Prompt Engineering - an Art, a Science, or your next Job Title?
It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one.
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Maxim Salnikov
Digital & App Innovation Business Lead
at
Microsoft Western Europe
The ML science behind Amazon Compliance Shared Services
Amazon Compliance Shared Services org is the leading team processing unstructured data for a range of use-cases from knowledge extraction, understanding and reasoning over multimodal data. We are showcasing how "think big" and "customer obsession" can be applied to open research problems, driving business impact for Amazon and scientific publications with impact to the research community.
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Alin Ionut Popa
Senior Research Scientist
at
Amazon
Speed Up AI Development 10x with Langflow!
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Michel de Ru
Solution Engineer
at
DataStax
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Dieter Flick
Solution Engineer
at
DataStax
Empowering Data, AI, and ML: Our Journey to a Scalable Multi-Regional Platform
The Azure Data Platform team is leading the development of a scalable, multi-regional data platform that empowers teams to build data products for a wide range of use cases, from descriptive analytics to GenAI-driven insights.
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Mathieu Beine
Lead Solution Architect - Azure Data Platform
at
AD/01
How we've built a Market Intelligence cloud-first data product
A short story on the creation of a financial data set covering key technical intricacies in the trial-and-error process from identifying a client need to the continuous fine tuning of the data intensive pipeline
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Mihai Angheluta
Executive Director, Software Development/Engineering
at
S&P Global
Combining Business and Engineering Metrics in ML-Powered Scorecards: A Modern Approach to Product Health Assessment
In the tech industry, engineers typically focus on engineering metrics like reliability, performance, test coverage, and success rates when evaluating product health.
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Marianna Budnikova
Lead Android Developer Experience Engineer
at
Cash App
The Essential Role of Data Testing and Quality
Data testing and quality assurance are no longer just checkpoints—they're strategic pillars for any data-driven operation.
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Cristian Oprescu
Quality Engineering Manager
at
Tremend – Publicis Sapient
From Theory to Practice: The Rise of Generative AI
Generative AI has rapidly transitioned from a theoretical concept to a cornerstone of practical AI applications.
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Andrzej Lassak
Senior Director of Cloud AI Services
at
Pega
Democratization of AI
AI enablement at enterprise level that creates real impact requires facilitation of learning resources, proper tools and having a clear AI governance. Experimentation and rapid prototyping are the first milestone and after that comes the scaling up phase. We’ve just started this journey. Let’s explore our insights, the wow moments and the challenges we are facing.
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Dan Cristea
Lead AI Innovation
at
BCR