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The Rise of Agentic AI: Transforming Business Operations
Summary In this episode of the AI Engineering Podcast, host Tobias Macey sits down with Ben Wilde, Head of Innovation at Georgian, to explore the transformative impact of agentic AI on business operations and the SaaS industry. From his ear
Protecting AI Systems: Understanding Vulnerabilities and Attack Surfaces
Summary In this episode of the AI Engineering Podcast Kasimir Schulz, Director of Security Research at HiddenLayer, talks about the complexities and security challenges in AI and machine learning models. Kasimir explains the concept of shad
Understanding The Operational And Organizational Challenges Of Agentic AI
Summary In this episode of the AI Engineering podcast Julian LaNeve, CTO of Astronomer, talks about transitioning from simple LLM applications to more complex agentic AI systems. Julian shares insights into the challenges and considerations
The Power of Community in AI Development with Oumi
Summary In this episode of the AI Engineering Podcast Emmanouil (Manos) Koukoumidis, CEO of Oumi, about his vision for an open platform for building, evaluating, and deploying AI foundation models. Manos shares his journey from working on n
Arch Gateway: Add AI To Your Apps Without Custom Development
Summary In this episode of the AI Engineering Podcast Adil Hafiz talks about the Arch project, a gateway designed to simplify the integration of AI agents into business systems. He discusses how the gateway uses Rust and Envoy to provide a
The Role Of Synthetic Data In Building Better AI Applications
Summary In this episode of the AI Engineering Podcast Ali Golshan, co-founder and CEO of Gretel.ai, talks about the transformative role of synthetic data in AI systems. Ali explains how synthetic data can be purpose-built for AI use cases,
Optimize Your AI Applications Automatically With The TensorZero LLM Gateway
Summary In this episode of the AI Engineering podcast Viraj Mehta, CTO and co-founder of TensorZero, talks about the use of LLM gateways for managing interactions between client-side applications and various AI models. He highlights the ben
Harnessing The Engine Of AI
Summary In this episode of the AI Engineering Podcast Ron Green, co-founder and CTO of KungFu AI, talks about the evolving landscape of AI systems and the challenges of harnessing generative AI engines. Ron shares his insights on the limita
The Complex World of Generative AI Governance
Summary In this episode of the AI Engineering Podcast Jim Olsen, CTO of ModelOp, talks about the governance of generative AI models and applications. Jim shares his extensive experience in software engineering and machine learning, highligh
Building Semantic Memory for AI With Cognee
Summary In this episode of the AI Engineering Podcast, Vasilije Markovich talks about enhancing Large Language Models (LLMs) with memory to improve their accuracy. He discusses the concept of memory in LLMs, which involves managing context
The Impact of Generative AI on Software Development
Summary In this episode of the AI Engineering Podcast, Tanner Burson, VP of Engineering at Prismatic, talks about the evolving impact of generative AI on software developers. Tanner shares his insights from engineering leadership and data e
ML Infrastructure Without The Ops: Simplifying The ML Developer Experience With Runhouse
Summary Machine learning workflows have long been complex and difficult to operationalize. They are often characterized by a period of research, resulting in an artifact that gets passed to another engineer or team to prepare for running in
Building AI Systems on Postgres: An Inside Look at pgai Vectorizer
Summary With the growth of vector data as a core element of any AI application comes the need to keep those vectors up to date. When you go beyond prototypes and into production you will need a way to continue experimenting with new embeddi
Running Generative AI Models In Production
Summary In this episode Philip Kiely from BaseTen talks about the intricacies of running open models in production. Philip shares his journey into AI and ML engineering, highlighting the importance of understanding product-level requirement
Enhancing AI Retrieval with Knowledge Graphs: A Deep Dive into GraphRAG
Summary In this episode of the AI Engineering podcast, Philip Rathle, CTO of Neo4J, talks about the intersection of knowledge graphs and AI retrieval systems, specifically Retrieval Augmented Generation (RAG). He delves into GraphRAG, a nov
Harnessing Generative AI for Effective Digital Advertising Campaigns
Summary In this episode of the AI Engineering podcast Praveen Gujar, Director of Product at LinkedIn, talks about the applications of generative AI in digital advertising. He highlights the key areas of digital advertising, including audien
Building Scalable ML Systems on Kubernetes
Summary In this episode of the AI Engineering podcast, host Tobias Macy interviews Tammer Saleh, founder of SuperOrbital, about the potentials and pitfalls of using Kubernetes for machine learning workloads. The conversation delves into the
Expert Insights On Retrieval Augmented Generation And How To Build It
Summary In this episode we're joined by Matt Zeiler, founder and CEO of Clarifai, as he dives into the technical aspects of retrieval augmented generation (RAG). From his journey into AI at the University of Toronto to founding one of the f
Barking Up The Wrong GPTree: Building Better AI With A Cognitive Approach
Summary Artificial intelligence has dominated the headlines for several months due to the successes of large language models. This has prompted numerous debates about the possibility of, and timeline for, artificial general intelligence (AG
Build Your Second Brain One Piece At A Time
Summary Generative AI promises to accelerate the productivity of human collaborators. Currently the primary way of working with these tools is through a conversational prompt, which is often cumbersome and unwieldy. In order to simplify the
Strategies For Building A Product Using LLMs At DataChat
Summary Large Language Models (LLMs) have rapidly captured the attention of the world with their impressive capabilities. Unfortunately, they are often unpredictable and unreliable. This makes building a product based on their capabilities
Improve The Success Rate Of Your Machine Learning Projects With bizML
Summary Machine learning is a powerful set of technologies, holding the potential to dramatically transform businesses across industries. Unfortunately, the implementation of ML projects often fail to achieve their intended goals. This fail
Using Generative AI To Accelerate Feature Engineering At FeatureByte
Summary One of the most time consuming aspects of building a machine learning model is feature engineering. Generative AI offers the possibility of accelerating the discovery and creation of feature pipelines. In this episode Colin Priest e
Learn And Automate Critical Business Workflows With 8Flow
Summary Every business develops their own specific workflows to address their internal organizational needs. Not all of them are properly documented, or even visible. Workflow automation tools have tried to reduce the manual burden involved
Considering The Ethical Responsibilities Of ML And AI Engineers
Summary Machine learning and AI applications hold the promise of drastically impacting every aspect of modern life. With that potential for profound change comes a responsibility for the creators of the technology to account for the ramific
Build Intelligent Applications Faster With RelationalAI
Summary Building machine learning systems and other intelligent applications are a complex undertaking. This often requires retrieving data from a warehouse engine, adding an extra barrier to every workflow. The RelationalAI engine was buil
Building Better AI While Preserving User Privacy With TripleBlind
Summary Machine learning and generative AI systems have produced truly impressive capabilities. Unfortunately, many of these applications are not designed with the privacy of end-users in mind. TripleBlind is a platform focused on embedding
Enhancing The Abilities Of Software Engineers With Generative AI At Tabnine
Summary Software development involves an interesting balance of creativity and repetition of patterns. Generative AI has accelerated the ability of developer tools to provide useful suggestions that speed up the work of engineers. Tabnine i
Validating Machine Learning Systems For Safety Critical Applications With Ketryx
Summary Software systems power much of the modern world. For applications that impact the safety and well-being of people there is an extra set of precautions that need to be addressed before deploying to production. If machine learning and
Applying Declarative ML Techniques To Large Language Models For Better Results
Summary Large language models have gained a substantial amount of attention in the area of AI and machine learning. While they are impressive, there are many applications where they are not the best option. In this episode Piero Molino expl
