Mackenzie is the Global Startup Evangelist at AWS. His days are spent traveling the globe to meet startups, share their stories, and connect engineering teams together. Every day there are a large number of startups launching on AWS across every imaginable industry. It’s Mackenzie’s mission to find stories of startups that are helping to improve the world and share these stories with a wide audience.
Prior to joining AWS, Mackenzie was the Head of Technical Operations at Betterment, the world’s largest independent robo-advisor based in NYC which manages over $8B in assets. Mackenzie was a founding engineer and Head of Technical Operations at Oscar Health, an insurance startup also based in NYC, helping to grow the company to over 400+ employees.
Join fellow software executives and AWS leaders for a day of networking, workshops, and a VIP reception at the luxurious Millennium Hilton New York One UN Plaza.
This event is tailored specifically for software executives and will include a variety of session formats on the topics of generative AI and data, including presentations, customer lightning talks, interactive workshops, expert sessions, and panel discussions. You will also have the opportunity to engage in valuable Q&A with AWS leaders and as customer speakers about their journey with AWS solutions and roadmaps.
The software industry has witnessed explosive growth over the past several years as a result of several technology trends that uniquely supported software. Today, the market is being shaped by two broad trends – changing expectations as a result of macroeconomic uncertainty and the disruptive potential of generative AI – which in many ways are polar opposites, but are also jointly creating a set of imperatives for technology companies.
In this session we will explore how these trends are uniquely affecting the software industry and how other successful software companies are adapting their strategies to best take advantage and create value.
In this talk, AWS customers will share how they enhanced their experimentation capabilities with Amazon Bedrock, a fully managed generative AI service. By strengthening its experimentation offering with generative AI, AWS customers streamline experimentation processes significantly. It reduces setup complexity, accelerates iteration cycles, and empowers engineering and product teams to explore a broader range of treatment variants and make smarter decisions based on historical data.
Executives exploring generative AI face a shifting sales landscape. Internal stakeholders like AI committees and tiger teams now shape the purchasing process, requiring a different approach. In this session, sales leaders from pioneering generative AI companies Pinecone and ScaleAI reveal how they capture interest, convey ROI, and seal deals. Gain strategies and tactics to sell generative AI solutions to this educated and dynamic new buyer.
In this session you’ll learn how to accelerate generative pre-trained transformers large language model training natively on AWS. This technology is being applied across vertical industries like healthcare, finance, legal, and marketing for many use cases, including generating human-like responses to customer inquiries. Learn how to build and/or leverage LLM technology optimally for performance and cost on AWS.
Prompt engineering is an important tool for any business seeking to optimize Claude. Effective prompts improve Claude’s outputs, reduce deployment costs, and ensure customer-facing experiences are on-brand. Learn how to optimally construct prompts and build for complex business use cases with an Anthropic prompt engineer.
In this session, learn how your company can get accurate answers, solve problems, generate new content, and take actions using the data and expertise found in your company's information repositories, including your code and enterprise systems. With Amazon Q, your team can streamline tasks, speed decision-making, and help spark creativity and innovation.
As General Manager, Brendan leads the product engineering and R&D, product marketing, product management, product led growth and offering management teams related to Qlik’s analytics offerings. Prior to this role, Brendan served as VP and General Manager for Qlik Cloud. Previously, Brendan has led multiple sales and go-to-market organizations over his career, including Worldwide Digital Sales Leader for Watson Analytics at IBM, Worldwide IT Portfolio Manager at Cognos and multiple roles at PTC.
Laura Ellis is the Vice President of Data at Rapid7. Her mission is to make artificial intelligence, data science, and analytics accessible to everyone in a secure and scalable manner. She is the co-host of data mishaps night and has a long time blog where she writes about all things data: www.littlemissdata.com
Nicholas Marwell is a member of the technical staff on Anthropic's product research team, working on optimizing models for end customer use cases and tool use capabilities. He also serves as the technical lead for first party Amazon adoption of Anthropic models, and leads the company's embeddings partnerships. Prior to joining Anthropic, Nicholas most recently spent time as an Entrepreneur in Residence at Thrive Capital and the Head of Merchant products at Snackpass.
