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Amazon Has A Problem: Alexa Needs To Stop Hallucinating

There was a time when Alexa being able to tell you the weather or select and play your favourite Wayne Newton track was enough, but those days are gone.

Artificial Intelligence is apparently where it’s at, and so when Amazon relaunches Alexa at some point – after a few years of intense R&D – it will need to be able to handle more than playing weatherperson or music librarian. 

It will need to answer difficult questions quickly in a pleasant and accurate way; maintain conversations; extract information from myriad sources and arrange words in a meaningful, easy to digest fashion.

All elements are crucial, but one more so than the others, and that is accuracy when answering questions. 

Without it, AI is as useful as an ashtray on a motorbike. You might as well sit a troop of monkeys in front of typewriters and encourage its members to bash away at the keys in the hope of stumbling across the facts.

According to a Financial Times report, Amazon is readying itself to relaunch Alexa as an AI “agent”, but there is trouble at mill.

It echoes a story written last June by former Alexa research scientist Eric Mihail, who said “Alexa AI was riddled with technical and bureaucratic problems” during his two-and-a-half years there, starting in 2019. He said that he and the team were there to “bring the latest and greatest in AI research into the Alexa product and ecosystem”.

During his time the team grew from two to 20, but Mihail catalogues how it was held back by excruciatingly slow decision-making processes and lack of access to data.

Success requires Amazon to rebuild Alexa’s software, which is embedded in half a billion devices around the world, from the ground up, so it has a generative AI “brain” opposed to the ability to quickly grab basic information or turn your lights on.

Alexa be trippin’. Artwork: ChannelNews.

Leader of the artificial general intelligence (AGI) team at Amazon, Rohit Prasad, told the Financial Times the voice assistant still needed work.

“This includes solving the problem of ‘hallucinations’ or fabricated answers, its response speed or ‘latency’, and reliability,” the FT said. 

“Hallucinations have to be close to zero,” Prasad told the paper. “It’s still an open problem in the industry, but we are working extremely hard on it.  

“Sometimes we underestimate how many services are integrated into Alexa, and it’s a massive number. 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.”

Amazon Alexa products.

The FT said it had been told by people who had worked on Amazon’s voice assistant teams in recent years “its effort has been beset with complications … Several former workers said the long wait for a rollout was largely due to the unexpected difficulties involved in switching and combining the simpler, predefined algorithms Alexa was built on with more powerful but unpredictable large language models”.

One former senior member of the Alexa team told the paper that even sophisticated large language models (LLMs) can spit out answers that are “completely invented some of the time”. 

“At the scale that Amazon operates, that could happen large numbers of times per day,” they said. 

Even in the post-truth era, this is not where Amazon wants to be.

But as AI models – with zero concern for copyright or accuracy – hoover up information that is good, great, dodgy, dangerous and delusional, and regurgitate it back at us in bite-sized chunks, it’s an issue that will simmer away for years to come.



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