The AI Conference https://aiconference.com/ Shaping the Future of AI Fri, 12 Sep 2025 23:09:40 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.4 https://aiconference.com/wp-content/uploads/2017/04/cropped-favicon-32x32.png The AI Conference https://aiconference.com/ 32 32 Julien Launay https://aiconference.com/speakers/julien-launay/ Fri, 12 Sep 2025 20:16:56 +0000 https://aiconference.com/?p=27843 Julien Launay is the CEO and co-founder of Adaptive ML, a startup focused on enabling AI models to learn from experience. With dual headquarters in New York City and Paris, Adaptive ML is used by Fortune 500 enterprises—such as AT&T—to develop unique AI agents able to seamlessly interface with their systems and to learn from production data.

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Julien Launay

Adaptive-ML
CEO and co-founder
Adaptive ML

Panel Title:

Dual-Use AI:
Building for Commercial and National Security Impact

Panel Summary:

Commercial AI breakthroughs increasingly define the technology available to national security operators.

 

This panel examines how startups like AdaptiveML and Enigma navigate the dual-use landscape, balancing commercial traction with mission alignment, and what that means for the future of AI adoption in defense and intelligence.

Picture of About | Julien Launay

About | Julien Launay

Julien Launay is the CEO and Co-founder of Adaptive ML, a startup enabling AI models to learn from experience. With dual headquarters in New York City and Paris, Adaptive ML powers Fortune 500 enterprises—including AT&T—by developing unique AI agents that seamlessly interface with enterprise systems and learn from production data.

Previously, Julien led extreme-scale research teams at HuggingFace and LightOn, where he pioneered advances in data scalability & quality, large-scale training pipelines, and principled model architectures. He is also the organizer of the Efficient Systems for Foundation Models workshop at ICML, a leading forum for discussions on scalable AI systems.

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Priyambada Jain https://aiconference.com/speakers/priyambada-jain/ Wed, 10 Sep 2025 22:00:04 +0000 https://aiconference.com/?p=27791 Priyambada Jain is a data science and artificial intelligence professional based in California, currently working in AI at BlackRock in Palo Alto. She has extensive experience in Generative AI, machine learning, and statistical modeling, applying these technologies to solve real-world business problems. She holds a degree from the University of Southern California (USC) and has contributed to academic research in data science education.

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Priyambada Jain

Priyambada Jain headshot
Blackrock logo
Senior Data Scientist
BlackRock

Presentation Title:

Agentic AI for Financial Data
Automating Insights from Large-Scale Tables

Presentation Summary:

1. Problem Statement:
Financial datasets are vast, complex, and difficult to process manually. Extracting key insights from large financial tables remains a bottleneck for analysts. Unlike free-form text, tabular data is hierarchical, relational, and context-dependent, requiring specialized techniques for accurate summarization and insight generation. Traditional LLMs struggle with numerical reasoning, row-column relationships, and multi-step financial calculations, making agentic AI architectures essential for structured data interpretation.

2. Agentic AI Approach:
Built an autonomous AI agent leveraging LLMs and domain-specific fine-tuning to analyze, summarize, and extract key financial insights dynamically.

3. Core Capabilities:

  • LLM Fine-Tuning: Trained on financial documents to improve context understanding and numerical reasoning.
    • Bayesian Optimization for hyperparameter tuning.
    • Contrastive Learning to improve structured data representation.
    • Quantile Regression to enhance financial trend prediction.
    • Expectation-Maximization (EM) for better handling of missing data in tabular structures.
  • Named Entity Recognition (NER) & Ontology Learning:
    • Developed a NER model to learn the ontology of financial use cases, enabling precise identification of different columns and their relationships.
    • Fine-tuned an embedding model to capture semantic relationships between financial entities, improving contextual understanding of structured data.
  • Evaluation Framework: Supports researchers in assessing different prompting techniques like Chain-of-Thought (CoT) and Chain-of-Table (CoTab) to improve reasoning on structured financial data.
  • Tabular Data Extraction: AI pipeline identifies patterns, trends, and anomalies in financial statements.
  • Synthetic Data Generation: Capable of creating synthetic financial datasets for benchmarking, evaluation, and fine-tuning the framework.
  • Explainability & Auditability: Ensures AI-generated insights are traceable and interpretable for decision-makers.

