where understanding and processing human language are crucial, such as customer service or virtual assistance. Adding LPUs redefines AI’s boundaries, promising substantial progress in how machines comprehend, interact with, and serve humans. As LPUs become more integrated into AI frameworks, we can anticipate even more groundbreaking progression in AI capabilities across various industries. 

Challenges and Limitations

While the excitement around LPUs is well-founded, it’s essential to recognise the practical considerations of integrating this new technology. One main challenge is ensuring LPUs can work seamlessly with existing systems in contact centres, particularly where GPUs and CPUs are still in use, potentially limiting latency improvements. However, this should not be a major concern for contact centre managers.

Suppliers of these LPUs provide Infrastructure as a Service (IaaS), meaning you pay for what you use rather than bearing the capital expense of the hardware itself—similar to what AWS did for software businesses in the 2000s. The more pressing issues are around misuse or misrepresentation. For instance, using AI to pose as a human can be problematic. While society is still catching up with these advancements, it’s crucial to check with the customer base on what is acceptable and what isn’t.

Additionally, ensuring sufficient handoffs are in place is vital—AI isn’t a silver bullet (yet). Training now focuses on maintaining and fine-tuning the systems, tweaking the models, and adjusting the prompts. So, while there are challenges, they are manageable and should not overshadow the significant benefits LPUs bring to enhancing customer interactions.

Broader Impact Beyond Contact Centres

LPUs aren’t just changing the game in contact centres; they will likely impact operations in most sectors at some point. In healthcare, for instance, real-time language processing could help with everything from scheduling appointments to understanding patient symptoms faster and more accurately. In finance, LPUs could speed up customer service interactions and reduce or even remove wait times for customers seeking advice or needing more complex problem resolution. Retail businesses can leverage LPUs to deliver personalised shopping experiences by enabling customers to find products through voice commands and receive instant information without negatively impacting the shopping experience. Of course, all of these things will take time and investment to come to fruition, but we are clearly on a path to a new kind of customer experience. But are we mere humans ready?

Future

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Looking ahead, the potential for LPUs in AI development is vast. As technology advances, we can expect LPUs to become even more capable of handling more complex language processing tasks more efficiently. They will likely play a crucial role as voice AI continues integrating with emerging technologies like 5G, improving connectivity, and the Internet of Things (IoT), which will broaden the scope of smart devices that can benefit from real-time voice interaction. As LPUs evolve, they will refine how AI understands and processes human language and expand the horizons of what AI-powered systems can achieve across different industries.

Bisley concludes: “As we look toward the future, voice technology in contact centres is not just about understanding words—it’s about understanding intentions and emotions, shaping interactions that feel as natural and nuanced as human conversation. With LPUs, we are stepping into an era where AI doesn’t just mimic human interaction; it enriches it, making every customer interaction more efficient, personal, and insightful. The potential is vast, and as these technologies evolve, they will transform contact centres and redefine the essence of customer service.”

Conclusion

Integrating LPUs into voice AI systems represents a giant leap for contact centres, offering unprecedented improvements in operational efficiency, customer satisfaction, and agent workload. As these technologies mature, their potential to refine the mechanics of voice AI and the very nature of customer interactions is huge. Looking forward, LPUs are set to redefine customer service, making voice AI interactions indistinguishable from human engagements regarding their responsiveness and reliability. The future of AI in customer experiences, powered by LPUs, is not just about maintaining pace with technological advancements but setting new benchmarks for what AI can achieve.

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