GenML 2024

Where AI Theory Meets Real-World Impact

10

December 2024

09:00-15:00

Tel-Aviv

ZOA House TLV

Daniel Frisch St 1

About The Conference

GenML, returning for its second year, focuses on generative AI integration with ML models. This conference brings together researchers, data scientists, data engineers, ML experts, professionals from leading companies, and more to discuss recent developments in the field. The event will focus on research aspects related to generative AI and ML integration.

Join us at GenML to connect with industry leaders, exchange ideas with fellow practitioners, and contribute to ongoing generative AI research. This is an opportunity to learn about cutting-edge developments, share your insights, and engage with experts in this field.

Register now to secure your place at this must-attend event!

Who is it for?

This conference is ideal for AI researchers, data scientists, engineers, academics, students, and enthusiasts interested in exploring generative AI's technical and theoretical aspects. Whether you are an experienced professional or a curious newcomer, join us to gain valuable insights, exchange ideas, and expand your network in this rapidly evolving field.

The Event Details

  • 10.12.2024

  • 09:00-17:00

  • ZOA House | Daniel Frisch St 1,TLV

Previous Event Highlights

Speakers

Ronen Dar

Co-Founder and CTO

Run:ai

Lior Cohen

Senior Data Scientist

Nvidia

Boris Dahav

Data, Analytics & AI Domain Specialist

IMOD Division, Oracle

Gili Nachum

Principal Gen AI & ML Solutions Architect

AWS

Yam Peleg

Founder & CEO

Deep Trading

Oded Zinman

Applied Researcher

eBay

Ran Bar-Zik

Senior Software Architect

CyberArk

Asi Messica

VP Data Science

Lightricks

Ido Farhi

Senior Data Scientist

Intuit

Guy Tamir

Technology Evangelist, Director: oneAP

Intel

Sveta Morag

Cloud Solutions Architect

Google Cloud

Doron Bartov

Staff Data Scientist

HoneyBook

Lior King

Sr. Cloud Solutions architect - Data & AI

Microsoft

Amit Mandelbaum

Tech Lead

AI21 Labs

Agenda

8:30-9:30

Gathering & mingling

× ×

09:30-09:40

Opening remarks

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Uri Eliabayev

Founder at MDLI

9:40-10:10

Easily build Gen AI application with RAG, Agents and Evaluation, using Amazon Bedrock

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Gili Nachum

Principal Gen AI & ML Solutions Architect at AWS

10:00-13:00

Generative-AI on the go, The AI revolution on your AI-PC. Workshop for IDF reserve members or their partners.

× ×

Generative-AI on the go,  The AI revolution on your AI-PC.

Join us for a hands-on workshop where you can visualize the latest AI algorithms and experience code building.

Spend 3 hours learning and tinkering with the state-of-the-art AI technologies on AI-PCs.

 

What will we learn

  • What is an AI PC?

                Understand the main differences between a CPU, GPU and NPU

                Learn which models perform best on each type of device.

                Discover how to program and maximize the potential of an AI-PC.

  • Text Generation

                Explore how Large Language Models (LLMs) generate text.

Create a chatbot and delve into Retrieval Augmented Generation (RAG).

  • Image Generation

                Learn how text-to-image technology works.

Generate stunning images or videos using stable diffusion and other methods.

  • Music Generation

                Can LLMs generate music?

Advanced music editing and music generation on your laptop.

Who should attend

  • Enthusiasts eager to learn about AI and its applications.
  • Programmers looking to expand their skill set and gain deeper understanding of AI algorithms.
  • Professionals interested in integrating AI into their work.

Requirements

  • Basic python programming skill
  • We’ll provide everything else!

The workshop is offered now only for IDF reserve members or their partners.

Applications require a reserve approval certificate!

Guy Tamir

Technology Evangelist, Director: oneAP at Intel

10:10-10:40

GenAI in the Wild: Protecting Your Herd from Predators

× ×

GenAI is a powerful technology that is being rapidly adopted for a plethora of use cases. However, its power also makes it a prime target for attackers looking to exploit vulnerabilities. In this talk, we will discuss the need for GenAI security and the challenges involved in defending against GenAI attacks. We will highlight the complexity of the threat landscape and the difficulties in threat detection in the context of constantly evolving use cases. Join us as we explore this unexplored and misunderstood domain and discuss our efforts to invent the wheel at Intuit with GenOS and GenSRF.

Ido Farhi

Senior Data Scientist at Intuit

10:40-11:10

Making AI development easy with Prompt Flow

× ×

Prompt Flow is an open-source development tool designed to streamline the entire development cycle of AI applications powered by LLMs. Prompt Flow simplifies the process of prototyping, experimenting, iterating, and deploying your AI applications, and has its own VSCode extension.
In this session I'll introduce Prompt Flow and demonstrate how you can use it for building a chat flow, evaluate it and use it as an LLMOps tool.

Lior King

Sr. Cloud Solutions architect - Data & AI at Microsoft

11:10-11:30

Weights & Biases

× ×

11:30-11:50

Exploring Function Calling with Gemini

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Traditional LLMs have limitations. They can't access up-to-date information or interact with the real world meaningfully. Function calling solves these problems. This session explores how function calling expands the capabilities of LLMs.