4. Impact & Business Value:

  • Efficiency Gains: Reduces manual processing time from hours to minutes.
  • Enhanced Decision-Making: Empowers financial professionals with concise, data-driven summaries.
  • Scalability: Adaptable across different financial reports, including earnings statements, balance sheets, and regulatory filings.

Conclusion:
This agentic AI architecture bridges the gap between raw financial data and actionable intelligence, offering a research-friendly framework for advancing structured reasoning in AI. By addressing the unique complexities of tabular financial data, it enables more accurate, interpretable, and scalable AI-driven financial analysis.

Picture of About | Priyambada Jain

About | Priyambada Jain

Priyambada Jain is a data science and artificial intelligence professional based in California, currently working in AI at BlackRock in Palo Alto. She has extensive experience in Generative AI, machine learning, and statistical modeling, applying these technologies to solve real-world business problems.

She holds a degree from the University of Southern California (USC) and has contributed to academic research in data science education. She co-authored papers such as Democratizing Data Science through Data Science Training and worked as a Research Assistant at USC on an NIH-funded project aimed at extending machine learning education to biomedical practitioners.

As part of this initiative, she contributed to the Educational Resource Discovery Index (ERuDIte), which focused on organizing online data science materials for broader accessibility.

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Jackie Ho https://aiconference.com/speakers/jackie-ho/ Wed, 10 Sep 2025 21:21:31 +0000 https://aiconference.com/?p=27784 Jackie Ho is a Product Lead at Predibase, where she drives the development of cutting-edge AI infrastructure that helps enterprises deploy, fine-tune, and govern machine learning models and agents at scale.

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Jackie Ho

Jackie Ho headshot
Predibase logo
AI Product Lead
Predibase

Presentation Title:

Agentic Transformation
Navigating the 4 Stages of AI Agent Maturity

Presentation Summary:

AI agents are rapidly spreading across the enterprise as teams look to transform operations and unlock new innovation. But in a large organization, the path from a single proof-of-concept to an autonomous fleet of AI agents is riddled with security, data, and integration challenges. Join this session to explore a practical 4-stage AI maturity roadmap to help you assess, plan, and accelerate your journey toward deploying agents at scale.
In this talk, you’ll learn how to:
  • Assess your maturity:
    Use our agent maturity framework to pinpoint where your organization is on the journey from Experimentation to Autonomous AI.
  • Anticipate the roadblocks:
    Understand the specific hurdles in each stage, including:
    • Tooling gaps
    • Governance challenges
    • The “last mile” problems of optimizing agent performance
  • Plan for success:
    Explore what it takes to advance to the next stage of maturity.
    Get an overview of how Predibase and Rubrik are helping teams improve agent operations.

This session is a must-attend for both enterprise builders and the startups that serve them.

Picture of About | Jackie Ho

About | Jackie Ho

Jackie Ho is AI Product Lead at Predibase, where she drives the development of cutting-edge AI infrastructure that helps enterprises deploy, fine-tune, and govern machine learning models and agents at scale.

With deep expertise spanning data science, MLOps, and product management, Jackie focuses on translating complex AI capabilities into practical, enterprise-ready solutions.

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Adam Pingel https://aiconference.com/speakers/adam-pingel/ Tue, 09 Sep 2025 23:06:54 +0000 https://aiconference.com/?p=27721 Adam Pingel is the IBM Head of Open Tools and Applications for the AI Alliance, a role he assumed in 2024 after joining IBM in 2022.

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Adam Pingel

Adam Pingel headshot
AI Alliance logo
IBM Head of Open Tools and Applications
AI Alliance.

