Research and Side Projects
To encourage learning and motivate the exceptional individuals at LakeTide, we conduct industrial research in side projects both within the company and with exciting startups.
In order to leave the world a better place for our children, we are invested and working hard on AI powered hydroponic farming. We need to reach a degree of scalability and low cost that will allow people to do what’s right for the environment without operating at a loss. An important part in achieving this is AI-powered automation, and LakeTide’s expertise in real-time video analysis is playing a critical role.
Improving the safety, accessibility, and efficiency of our cities is in everyone’s interest. At LakeTide we have several interesting ongoing projects with municipalities and federal administrations to reduce operational expenses and gain better insight into hour our societies use common city resources. Graph processing and traffic simulation are used to make better decisions on how to expand future infrastructure. Smart cameras use AI to process what they see in-place, without saving or sending sensitive data over the internet. At LakeTide, we believe that in making a better society means first looking inward and asking yourself what you can do to help.
With a 3D printer, Nvidia Jetsons, actuators, sensors, breakout boards, and more, LakeTide experiments freely at the intersection of AI and robotics. Can deep learning be used to make servo movement more quiet? Yes! Can parallax head-movement be used to gauge distance using a regular 2D camera? Yes! Not only are robots fun to build, but there is a lot to be learned that transfers to all of LakeTide’s other engagements.
University Graduate Thesis Projects
Every year we enroll a handful of talented graduate students to work on challenging tasks in machine learning, distributed systems, and related fields. The experience for everyone involved has been nothing short of phenomenal.
By phrasing industry challenges as scientific research questions, LakeTide is able to apply top university talent to some of the toughest and most interesting applications of data science. Examples of past projects include:
- Tensor Rank Decomposition for Increased DNN Inference Speed
- Parallelization of Raster to Vector Algorithms
- Approximating Radio Signal Filters Using Deep Learning
- Learning to Traverse Complex Graphs using DNNs
- Effective Techniques for the Binarization of Neural Networks
If you think your profile is a good fit for LakeTide then we’d love to hear from you. Feel free to make an introduction at firstname.lastname@example.org.