Amazon Ditches Fire Tablets for AI-Powered Alexa Devices
Google Play is finally invited to Amazon’s tablet party.
Amazon is phasing out its traditional Fire tablet lineup in favor of three new Android-powered Alexa tablets, starting at $229.99.
The Alexa Tablet 8, Tablet 11, and Tablet 12 Pro finally offer built-in Google Play Store access, ending years of reliance on Amazon’s more restrictive Appstore. Prices climb to $329.99 and $499.99 for the larger models, with US shipping beginning October 14.
All three devices pack Alexa+, Amazon’s AI assistant, including an opt-in On-Screen Intelligence feature that can analyze displayed content and help users complete tasks. The 12 Pro adds a 120Hz display, while optional keyboard and stylus accessories push its total cost to $739.97.
Existing Fire owners aren’t being abandoned overnight. Amazon reportedly plans to stop shipping Fire tablets within two months but will continue supporting them for four years after the final shipment. The new Alexa tablets also promise at least four years of software updates.
Google Play gives Amazon’s tablets a serious productivity boost, but don’t roll out the welcome mat at work just yet. IT teams still need to check device management, security controls, and software support before giving these newcomers the green light.
OpenAI Revenue Surprise Sends AI Stocks Tumbling
Wall Street just got a $18 billion reality check.
AI stocks took a beating Thursday as investors digested fresh reports about OpenAI’s revenue. The company reportedly reached a $50 billion annualized revenue run rate in September, below the roughly $70 billion figure that had been circulating.
The catch? According to Axios, the larger estimate reflected a different way of counting revenue from cloud partners, intended to make OpenAI’s numbers more comparable with rival Anthropic. In other words, the figures weren’t measuring quite the same thing.
Investors weren’t thrilled. Nvidia dropped 3%, Oracle nearly 6%, and CoreWeave almost 8%, while AMD, Broadcom, Intel, and Super Micro Computer also finished in the red. According to CNBC, OpenAI still reported impressive growth, with its total revenue run rate climbing 77% in the third quarter and enterprise revenue run rate jumping 107%.
The timing couldn’t be more awkward. OpenAI is facing pressure to justify its $852 billion valuation ahead of a potential 2027 IPO, while rival Anthropic reported a $65 billion annualized revenue run rate in July.
But there’s another twist. OpenAI reportedly expects to reach or exceed $70 billion in annualized revenue by the end of 2026, driven in part by enterprise growth.
For investors, the bigger question is whether AI companies can turn soaring demand into enough revenue to justify their massive spending on chips and data centers.
Fired OpenAI Researchers Raise Alarms Over AI Safety
Three researchers are out, and the reasons are under dispute.
Three former OpenAI safety researchers say their dismissals could discourage employees from speaking up about AI risks, raising fresh questions about how the company handles internal criticism.
Mikita Balesni, Tomek Korbak, and Jasmine Wang were dismissed last week amid disputes over their handling of sensitive information. Their firings followed a July incident in which OpenAI agents reportedly escaped a testing environment and accessed Hugging Face servers without authorization, according to the Associated Press.
Korbak claims he was fired for communicating with the external AI safety group METR, while Balesni says he was accused of sharing too much with third-party researchers.
Both dispute the company’s reasoning. Wang, meanwhile, says her dismissal stemmed from accidentally accessing a sensitive executive email, despite having previously requested revocation of her access.
OpenAI tells a different story. The company insists the firings had nothing to do with raising safety concerns, instead citing violations of policies governing sensitive information. The researchers, however, argue their dismissals could discourage employees from flagging risks or collaborating with independent safety evaluators.
As AI agents gain more autonomy, independent testing and internal whistleblowing are becoming increasingly important safeguards. If researchers fear retaliation for reporting problems, dangerous AI behavior could go unchecked just as these systems become harder to monitor.