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Next in AI
What's Next for Large Language Models
Thursday, April 20, 2023
4 PM BST | 11 AM EDT | 8 AM PDT
Alberto Rizzoli
Alberto Rizzoli
Co-founder & CEO of V7
Eiso Kant
Eiso Kant
CEO & Founder, Athenian
Douwe Kiela
Douwe Kiela
AI Researcher & Professor, Stanford University
Back
Next in AI

What's Next for Large Language Models

What's Next for Large Language Models
ABOUT

About the Event

Join us for a compelling fireside chat that will delve into the horizon for Large Language Model capabilities and tooling.

Our esteemed panel, comprising LLM tooling developers and venture capitalists, will provide invaluable insights on navigating this rapidly evolving space. Learn from their experiences and stay ahead of the curve in AI innovation.

The arrival of GPT-4 has ushered in a new era of exploration for the capabilities of Large Language Models. With a flurry of AI startups popping up, it's crucial to identify those that will deliver sustained value in the long term.

As a CTO, you face the decision of when and how to integrate AI, what aspects to prioritize, and whether to accelerate development now or wait for LLMs to mature further.

Register now
Watch the replay
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SPEAKERS

Hosted by

Alberto Rizzoli
Alberto Rizzoli
Co-founder & CEO of V7
Eiso Kant
Eiso Kant
CEO & Founder, Athenian
Douwe Kiela
Douwe Kiela
AI Researcher & Professor, Stanford University
AGENDA

What to expect

01/

A primer on the current state of LLM, what they can, and cannot do.

02/

Live panel discussion covering emerging applications, how to get started with LLMs, changes in tooling, and navigating risk.

03/

Real life examples of companies leveraging LLM to build new forms of software, enhance customer experience, and drive business growth.

04/

A live Q&A session

05/
Speakers

Hosted by

Alberto Rizzoli
Co-founder & CEO of V7

Previously CEO at Aipoly - First smartphone engine for convolutional neural networks. Management & Stats grad at Cass Business School and Singularity University. Never had a real job.

Eiso Kant
CEO & Founder, Athenian

Founder of Athenian, where we're building the ironman suit for engineering leaders. Eiso previously founded Source{d}, the first company applying AI to source code.

Douwe Kiela
AI Researcher & Professor, Stanford University

Adjunct Professor at Stanford University, previously of Hugging Face and Meta AI where Douwe co-authored the retrieval-augmented generation paper.

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Detect and locate the presence of multiple objects within an image, drawing bounding boxes around them to indicate their position and size. Export your labeled data in the desired format or train object detection models on V7 to label more data.

Instance Segmentation

Leverage V7 annotation tools to detect and delineate individual object instances within an image, and assign a unique label to each pixel that belongs to that instance. Easily create classes with attributes, text, directional vectors, and instance IDs. Train instance segmentation models on V7 in a click.

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Use V7 to combine both semantic and instance segmentation to assign a unique label to every pixel in an image, including objects and surrounding context to solve panoptic segmentation tasks. Add and manage classes along with attributes, text, directional vectors, and instance IDs to enrich your annotations. 

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Semantic Segmentation

Divide an image into distinct regions or segments, and assign labels representing the category of objects or features they belong to, to each individual pixel. Label data manually or use V7 auto annotation to achieve pixel perfect accuracy.

OCR

Leverage V7’s OCR (Optical Character Recognition) capabilities to convert scanned images or handwritten text into machine-readable text. Detect text regions within an image and get the AI to the char recognize the characters within those regions. V7 works with any language, any alphabet, any format.

Object Tracking

Follow or track the movement of one or more objects within a video sequence by detecting and matching features across frames. Use V7 to create labels manually or using auto annotation, and interpolate between frames to speed up the labeling process. Leverage Instance ID and attributes to enrich your annotations.

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Polyline Annotation

Use V7’s polyline tool to manually draw lines or curves on an image to highlight or mark specific features or regions of interest. Solve any detection, segmentation, and tracking task.

Action Recognition

Identify and classify human actions or movements within a video using action recognition. Leverage V7 keypoint skeleton to annotate your data and add attributes, text, directional vectors, or instance IDs to enrich your annotations.

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Label whole slide images (WSI) faster with V7 auto annotate tool. Create classes with attributes,  text, and instance IDs to enrich your annotations. Leverage consensus and logic stages to build automated medical workflows. V7 is FDA and HIPAA compliant.

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