Leveraging AI For Product and Company Growth
Everyone thinks everyone else is deploying and leveraging AI, but in reality, most companies aren’t. The ones that are sometimes have AI initiatives that don’t line up with business growth. AI’s buzz may have everyone rushing to implement their own strategies to use this tech, but if your boardroom... Read more
An Introduction to Active Learning
The current utility and accessibility of machine learning is in part due to the exponential increase in the availability of data over time. While data is abundant, labels that are required for specific supervised machine learning tasks can be difficult to obtain. At ODSC West in 2018, Dr. Jennifer... Read more
Greatest Hurdles in AI Proliferation in Education
Whenever we talk about AI’s applications, we tend to doubt the reality of AI proliferation in education. The advancements and new research don’t talk much about applications in education, and Varun Arora, founding director of Open Curriculum, has some ideas about why this might be the case.  AI hasn’t... Read more
Using Mobile Devices for Deep Learning
A key avenue for deploying deep learning models is a mobile device. The advantage of running models in mobile apps instead of sending them to the cloud is the reduction in latency and the ability to ensure data privacy for users. Despite the variety of deep learning libraries and... Read more
OS for AI: How Serverless Computing Enables the Next Gen of ML
Jon Peck is a Full Spectrum Developer & Advocate for Algorithmia, an open marketplace for algorithms. At ODSC West 2018, he delivered a talk “OS for AI” which discussed how serverless computing enables the next generation of machine learning. The slides for Peck’s presentation can be found HERE.  The... Read more
Watch: State of the Art Natural Language Understanding at Scale
Natural language understanding is a key component in many data science systems that must understand or reason about text. Common use cases include question answering, paraphrasing or summarization, sentiment analysis, natural language BI, language modeling, and disambiguation. Building such systems usually requires combining three types of software libraries: NLP... Read more
Watch: Understanding Unstructured Data with Language Models
As data scientists, we’ve seen a rapid improvement in the last decades in the tools available for working with structured data (be it tabular data, graph data, sensor data etc.). Yet, the vast majority of our data (Merrill Lynch puts the figure at roughly 90%) is *unstructured*, and lives... Read more