Collaborating Authors

Adam Bry and Hayk Martiros's talk – Skydio Autonomy: Research in Robust Visual Navigation and Real-Time 3D Reconstruction (with video)


In the last online technical talk, Adam Bry and Hayk Martiros from Skydio explained how their company tackles real-world issues when it comes to drone flying. Skydio is the leading US drone company and the world leader in autonomous flight. Our drones are used for everything from capturing amazing video, to inspecting bridges, to tracking progress on construction sites. At the core of our products is a vision-based autonomy system with seven years of development at Skydio, drawing on decades of academic research. This system pushes the state of the art in deep learning, geometric computer vision, motion planning, and control with a particular focus on real-world robustness.

Monitoring the climate crisis with AI, satellites and drones – a workshop at NeurIPS2020


As part of the workshop programme at NeurIPS2020, Climate Change AI (CCAI) held an all-day session on "Tackling climate change with machine learning". You can watch the talks from this side event in full in a recording provided by CCAI. In this workshop, the speakers, from both industry and academia, discuss how artificial intelligence and remote sensing can be used to monitor global carbon impact. They also consider trust and accountability issues relating to governments, companies, and international projects. You can find out more about this event, and the main workshop, here.

Best Master's Programs in Machine Learning (ML) for 2021


Considering various factors such as the research areas, research focus, courses offered, duration of the program, location of the university, honors, awards, and job prospects, we came up with the best universities to help you in your choosing process. This article is most suited for individuals who'd like to pursue a master's degree with a focus on machine learning and need some guidance on their decision making. Feel free to jump to the end if you are only looking for the university names. Note: The universities mentioned below are in no particular order.

Best Public Datasets for Machine Learning and Data Science


This resource is continuously updated. If you know any other suitable and open datasets, please let us know by emailing us at or by dropping a comment below. Google Dataset Search: Similar to how Google Scholar works, Dataset Search lets you find datasets wherever they are hosted, whether it's a publisher's site, a digital library, or an author's web page. It's a phenomenal dataset finder, and it contains over 25 million datasets. Kaggle: Kaggle provides a vast container of datasets, sufficient for the enthusiast to the expert.

Driving Efficiency with MLOps


The advancements in machine learning has more and more enterprises turning towards the insights provided by it. Data scientists are busy creating and fine-tuning machine learning models for tasks ranging from recommending music to detecting fraud. Here's what a machine learning model lifecycle looks like: According to Wikipedia, "MLOps ('Machine Learning' 'Operations') is a practice for collaboration and communication between data scientists and operations professionals to help manage the production ML lifecycle. MLOps looks to increase automation and improve the quality of production ML while also focusing on business and regulatory requirements. MLOps applies to the entire lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics." So, is MLOps just another fancy name for DevOps?

Python Code Assistant Powered by GPT-3


GPT-3 from OpenAI has captured public attention unlike any other AI model in the 21st century. The sheer flexibility of the model in performing a series of generalized tasks with near-human efficiency and accuracy is what makes it so exciting. It has created a paradigm shift in the world of Natural Language Processing(NLP), where till now the models were trained based on the ungenralized approach to excel at one or two tasks. GPT-3 is trained by OpenAI with a generalized approach on a massive scale involving 175 billion parameters which allows it to mimic functionalities of the human brain (like GPT-3 is capable of generating text that is surprisingly human-like after only being fed a few examples of the task you want it to do). Like a human brain GPT-3 is able to learn and do things with few shots of training unlike the conventional way of training an NLP model over a large corpus, which is both difficult and time-consuming.

The AI Monthly Top 3 -- February 2021


Odei Garcia-Garin et al. from the University of Barcelona have developed a deep learning-based algorithm able to detect and quantify floating garbage from aerial images. They also made a web-oriented application allowing users to identify these garbages, called floating marine macro-litter, or FMML, within images of the sea surface.

Practical Guide: Build and Deploy a Machine Learning Web App


This is a guide for a simple pipeline of a machine learning project. For this course, our target is to create a web app that will take as input a CSV file of flower attributes (sepal length/width and petal length/width) and returns a CSV file with the predictions (Setosa Versicolour Virginica). I know that you want to skip this step but don't. This will organize your packages and you will know exactly the packages you need to run your code incase we want to share it with someone else. Trust me, this is crucial.

The Future of AI Innovation


After rapid growth over the past few years, artificial intelligence has become one of the biggest focuses of enterprises. Well, what has made it so hot? With AI, we can design systems that learn and adapt to all the new data we collect. Just a few years ago, AI seemed to be impossible. But now, it's quickly becoming necessary and expected.

AI Reveals Current Drugs May Help Combat Alzheimer's Disease


Researchers have developed a method based on Artificial Intelligence (AI) that rapidly identifies currently available medications that may treat Alzheimer's disease. The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. Importantly, it could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action. "Repurposing FDA-approved drugs for Alzheimer's disease is an attractive idea that can help accelerate the arrival of effective treatment -- but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer's disease," said researcher Artem Sokolov from Harvard Medical School. "We, therefore, built a framework for prioritising drugs, helping clinical studies to focus on the most promising ones," Sokolov added.