Sources detail Amazon's struggles to build a new generative AI-powered Alexa, including privacy concerns keeping Alexa's teams from using Anthropic's Claude
“Alexa, let's chat.” — With that phrase, David Limp, at the time Amazon's head of devices and services, showed off …
FortuneSharon Goldman
Context & Ripple Effects
Amazon had already positioned Alexa for a more conversational, personalized generative-AI upgrade in a free US preview of generative Alexa features. This report shows that moving from that product ambition to a production-ready assistant is constrained by development access and data-handling rules.
Privacy is a particularly consequential constraint for Alexa because earlier coverage detailed human review of customer voice clips in its AI-training process. The Claude restriction therefore sits in a longer-running tension between improving the assistant and limiting exposure of sensitive user interactions.
First-order effects
Amazon’s Alexa teams cannot use Anthropic’s Claude for the reported development work while the privacy concerns remain unresolved, narrowing the tools available for the new assistant.
The reported build difficulties delay or complicate Amazon’s effort to turn Alexa’s generative-AI preview into a more capable product, while Anthropic loses a potential development use case within Amazon.
Second-order effects
Amazon must either establish controls that satisfy its privacy requirements or rely more heavily on alternative models and internal development, adding integration and evaluation work.
The episode raises the bar for voice-assistant deployments: model providers and device platforms need arrangements that address how conversational data is accessed during testing and improvement.
Third-order effects
If such restrictions persist, consumer AI assistants may be differentiated less by a model’s raw capability than by whether vendors can govern data use across model, device, and cloud boundaries.
The pattern points toward more segmented AI stacks for assistants, with privacy and data-access policies shaping which external models can be deployed in sensitive consumer contexts.
The trend: Generative voice assistants are evolving into ambient AI products whose rollout depends as much on privacy governance and data controls as on model quality.
@mihail_eric Thanks for sharing this. It's a warning to all tech companies that corporate dogmas and incentive structures can crush the creative energy that's required for success.
The Sept 2023 demo, the former employees emphasize, was just that—a demo. The new Alexa is still not ready for a prime time rollout: The Alexa LLM, Amazon positioned as taking on OpenAI's ChatGPT, is, they say, far from state-of-the-art. /5
Amazon has also, former employees say, repeatedly deprioritized the new Alexa in favor of building generative AI for AWS. And while Amazon has invested $4 billion in Anthropic, it has been unable to capitalize on that relationship to build a better Alexa. /7
Research scientists who worked on the LLM said Amazon does not have enough data or access to the specialized computer chips needed to run LLMs to compete with rival efforts at companies like OpenAI. /6
Brilliant post👇 A case study in why disrupting existing businesses with tech typically requires buy-in from the CEO. The Alexa org within Amazon became a victim of its own success. A decentralized empire with too much management and too little concern over where AI was headed.
fascinating post on the failure of Alexa to incorporate LLMs being an org design and corporate incentive issue, not deficient technical capabilities https://x.com/...
This is a must read, deep dive on why @amazon has failed so far in its efforts to revamp Alexa for the generative AI era. Brilliant reporting from my @FortuneMagazine colleague @sharongoldman It has important implications for Apple and its Siri efforts too.
“Privacy concerns have kept Alexa's teams from using Anthropic's Claude model, former employees say—but so too have Amazon's ego-driven internal politics.” And, I got an Alexa thinking it will be better than Google Assistant 😢
How Alexa dropped the ball on being the top conversational system on the planet — A few weeks ago OpenAI released GPT-4o ushering in a new standard for multimodal, conversational experiences with sophisticated reasoning capabilities. Several days later, my good friends at PolyAI.…
Amazon has spent between $20B & $43B on Alexa & has/had 10,000 people working on it. It is all obsolete. To the extent that it is completely exceeded by the new Siri powered mostly by a tiny 3B LLM running on a phone. What happened? This thread suggests organizational issues
NEW 🧵: I spent the last few weeks speaking to over a dozen former employees at @amazon's Alexa organization, who say say the company dropped the ball on releasing a generative AI-powered Alexa, nine months after a splashy demo. /1 https://fortune.com/...
If you've never been at BigCo, you've likely found yourself thinking something like: > why the fuck is this BigCo thing so obviously shitty? Fixing this would take me one afternoon! Their engineers/designers must be trash. The screenshot below perfectly describes why: [image]