Luca Antiga is the CTO at Lightning AI. He is an early contributor to PyTorch core and co-authored “Deep Learning with PyTorch” (published by Manning). He started his journey as a researcher in Bioengineering, and later co-founded Orobix, a company focused on building and deploying AI in production settings.
Vijay Karunamurthy is the field Chief Technology Officer at Scale AI, where he works to democratize the capabilities of Generative AI and Large Language Models, partnering with large model providers, governments, and Fortune 500 companies. Prior to Scale, Vijay was a Director of Engineering at Apple and Google, where he worked on applications of AI for personalizing human interfaces.
Zhe Zang is currently Head of Open Source Engineering (Ray.io project) at Anyscale. Before Anyscale, Zhe spent 4.5 years at LinkedIn where he managed the Hadoop/Spark infra team. He has been working on open source for about 10 years; he's a committer and PMC member of the Apache Hadoop project, and a member of the Apache Software Foundation.
Frank Della Rosa is Research Vice President responsible for SaaS, Business Platforms, and Industry Cloud. Mr. Della Rosa's core research analyzes current market conditions and trends and provides strategic guidance to technology suppliers and mid-market and enterprise technology buyers. Ongoing research highlights various SaaS and cloud computing aspects, including hybrid and multi-cloud application deployments, business platforms, cloud marketplaces, buyer behavior, and global trends across vertical and functional markets. Mr. Della Rosa's research covers emerging ISVs' journey to SaaS, SaaS management platforms, market forecasts, and supplier market shares.
Carol Potts is Head of Independent Software Vendor (ISV) Sales at AWS, leading an organization of customer-obsessed sales professionals across the US in their mission to innovate for and with ISVs. A steady, strategic leader with a successful track record steering multi-billion-dollar businesses, Carol has proven expertise in Software as a Service (SaaS), Cloud Computing, Enterprise Software, Solution Selling, and Partner relationships. She is known for exponentially expanding market share and helping the world’s most ambitious companies disrupt markets, accelerate innovation and build the future.
Max leads the Generative AI ISV segment at AWS. The segment’s mission is to make AWS the best place for generative AI infrastructure companies and AI powered application businesses to build product, and win customers. He’s been at Amazon since 2014, and has worked with companies like Robinhood, Affirm, and DraftKings prior to their IPO’s, and enterprises like SAP.
Edo Liberty is the Founder and CEO of Pinecone, the managed database for large-scale vector search. Until April 2019, Edo was a Director of Research at AWS and Head of Amazon AI Labs. The Lab built cutting-edge machine learning algorithms, systems, and services for AWS customers. The team built parts of SageMaker, Kinesis, QuickSight, Amazon ElasticSearch, Glue, Rekognition, DeepRacer, Personalize, Forecast, and other yet-to-be-released services. Before AWS, Edo was a Senior Research Director at Yahoo and Head of Yahoo’s Research Lab in New York. He worked on building horizontal machine learning platforms and improving applications such as online advertising, search, security, media recommendation, email abuse prevention, and many more. Edo received his B.Sc in Physics and Computer Science from Tel Aviv University and my Ph.D. in Computer Science from Yale University. After that, he was a Postdoctoral fellow at Yale in the Program in Applied Mathematics. He is the author of more than 75 academic papers and patents about machine learning, systems, and optimization.
Kalpana Mahesh is the Head of the Data & Gen AI Solutions Architects organization at AWS and focuses on accelerating customer business outcomes through the democratization of ML. Her background includes the diverse areas of machine learning, data, software development, hardware engineering, battery management, and IoT along with global customer & business management. She holds 2 patents in the energy harvesting space, has a MS EE from Missouri Science & Technology University and a MBA from SMU. Her passions outside of work are family and community! She is actively involved in the community through the Sankara Eye Foundation and Hunger Heroes, a technology solution built on AWS for solving hunger in the communities.
