Tryolabs Blog
tryolabs.com · Company blog · on HN since 2012
Tryolabs, a machine learning consultancy, writes about deep learning, computer vision, NLP, Python libraries, and ML conferences.
What HN saysHN links it for computer vision and vision-language model explainers, and for its collaboration with Google on the Temporian library.
33HN people shared it
4linked it in comments
121stories submitted
2.3Kstory points
8 months agolast shared
2012people per year2026
Most-shared posts
- 1List of Machine Learning/Deep Learning Conferences in 20196 people · 55 points · first shared 2017 · 3 comments on HN
- 2Deep Learning for NLP, advancements and trends in 20174 people · 22 points · first shared 2017 · discussion on HN
- 3Machine Learning on the Edge Devices: Benchmark Report4 people · 17 points · first shared 2019 · 1 comments on HN
- 4The Definitive Guide to Video Analytics in 20194 people · 12 points · first shared 2019 · discussion on HN
- 5Swift: Google’s Bet on Differentiable Programming3 people · 700 points · first shared 2020 · 539 comments on HN
- 6Top Python libraries of 20163 people · 336 points · first shared 2016 · 40 comments on HN
- 7Introduction to Recommender Systems in 20183 people · 16 points · first shared 2018 · discussion on HN
- 8Top Python libraries of 2019 you should know about3 people · 10 points · first shared 2019 · discussion on HN
- 9Guide to Visual QA: Datasets, Approaches and Evaluation3 people · 10 points · first shared 2018 · discussion on HN
- 10How Machine Learning Is Reshaping Price Optimization3 people · 10 points · first shared 2018 · discussion on HN
- 1111 Questions to Ask Before Starting a Machine Learning Project3 people · 9 points · first shared 2019 · discussion on HN
- 12A complete guide to computer vision3 people · 9 points · first shared 2019 · discussion on HN
- 13Major advancements in Deep Learning in 20162 people · 351 points · first shared 2016 · 75 comments on HN
- 14Top Python libraries of 2020 you should know about2 people · 281 points · first shared 2020 · 50 comments on HN
- 15Object detection: an overview in the age of Deep Learning2 people · 185 points · first shared 2017 · 20 comments on HN
What HN people wrote when they linked it
0xbadcafebee · 2026-03-04
You would use a VLM (vision language model). The model analyzes the image and outputs text, along with general context, that can drive intelligent decisions. https://tryolabs.com/blog/llms-leveraging-computer-vision
m_kos · 2024-02-13
Looks like it is a collaboration with Tryolabs: https://tryolabs.com/blog/tryolabs-google-introducing-temporian
JSeymourATL · 2017-07-31
Given your objectives -- assuming no restrictions during your earn-out period. Go find another early-stage company or two that you can help. Industry conferences should prove a target rich environment to find them > https://tryolabs.com/blog/machine-learning-deep-learning-conferences/
thegeomaster · 2016-12-14
What enabled the ML revolution we're witnessing now is mostly the advent of powerful and low-cost GPGPUs and the abundance of training data, as you mentioned. Of course, there are theoretical breakthroughs and interesting new applications [1], but it wasn't the deciding factor. Even ConvNets aren't new. For example, AlexNet is basically a much larger reimplementation of the original Lenet idea [2] from 1998.
This is not to discredit any new work that's being done. I think it's awesome to see so much progress in a field that's certainly on its way of defining an era. I'm just pointing out that we have known about most of the fundamentals for a long time.
[1]: https://tryolabs.com/blog/2016/12/06/major-advancements-deep-learning-…
[2]: http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf