
Karamo Brown, famous for his pep talks on Netflix’s “Queer Eye,” has jumped into the wellness and AI space with his new app, Kē. After spending a year and a half focusing on his own journey—from fitness and nutrition to meditation, sobriety, relationships, and personal growth—Brown wants to help others do the same. Kē offers […]
Karamo Brown, known from Netflix's "Queer Eye," has launched a wellness app called Kē that includes personalized fitness plans, nutrition guidance, meditation content, and community support features. The app's distinctive feature is an AI digital clone of Brown powered by an AI startup, which allows users to ask questions and receive advice in his voice, drawing from his interviews, podcasts, and other material. Brown emphasizes that the AI clone is designed as a tool to support personal development rather than replace human relationships, with safeguards and human oversight in place. This reflects a broader trend of celebrities creating AI digital replicas, though the source notes concerns exist about unauthorized use of likenesses and voices, as well as risks of one-sided emotional attachments to celebrity chatbots.

Generative AI has reshaped how software gets built. What began as line-by-line autocomplete now spans full application generation, multi-agent build pipelines, and natural-language interfaces to entire codebases. Large language models trained on code can read context, follow intent, and produce working frontends, backends, and infrastructure with little manual setup. For early-level AI engineers, software engineers, and data scientists, the practical question is no longer whether these tools

The all-cash deal gives MoEngage access to technology that assigns AI agents to individual customers.

A new update for Google Home could make it less likely your smart home cameras mistake you for someone else, just because you're facing away from the camera. Starting June 23rd, Google's expanding its facial recognition feature so that people you've tagged in your Familiar Faces library can continue to be identified when their faces aren't clearly visible, using "additional non-biometric signals (body size, clothing color, etc.)." The Familiar Faces library will also begin aut
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