Presentation Title:

Human/Agent Co-Creation of Shared Knowledge with Semiont

Presentation Summary:

Semiont is a new open-source framework from the AI Alliance that enables humans and intelligent agents to co-create shared knowledge — governed by you and built to last. At its core, Semiont supports the simultaneous co-creation of a wiki and a knowledge graph, allowing text and structured relationships to evolve side by side. On top of this foundation, Semiont provides powerful retrieval and contextualization, drawing on the principles of GraphRAG (Graph-based Retrieval-Augmented Generation).

By weaving together collaborative editing with graph-grounded semantics, Semiont provides a durable framework for meaning-making that goes beyond static documentation or siloed AI memory. Humans and intelligent agents can jointly annotate, connect, and refine entities and relationships, while operators retain full control over what is shared and preserved.

In this talk, I will introduce the core principles behind Semiont, demonstrate its workflows, review its roadmap, and explore the broader implications for sustainable knowledge infrastructure in the age of AI.

Picture of About | Adam Pingel

About | Adam Pingel

Adam Pingel is the IBM Head of Open Tools and Applications for the AI Alliance, a role he assumed in 2024 after joining IBM in 2022.

Adam has been fascinated by AI and chatbots since playing with Racter in the 80’s, though the “winters” were long and frequent. Nearly three decades later, in 2015, the stars aligned when he became VPE at Ravel Law. Ravel was building AI-powered tools for the legal industry and working with Harvard Law School on what is now known as the Caselaw Access Project. Following its acquisition by LexisNexis in 2017, Adam became CTO of Global Platforms in 2019.

When not at a keyboard, he enjoys spending time with his family.

Links
GitHub: https://github.com/adampingel
LinkedIn: https://www.linkedin.com/in/adampingel/

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Hicham Oudghiri https://aiconference.com/speakers/hicham-oudghiri/ Tue, 09 Sep 2025 22:55:47 +0000 https://aiconference.com/?p=27716 Hicham Oudghiri is co-founder and CEO of Enigma, a New York-based data science and artificial intelligence company. While working as an energy analyst and managing a private sustainable finance program, he experienced a gap in the ability of enterprises to access and leverage data to solve problems.

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Hicham Oudghiri

Hicham Oudghiri headshot
Enigma logo
Co-founder and CEO
Enigma

Panel Title:

Dual-Use AI:
Building for Commercial and National Security Impact

Panel Summary:

Commercial AI breakthroughs increasingly define the technology available to national security operators.

 

This panel examines how startups like AdaptiveML and Enigma navigate the dual-use landscape, balancing commercial traction with mission alignment, and what that means for the future of AI adoption in defense and intelligence.

Picture of About | Hicham Oudghiri

About | Hicham Oudghiri

Hicham Oudghiri is Co-Founder and CEO of Enigma, a New York-based data science and artificial intelligence company. While working as an energy analyst and managing a private sustainable finance program, he experienced a gap in the ability of enterprises to access and leverage data to solve problems.

Hicham co-founded Enigma in 2012 with the mission of gathering and entity-resolving data from public and private sources to map out the relationships between companies, people, and places.

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Rita Waite https://aiconference.com/speakers/rita-waite/ Tue, 09 Sep 2025 22:50:39 +0000 https://aiconference.com/?p=27686 Rita Waite is a Partner at In-Q-Tel, the strategic investor for the U.S. Intelligence and Defense Communities. Rita joined In-Q-Tel in 2022 and primarily leads investments across the AI landscape. Prior to In-Q-Tel, Rita was an investor at Juniper Networks’ venture arm and Semapa Next VC, where she focused on AI/ML, computer networking, and fintech.

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Rita Waite

Rita Waite headshot
Iqt logo
Partner
In-Q-Tel

Panel Title:

Dual-Use AI:
Building for Commercial and National Security Impact

Panel Summary:

Commercial AI breakthroughs increasingly define the technology available to national security operators.

