Boston AI, Machine Learning and Data Science Meetup

Register for the Zoom:
https://voxel51.com/computer-vision-events/december-2023-ai-machine-learning-data-science-meetup/

Agenda

* Building Yourself a Private Search System with Retrieval Augmentation with Haystack – Tuana Çelik at deepset
* Rise of the Intelligent Data Platform – Franco Patano at Databricks
* Scaling Similarity Search with USearch - Ash Vardanian at Unum Cloud

Building Yourself a Private Search System with Retrieval Augmentation with Haystack

In this talk we will have a look at Haystack, an open source LLM framework, and how we can use it to create custom, private search systems on our own data. We will look at how we can build retrieval augmented generative pipelines for our Notion pages, and how Haystack can help you create custom tooling for larger NLP applications.

Speaker: Tuana Çelik is a Lead Developer Advocate at deepset.ai, where she focuses on the open-source NLP community. With a background in engineering, her main focus is to help the Haystack developer community.

Rise of the Intelligent Data Platform

At Databricks, we see organizations looking to leverage the power of AI, not only to deliver intelligent solutions, but to also have intelligent user interfaces. Join us as we delve into how lakehouse architecture forms the backbone of intelligent data platforms, integrating AI to enhance user interaction and self-management. Discover how this evolution is democratizing data and AI access for all data workers in modern organizations, paving the way for the next generation of data and AI enabled solutions.

Speaker: Franco Patano is a Strategic Data and AI Advisor at Databricks, where he collaborates with customers to understand their business needs, challenges, and goals, and help them leverage the power of Databricks to deliver data products that drive value, innovation, and growth.

Scaling Similarity Search with USearch

Vector and similarity search is increasingly critical in 2023, but most libraries struggle to fully utilize modern hardware due to issues rooted in their code architecture. Many rely on object-oriented programming, which reduces memory-efficiency and data-locality. Additionally, dependence on compilers for low-level optimizations fails to properly emit key AVX-512 and SVE Assembly instructions for x86 and Arm. My talk will dissect these and other pitfalls, and demonstrate how USearch innovates in areas like architecture and SIMD utilization to overcome them.

Speaker: Ash Vardanian, Founder of Unum Cloud. With background across astrophysics, high performance computing, and systems design, Ash focuses on bridging theory and real-world AI applications.

Where
Virtual / Zoom - https://voxel51.com/computer-vision-events/jan-25-ai-machine-learning-data-science-meetup/

SANPO: A Scene Understanding, Accessibility, Navigation, Pathfinding, Obstacle Avoidance Dataset

In this talk we introduce SANPO, a large-scale egocentric video dataset focused on dense prediction in outdoor environments. It contains stereo video sessions collected across diverse outdoor environments, as well as rendered synthetic video sessions. To our knowledge, this is the first human egocentric video dataset with both large scale dense panoptic segmentation and depth annotations.

Speaker: Kimberly Wilber is a computer vision researcher at Google Research NYC. She previously studied tasks at the intersection of computer vision and crowdsourcing at Cornell Tech.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.

Where
Virtual / Zoom - https://voxel51.com/computer-vision-events/fiftyone-workshop-1-31-2024/

Want greater visibility into the quality of your computer vision datasets and models? Then join Leila Kaneda, customer-facing Machine Learning Engineer at Voxel51, for this free 90 minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.

In the first part of the workshop we’ll cover:

• FiftyOne Basics (terms, architecture, installation, and general usage)
• An overview of useful workflows to explore, understand, and curate your data
• How FiftyOne represents and semantically slices unstructured computer vision data

The second half will be a hands-on introduction to FiftyOne, where you will learn how to:

• Load datasets from the FiftyOne Dataset Zoo
• Navigate the FiftyOne App
• Programmatically inspect attributes of a dataset
• Add new sample and custom attributes to a dataset
• Generate and evaluate model predictions
• Save insightful views into the data

Prerequisites are a working knowledge of python and basic computer vision. All attendees will get access to the tutorials, videos, and code examples used in the workshop.

Where
Virtual / Zoom - https://voxel51.com/computer-vision-events/feb-2024-ai-machine-learning-data-science-meetup/

Agenda

Towards Fair Computer Vision: Discover the Hidden Biases of an Image Classifier

Recent works find that AI algorithms learn biases from data. Therefore, it is urgent and vital to identify biases in AI algorithms. However, previous bias identification methods overly rely on human experts to conjecture potential biases, which may neglect other underlying biases not realized by humans. Is there an automatic way to assist human experts in finding biases in a broad domain of image classifiers? In this talk, I will introduce solutions.

Speaker: Chenliang Xu is an Associate Professor in the Department of Computer Science at the University of Rochester. His research originates in computer vision and tackles interdisciplinary topics, including video understanding, audio-visual learning, vision and language, and methods for trustworthy AI. He has authored over 90 peer-reviewed papers in computer vision, machine learning, multimedia, and AI venues.

Food Waste Classification with AI

1/3 of all food gets wasted, with millions of tons of food being thrown away each day. Food does not mean the same thing everywhere in the world, there are thousands of different meals across the world, therefore a lot of different classes to distinguish between. In this talk we’ll see through challenges of food-waste classification and see how foundation models can be useful to this task. We will also explore how we use FiftyOne to test models during development.

Speaker: Luka Posilović is a computer scientist with a PhD from FER, Zagreb, Croatia, working as a Head of machine learning in Kitro. Him and the team are trying to reduce the global food waste problem by using AI.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.