Amazon is pushing to transform its Alexa voice assistant into a more capable AI agent, but faces challenges in overcoming 'hallucinations' and ensuring reliability. The company aims to leverage generative AI to enable Alexa to perform complex tasks and act as a personalized concierge. However, experts and former employees highlight technical and organizational difficulties, raising questions about whether Amazon can compete with rivals like Microsoft and Google in the rapidly evolving AI landscape.
Amazon is preparing to relaunch its Alexa voice assistant as an artificial intelligence (AI) 'agent' capable of completing practical tasks. This move comes as the tech giant strives to overcome the challenges hindering its AI overhaul. Amazon , valued at $2.4 trillion, has spent the past two years reimagining Alexa , its conversational system integrated into 500 million consumer devices globally. The goal is to transplant the software's 'brain' with generative AI.
Rohit Prasad, head of Amazon's artificial general intelligence (AGI) team, told the Financial Times that the voice assistant still faces several technical hurdles before its relaunch. These include addressing 'hallucinations' or fabricated answers, improving response speed or 'latency,' and ensuring reliability. 'Hallucinations have to be close to zero,' said Prasad. 'It's still an open problem in the industry, but we are working extremely hard on it.' Amazon's vision is to transform Alexa from its current role of handling simple tasks like playing music and setting alarms to an 'agentic' product acting as a personalized concierge. This could encompass a wide range of functionalities, from suggesting restaurants to adjusting bedroom lighting based on a person's sleep cycles.Alexa's redesign began following the launch of OpenAI's ChatGPT, backed by Microsoft, in late 2022. While Microsoft, Google, Meta, and others have quickly integrated generative AI into their computing platforms and enhanced their software services, critics question if Amazon can resolve its technical and organizational challenges to compete with its rivals. According to multiple staff members who have worked on Amazon's voice assistant teams in recent years, the effort has faced significant complications. They report that the long wait for a rollout stems from the unexpected difficulties in transitioning from the simpler, predefined algorithms Alexa was built upon to more powerful but unpredictable large language models (LLMs).In response, Amazon stated it is 'working hard to enable even more proactive and capable assistance' for its voice assistant. It emphasized that implementing this scale of technology into a live service and suite of global devices was unprecedented and not as simple as overlaying an LLM onto the Alexa service. Prasad, Amazon's former chief architect of Alexa, said last month's release of the company's in-house Amazon Nova models, led by his AGI team, was partly motivated by the need for optimal speed, cost, and reliability to help AI applications like Alexa 'get to that last mile, which is really hard.' For Alexa to operate as an agent, its 'brain' must be able to call hundreds of third-party software and services. 'Sometimes we underestimate how many services are integrated into Alexa, and it's a massive number,' Prasad said. 'These applications get billions of requests a week, so when you're trying to make reliable actions happen at speed... you have to be able to do it in a very cost-effective way.' The complexity arises from Alexa users expecting quick responses and extremely high accuracy. These qualities clash with the probabilistic nature of current generative AI, a statistical software that predicts words based on speech and language patterns.Some former staff also highlight struggles to preserve Alexa's original attributes, including consistency and functionality, while integrating new generative features like creativity and free-flowing dialogue. Due to the more personalized, conversational nature of LLMs, Amazon also plans to hire experts to shape the AI's personality, voice, and diction to maintain familiarity for Alexa users. One former senior member of the Alexa team acknowledged that while LLMs are sophisticated, they carry risks, such as producing 'completely invented' answers. 'At the scale that Amazon operates, that could happen large numbers of times per day,' they said, potentially damaging the company's brand and reputation. In June, Mihail Eric, a former machine learning scientist at Alexa and founding member of its 'conversational modelling team,' publicly stated that Amazon had 'dropped the ball' in becoming 'the unequivocal market leader in conversational AI' with Alexa. Eric claimed that despite having strong scientific talent and 'huge' financial resources, the company had been 'riddled with technical and bureaucratic problems,' suggesting 'data was poorly annotated' and 'documentation was either non-existent or stale.
AMAZON ALEXA AI ARTIFICIAL INTELLIGENCE GENERATIVE AI Llms CHATBOT VOICE ASSISTANT TECHNOLOGY INNOVATION COMPETITION
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