 

This panel examines how startups like AdaptiveML and Enigma navigate the dual-use landscape, balancing commercial traction with mission alignment, and what that means for the future of AI adoption in defense and intelligence.

Picture of About | Rita Waite

About | Rita Waite

Rita Waite is a Partner at In-Q-Tel, the strategic investor for the U.S. Intelligence and Defense Communities. Rita joined In-Q-Tel in 2022 and primarily leads investments across the AI landscape.

Prior to In-Q-Tel, Rita was an investor at Juniper Networks’ venture arm and Semapa Next VC, where she focused on AI/ML, computer networking, and fintech. Additionally, she held strategy and operational roles at Juniper Networks and Millennium bcp. Rita also serves as a startup mentor through Alchemist Accelerator and NVCA.

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Bobak Tavangar https://aiconference.com/speakers/bobak-tavangar/ Tue, 09 Sep 2025 18:42:35 +0000 https://aiconference.com/?p=27614 Bobak Tavangar is a co-founder and CEO at Brilliant Labs where he works alongside a small but mighty team who are building an open source AI glasses platform.

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Bobak Tavangar

Bobak Tavangar headshot
Brilliant Labs logo
Co-founder and CEO
Brilliant Labs

Panel Title:

AI at the Edge:
Wearables, Glasses & Ambient Devices

Panel Summary:

We’re entering an era where AI isn’t in your pocket—it’s all around you. This panel brings together product leaders from Meta and Google to explore how wearables, glasses, and ambient devices are becoming the new access points for intelligence. 

From real-time translation to multimodal sensing, these experiences are fast, contextual, and hands-free. Hear how the next generation of hardware is bringing AI closer to the edge—and closer to us.

Picture of About | Bobak Tavangar

About | Bobak Tavangar

Bobak Tavangar is the Co-Founder and CEO of Brilliant Labs, where he works alongside a small but mighty team building an open source AI glasses platform.

A graduate of Cambridge University, Bobak is a life-long technologist, having previously founded several companies in computer vision and graph search before joining Apple as a Program Lead. Outside Brilliant Labs, Bobak is deeply engaged with the Baha’i Faith, its message of oneness, and its implications for global peace in today’s turbulent and interconnected world.

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Byung-Gon Chun https://aiconference.com/speakers/byung-gon-chun/ Fri, 05 Sep 2025 22:51:31 +0000 https://aiconference.com/?p=27575 Byung-Gon Chun is the Founder and CEO of FriendliAI, leading innovations that make AI deployment more efficient and scalable. With decades of experience at the intersection of AI platform and distributed systems, he blends academic rigor with practical leadership to advance AI performance and impact. He pioneered continuous batching, now the industry standard for LLM inference.

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Byung-Gon Chun

Byung-Gon Chun headshot
FriendliAI company logo
Founder and CEO
FriendliAI

Presentation Title:

Scaling Inference for Generative AI

Presentation Summary:

As adoption of generative AI accelerates and agentic AI systems add new inference demands, the greatest challenge lies in scaling workloads from prototypes to production, where costs, latency, and GPU management complexity often stall deployment. This talk explores essential strategies such as quantization, batching, caching, and hardware aware optimization that bridge the gap between research performance and production grade performance and reliability

Drawing on lessons from large scale deployments, we highlight how these strategies enable developers to achieve higher throughput, lower costs, and predictable outcomes. We conclude by showing how these principles are realized in FriendliAI, powered by a purpose built inference stack that abstracts infrastructure complexity and consistently delivers unmatched performance at scale.

Picture of About | Byung-Gon Chun

About | Byung-Gon Chun

Byung-Gon Chun is the Founder and CEO of FriendliAI, leading innovations that make AI deployment more efficient and scalable. With decades of experience at the intersection of AI platforms and distributed systems, he blends academic rigor with practical leadership to advance AI performance and impact. He pioneered continuous batching, now the industry standard for LLM inference.

