TensorFlow’s lightweight solution for mobile and embedded devices. TensorFlow has always run on many platforms but as the adoption of ML models has grown exponentially over the last few years, so has the need to deploy them on mobile and embedded devices. TensorFlow Lite enables low-latency inference of on-device machine learning models.
TensorFlow Lite launched on Product Hunt on November 14th, 2017 and earned 155 upvotes and 0 comments, placing #13 on the daily leaderboard. TensorFlow’s lightweight solution for mobile and embedded devices. TensorFlow has always run on many platforms but as the adoption of ML models has grown exponentially over the last few years, so has the need to deploy them on mobile and embedded devices. TensorFlow Lite enables low-latency inference of on-device machine learning models.
TensorFlow Lite was featured in Android (57.1k followers), Developer Tools (511.4k followers), Artificial Intelligence (466.8k followers) and Search (18k followers) on Product Hunt. Together, these topics include over 196.9k products, making this a competitive space to launch in.
Who hunted TensorFlow Lite?
TensorFlow Lite was hunted by Chris Messina. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how TensorFlow Lite stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Chris Messina