Giant tech company Amazon is developing a more generalized and capable large language model (LLM) to power its voice-enabled assistant Alexa.
During the company’s first-quarter earnings call, Amazon CEO Andy Jassy disclosed that the company has an LLM that powers Alexa, but it is working to develop a more improved model than the current one. Jasst believes that an improved LLM will help the company in working towards its goal of building the world’s best assistant.
In his words,
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“We’ve had a large language model underneath it, but we’re building one that’s much larger and much more generalized and capable,” Jassy said. “And I think that’s going to rapidly accelerate our vision of becoming the world’s best personal assistant. I think there’s a significant business model underneath it.”
Jassy further disclosed that Amazon’s vision to build the world’s best personal assistant would however be difficult across a lot of domains which is a very broad surface area. He however acknowledged that the advent of Large language models (LLM) and Artificial Intelligence (AI) has made such models more effective.
Jassy went on to say that he believes Amazon has a good starting point with Alexa, as it has a couple of hundred million endpoints being used across entertainment, shopping, and smart homes. He also noted that there is a lot of involvement from third-party ecosystem partners.
It is however interesting to note Amazon wasn’t the only company that proposed to invest in AI during its first quarter earnings call, other tech giants such as Meta, Alphabet, and Microsoft, also disclosed their investment plans in large language models.
With all the hype surrounding ChatGPT, it’s no surprise that major tech companies are looking to incorporate LLM-based improvements to their offerings to keep up with the fast-paced AI space. The arrival of OpenAI chatbot ChatGPT last year marked the clear coming out of a different kind of LLM as the foundation of generative AI and transformer neural networks. They are increasingly heralded as a revolutionary disruption of AI.
In the last two years, LLM has been reported to quietly expand AI’s impact in healthcare, finance, gaming, robotics, etc, and functions including enterprise development of software and machine learning. These language models have been proven to be flexible and capable to answer deep domain questions, translate languages, comprehend and summarize documents, and many more.
The creation of specialized software and tools has made LLM more feasible and within reach, propelling new use cases. New advances are already driving a wave of innovation in AI and machine learning. For enterprises, LLMs offer the promise of boosting AI adoption hindered by a shortage of workers to build models.
With just a few prompts, LLMs can easily be leveraged by organizations without AI expertise which is a huge plus. Many analysts have predicted that LLM will continue to mature and grow rapidly.