Byung-Gon is currently on leave from Seoul National University, where he is a Professor of Computer Science and Engineering. His prior research experience spans Facebook, Microsoft, Yahoo!, and Intel. His work has received global recognition, including the ACM SIGOPS Hall of Fame Award, the EuroSys Test of Time Award, and research honors from Google, Microsoft, Amazon, and Facebook. He holds a Ph.D. from UC Berkeley, an M.S. from Stanford, and B.S./M.S. degrees from Seoul National University.

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Arvind Gopal https://aiconference.com/speakers/arvind-gopal/ Fri, 05 Sep 2025 22:42:43 +0000 https://aiconference.com/?p=27569 Arvind is VP of Product Management and Strategy at eGain, where he leads innovation across AI, knowledge management, and customer experience. With 20+ years of experience, he specializes in building scalable solutions that drive customer engagement and operational efficiency. Arvind holds multiple patents in customer engagement technology and frequently speaks at industry events, including masterclasses on generative AI in customer service.

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Arvind Gopal

Arvind Gopal headshot
Egain company logo
VP of Product Management and Strategy
eGain

Presentation Title:

The Missing Link in AI CX Automation:
A Trusted Knowledge Infrastructure What, Why and How

Presentation Summary:

In a 2025 KMWorld survey, a whopping 61% of respondents pointed to erroneous or inconsistent answers as the top barrier for AI adoption. Trust can make or break a brand especially in the high-stakes domain of CX. How do you automate and deliver trusted customer experiences at scale with AI?

The solution lies in building a central foundation or a hub of vetted data and knowledge content that is correct, consumable, consistent, and compliant. Attend this session to learn: What is an AI knowledge hub? How do you build a trusted AI knowledge hub?  How do you make knowledge content AI-ready? What does success look like in AI for CX?

Picture of About | Arvind Gopal

About | Arvind Gopal

Arvind is VP of Product Management and Strategy at eGain, where he leads innovation across AI, knowledge management, and customer experience. With 20+ years of experience, he specializes in building scalable solutions that drive customer engagement and operational efficiency.

Arvind holds multiple patents in customer engagement technology and frequently speaks at industry events, including masterclasses on generative AI in customer service.

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Wil Pong https://aiconference.com/speakers/wil-pong/ Thu, 04 Sep 2025 00:11:43 +0000 https://aiconference.com/?p=27520 Wil Pong is Vice President of Product at Fiddler AI, where he leads product management and design teams building the next generation of observability tools for AI systems.

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Wil Pong

Wil Pong headshot
Fiddler company logo.
Vice President of Product
Fiddler AI

Presentation Title:

Guardians of Agentic AI:
Control Planes for Orchestration and Governance

Presentation Summary:

The adoption of multi-agent AI systems is transforming governance and compliance, but it also introduces risks that conventional monitoring cannot detect. Autonomous agents communicate, delegate tasks, and chain reasoning in ways that create invisible failure modes and policy violations.

AI control planes act as a guardian layer for these systems, combining observability, guardrails, and governance into a unified framework. Beyond passive monitoring, they analyze context in real time, intercept unsafe actions, dynamically rerouting agent workflows, and enforcing policy compliance across agent interactions. This proactive approach allows enterprises to prevent violations before they escalate.

In this session, we will explore how a control plane for multi-agent AI works in practice, demonstrating scenarios where real-time guardianship enables safe and compliant multi-agent AI at scale.

Picture of About | Wil Pong

About | Wil Pong

Wil Pong is Vice President of Product at Fiddler AI, where he leads product management and design teams building the next generation of observability tools for AI systems. At the forefront of agentic observability, Wil’s team is pioneering ways to unify application and model performance, giving developers a powerful edge in building, monitoring, and improving AI-driven products.

Prior to Fiddler, Wil has held multiple senior product leadership roles, most notably at Netflix, LinkedIn, Box, and Amplitude.

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