The Internet Archive discovers and captures web pages through many different web crawls.
At any given time several distinct crawls are running, some for months, and some every day or longer.
View the web archive through the Wayback Machine.
Content crawled via the Wayback Machine Live Proxy mostly by the Save Page Now feature on web.archive.org.
Liveweb proxy is a component of Internet Archive’s wayback machine project. The liveweb proxy captures the content of a web page in real time, archives it into a ARC or WARC file and returns the ARC/WARC record back to the wayback machine to process. The recorded ARC/WARC file becomes part of the wayback machine in due course of time.
TIMESTAMPS
The Wayback Machine - https://web.archive.org/web/20181109075533/https://www.tensorflow.org/lite/
TensorFlow Lite is for mobile and embedded devices.
TensorFlow Lite is the official solution for running machine learning
models on mobile and embedded devices. It enables on‑device machine
learning inference with low latency and a small binary size on Android,
iOS, and other operating systems.
Many benefits
On-device ML inference is difficult because of the many constraints—TensorFlow Lite can solve these:
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Performance
TF Lite is fast with no noticeable accuracy loss—see the metrics.
Optimized float- and fixed-point CPU kernels, op‑fusing, and more.
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Acceleration
Integration with GPU and internal/external accelerators.
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Small model size
Controlled dependencies, quantization, and op registration.
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Tooling
Conversion, compression, benchmarking, power-consumption, and more.
Companies using TensorFlow Lite
“TensorFlow Lite helped us introduce machine learning and AI into our app in an easy and streamlined way. We could reduce the size of our models while keeping the accuracy high. This helped us create an amazing fishing experience for our users by allowing them to identify any fish species with just a photo.”
How it works
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Build
Build a new model or retrain an existing one, such as using transfer learning.
We love to hear what you're working on—it may even get highlighted on our social media! Tell us.
“The release of TensorFlow Lite has allowed us to deploy an engaging
real-time experience to our users that eliminates the requirement
for a data connection. TensorFlow Lite’s ability to compress and
optimize the TensorFlow graph for mobile deployment has been
transformative in expanding the capabilities of Snap It.
Through TensorFlow Lite, our users can now enjoy a state of the
art, computer-vision-based food logging experience without worrying
about signal strength. We look forward to future collaborations
with the TensorFlow Lite team.”
