
Meta is developing plans for a cloud infrastructure business, selling access to AI compute power and models. The move would pit it against the big cloud providers like Amazon Web Services, Google Cloud, and Microsoft Azure.
Meta is developing a cloud infrastructure business to sell access to its AI computing power and models, following a similar move by SpaceX weeks earlier. The company has invested billions in data centers for AI but hasn't generated significant revenue from its own AI models and services, making this a way to recoup some of its massive infrastructure spending. Some analysts suggest that the real winners in AI may be companies that own data centers rather than those providing the best models, though skeptics warn that the rush to build AI infrastructure could create a bubble dependent on depreciating chips.

In this tutorial, we build a complete PDF-to-structured-data extraction workflow around Lift, with a focus on controlled evaluation rather than a simple demo run. We begin by preparing a Colab-compatible GPU environment, selecting the appropriate precision mode for the available hardware, and patching model loading to ensure the Lift backend runs reliably even on constrained 16 GB GPUs via 4-bit NF4 quantization. From there, we generate synthetic multi-page research reports with deliberately pl

SpaceX reportedly showed investors a "handset-like" AI device before going public. It could be another signal SpaceX wants to expand into wireless.
For voice AI systems, response time is a critical problem that affects how natural conversations feel. Two companies partnered to demonstrate a speech-to-speech system using open-source components where fast inference on one company's hardware allows conversations to flow with responsiveness similar to human interaction, avoiding the multi-second delays that currently frustrate users. The system works as a modular pipeline that takes speech input, processes it through speech recognition and a language model, generates text-to-speech output, and delivers a spoken response, with each component being replaceable by developers. This approach is already being used to power robots currently deployed in the field, where responsiveness is essential to making interactions feel natural.
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