feb 14 generative ai, LLM, ml
This webinar will feature presentations around Generative AI, Large Language Models (LLM), Machine Learning (ML) and Automation, covering multiple topics like the ones listed below.
Angelbeat provides a unique opportunity to understand and compare GenAI offerings from AWS, Microsoft and Google, in this technical and focused program.
Click on the green button above to register, scroll down to see the full and detailed agenda, plus expert speakers. Click on their name to view their Linkedin profile, and session title for additional information.
Large Language Model (LLM) Strategies and Gen AI Business Use Cases/Deployment Scenarios
Responsible Gen AI and Eliminating Biased Outputs
Gen AI Data Ingestion across all types: Unstructured, Structured, Text, File, Video
Protecting/Isolating Corporate Data through Technology (Firewalls) and Legal (Contracts), while still leveraging LLM’s to create/train Gen AI Models
LLM/Gen AI Application and Prompt Optimization through Retrieval-Augmented Generation (RAG), Vector Databases and other Tools
Gen AI Integration with Cloud Platforms and Data Analytics Applications
Gen AI Security Risks/Threats and Solutions, covering Deepfakes and False, Malicious AI-Generated Content
AIOps: Leverage AI to analyze large data sets, predict issues, perform root-cause analysis, plus automate operational tasks such as data backups, workload scheduling, performance monitoring.
Here is typical and highly positive Angelbeat attendee feedback, this from the IT Director at a global pharmaceutical firm: “All the events that you host are always enjoyable because they are to the point, not a sales pitch and an educational, factual experience.”
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If you have any questions email rgerber@angelbeat.com and we will get back to you right away.
We understand that you may attend for only a portion of the webinar, or have to join after the start, that is fine, please still register.
1:05 Mamoon Chowdry, Solutions Architect, AI, Machine Learning, Cloud Computing, AWS
Generative AI for Every Business: Learn how to boost productivity, build differentiated experiences, and innovate faster with AWS, leveraging its enterprise-grade security and privacy, access to industry-leading foundation and large language models (LLM), and generative AI-powered applications. Specific topics to be discussed include:
Build and scale Generative AI applications with security, privacy, and responsible AI built in from day 1
Train and run inference at scale with infrastructure purpose-built for machine learning
Use AWS’ powerful and easily customized applications/capabilities to boost productivity, streamline coding, simplify business intelligence, and seamlessly integrate multiple data sources
1:25 Martin Holste, Field CTO, Cloud and AI, Trellix
GenAI Safety and CyberSecurity: The OWASP Top 10 Vulnerabilities for LLM Apps: It seems there is a new article about AI safety in the media every day. Let’s unpack the myths and questions to truly understand the current state of AI and what it means to digital safety. In this session, we’ll discuss the OWASP Top 10 vulnerabilities for LLM apps and what they mean to organizations.
1:45 Arunansu Pattanayak, Technical Specialist, Data & AI, Microsoft
LLMOps with Azure AI: One of the biggest obstacle organizations face in adopting Generative AI technology is a strategy for operationalizing applications built on Large Language Models (LLMs). Azure AI make LLMOps easy with security, compliance and monitoring built into the development environment. My talk will describe LLMOps life cycle and how it can be done using Azure AI.
2:05 Dr. Ravishankar Rao Vallabhajosyula, Senior Director, Data Science, Impetus
Unlock Innovation and Scale with GenAI Use-Cases in Enterprises: In the recent past, numerous enterprises have explored the potential of generative AI. Concurrently, there have been notable advancements within the LLM space. Amidst this ongoing evolution, what prospects does the forthcoming year hold for innovation and scale within any enterprise? How can enterprises effectively realize the ROI from their GenAI initiatives and investments?
Despite progress, enterprises still grapple with various challenges including data management, computational resources, regulatory compliance, and other pivotal factors as they transition from experimental to operational deployments.
Join our expert session to learn how Impetus Technologies empowers its clients through strategies such as data unification, responsible AI integration, contextualization, scalability, and more. Explore how to infuse and leverage GenAI capabilities for diverse use-cases, catalyze innovation, and deliver transformative user experiences.
2:25 Casey Mondoux, Chief Technologist, Trend Micro
Code and Consequence: Navigating the AI-Enhanced Cybersecurity Landscape: Generative AI has a dual role in cybersecurity, as it is used in both sophisticated cyber-attacks and advanced defense mechanisms. Learn how to address the challenges of this evolving AI-enhanced cybersecurity landscape, with specific emphasis on the need for robust and informed security strategies, to respond to these emerging threats.
2:45 Eddie Tinsley, Sr. Customer Engineer - Data Analytics Specialist, Google
Generative AI on Google Cloud: Deliver generative AI powered experiences quickly, efficiently, and responsibly, powered by Google’s most advanced technology and models including Gemini.
3:05 AWS Closing Session
Kishore Tatavarthi, Senior Partner Solution Architect, AWS
Narenda Gupta, Senior Solutions Architect, AWS
GenAI Integration with Enterprise Data Platforms, including Data Warehouse, Data Lake, Database: Learn how Generative AI and ML can be integrated and optimize the performance of your Data Platforms, including Data Warehouses, Data Lakes and Databases. There will be real example examples, covering Data Foundation, Data Governance and Secured Data Sharing Enterprise Use Cases, which highlight recent advancements in Amazon DataZone, AWS Data Clean rooms and Amazon Redshift.