Sveta Morag

Cloud Solutions Architect at Google Cloud

11:50-12:20

Break

× ×

12:20-12:40

Profiling Buyer Interests Using LLM-Generated Graphs

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How can we understand the core interests and passions of our buyers? How can we use this knowledge to introduce them to products they have yet to discover?

While typical recommendations often focus on items similar to those already viewed, our goal is to identify the deeper passions that drive buyers' shopping habits. This allows us to suggest related products from entirely different categories.

We use graphs generated by Large Language Models (LLMs) to represent buyers' interests. These graphs help us distinguish between different user interests and traverse the graph to identify various levels of interest granularity.

Oded Zinman

Applied Researcher at eBay

12:40-13:00

How to build GenAI agents that actually work

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Talking about GenAI agents is easy, but building ones that actually work is very hard.

In this talk I will shorty introduce what GenAI agents are and will talk about the three biggest challenges in implementing them:

Accuracy and user trust, latency and cost.

I will share a general framework for building GenAI agents using different techniques including different building blocks, planning and methods of evaluation.

I will also discuss how we, at AI21 labs are using these methods to deliver agent based products that actually work

Amit Mandelbaum

Tech Lead at AI21 Labs

13:00-13:20

Agentic AI in Production

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What are AI agents?

How do they differ from non-agentic AI products?

What real-world problems do they solve?

What are the essential components for developing agentic pipelines?

How can we scale AI agents, and what is the technology stack in this field?

In this session, we will explore these questions and more. We will examine the architecture, capabilities, and practical applications – Aiming to gain a comprehensive understanding as we create production-ready agentic workflows within our organizations.

Lior Cohen

Senior Data Scientist at Nvidia

13:20-13:40

Near-Realtime RAG on Production Data: Bringing AI to the Data

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Retrieval-augmented generation (RAG) implementations are becoming increasingly popular, and there is a growing demand for these systems to operate at near-realtime speeds and at scale.

In this session, we present our approach to meet these challenges by bringing the algorithms closer to the data. This involves integrating vector search capabilities with popular databases, enabling RAG implementations on production data.

Specifically, we discuss the necessity of vector data types and the development of advanced index solutions, such as graph-based or inverted-file vector indices, to handle large-scale data efficiently.

By incorporating these features into existing database systems, we aim to unlock the potential for generative AI applications on a grand scale. This session will explore the current state of vector search capabilities, RAG implementations, and other generative AI-related features in a leading database system, highlighting the opportunities and challenges of deploying near-realtime RAG on production data.

Boris Dahav

Data, Analytics & AI Domain Specialist at IMOD Division, Oracle

13:40-14:00

Building the Future: AI Infrastructure in the GenAI Era

× ×

Ronen Dar

Co-Founder and CTO at Run:ai

14:00-15:00

Break

× ×

15:00-15:20

Is My LLM Doing a Good Job? Evaluating LLMs at Scale: Lessons Learned from Lightricks

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As large language models (LLMs) become increasingly integrated into industry workflows, a pressing question arises: how do we know if our LLMs are truly delivering value across different user interactions?

This talk, drawing on lessons learned at Lightricks, explores real-world challenges in evaluating LLMs at scale, particularly for creativity-related use cases where there is no single correct answer. We’ll dive into the challenges we faced and share the evaluation framework we developed to align with specific business objectives and user experiences. Attendees will gain practical insights into measuring LLM effectiveness in dynamic, real-world environments, ensuring models are efficient and impactful for their intended use cases.

 

Asi Messica

VP Data Science at Lightricks

15:20-15:40

AI-Driven Meeting Prep summaries: Helping Client preparation

× ×

In this talk, I’ll present how we developed an AI-powered tool at HoneyBook that automatically generates tailored meeting summaries for members. The tool analyzes key data points, including previous meeting notes, client context, shared files, and business insights, to provide members with actionable snapshots before each meeting. This enables them to be better prepared, engage more effectively with clients, and make data-driven decisions. Attendees will learn how AI can enhance productivity through personalized, context-rich insights, and I will explore the technical implementation, challenges faced and results

Doron Bartov

Staff Data Scientist at HoneyBook

15:40-16:00

Taking AI to the smallest scale

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AI and LLM are in the world on a vast scale. But you can take ML model and LLM to a tiny scale – to the IoT world! You can run models even on tiny microprocessors that cost $4. In this session, you will learn how to work with LLM and ML models on small IoT devices to create exciting and smart devices with low cost and effort

Ran Bar-Zik

Senior Software Architect at CyberArk

16:00-16:20

Training State-of-the-Art Language Models, Lessons from reaching OpenLLM's Leaderboard 1st spot

× ×

Yam Peleg

Founder & CEO at Deep Trading

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Early Birds

Only 100 tickets are available. For purchasing more than one ticket, please contact [email protected]

355 ILS

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Generative AI on the go - Workshop

The workshop is offered only for IDF reserve members or their partners at a special price. Applications require a reserve approval certificate. Limited to 30 tickets.

279 ILS

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