The Machine Learning Podcast

Episode Archive

Episode Archive

32 episodes of The Machine Learning Podcast since the first episode, which aired on June 3rd, 2022.

  • Strategies For Building A Product Using LLMs At DataChat

    March 3rd, 2024  |  48 mins 40 secs

    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 a unique challenge. Jignesh Patel is building DataChat to bring the capabilities of LLMs to organizational analytics, allowing anyone to have conversations with their business data. In this episode he shares the methods that he is using to build a product on top of this constantly shifting set of technologies.

  • Improve The Success Rate Of Your Machine Learning Projects With bizML

    February 18th, 2024  |  50 mins 22 secs

    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 failure is due to a lack of collaboration and investment across technological and organizational boundaries. To help improve the success rate of machine learning projects Eric Siegel developed the six step bizML framework, outlining the process to ensure that everyone understands the whole process of ML deployment. In this episode he shares the principles and promise of that framework and his motivation for encapsulating it in his book "The AI Playbook".

  • Using Generative AI To Accelerate Feature Engineering At FeatureByte

    February 11th, 2024  |  44 mins 59 secs
    feature engineering, generative ai

    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 explains how FeatureByte is applying generative AI models to the challenge of building and maintaining machine learning pipelines.

  • Learn And Automate Critical Business Workflows With 8Flow

    January 28th, 2024  |  43 mins 2 secs

    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, but they are rigid and require substantial investment of time to discover and develop the routines. Boaz Hecht co-founded 8Flow to iteratively discover and automate pieces of workflows, bringing visibility and collaboration to the internal organizational that keep the business running.

  • Considering The Ethical Responsibilities Of ML And AI Engineers

    January 28th, 2024  |  39 mins 26 secs

    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 ramifications of their work. In this episode Nicholas Cifuentes-Goodbody guides us through the minefields of social, technical, and ethical considerations that are necessary to ensure that this next generation of technical and economic systems are equitable and beneficial for the people that they impact.

  • Build Intelligent Applications Faster With RelationalAI

    December 30th, 2023  |  58 mins 24 secs

    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 built as a co-processor for your data warehouse that adds a greater degree of flexibility in the representation and analysis of the underlying information, simplifying the work involved. In this episode CEO Molham Aref explains how RelationalAI is designed, the capabilities that it adds to your data clouds, and how you can start using it to build more sophisticated applications on your data.

  • Building Better AI While Preserving User Privacy With TripleBlind

    November 21st, 2023  |  46 mins 54 secs

    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 privacy preserving techniques in the machine learning process to produce more user-friendly AI products. In this episode Gharib Gharibi explains how the current generation of applications can be susceptible to leaking user data and how to counteract those trends.

  • Enhancing The Abilities Of Software Engineers With Generative AI At Tabnine

    November 12th, 2023  |  1 hr 4 mins

    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 is one of the main platforms offering an AI powered assistant for software engineers. In this episode Eran Yahav shares the journey that he has taken in building this product and the ways that it enhances the ability of humans to get their work done, and when the humans have to adapt to the tool.

  • Validating Machine Learning Systems For Safety Critical Applications With Ketryx

    November 7th, 2023  |  51 mins 12 secs

    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 AI are part of that application then there is a greater need to validate the proper functionality of the models. In this episode Erez Kaminski shares the work that he is doing at Ketryx to make that validation easier to implement and incorporate into the ongoing maintenance of software and machine learning products.

  • Applying Declarative ML Techniques To Large Language Models For Better Results

    October 24th, 2023  |  46 mins 11 secs

    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 explains how declarative ML approaches allow you to make the best use of the available tools across use cases and data formats.

  • Surveying The Landscape Of AI and ML From An Investor's Perspective

    October 15th, 2023  |  1 hr 2 mins

    Artificial Intelligence is experiencing a renaissance in the wake of breakthrough natural language models. With new businesses sprouting up to address the various needs of ML and AI teams across the industry, it is a constant challenge to stay informed. Matt Turck has been compiling a report on the state of ML, AI, and Data for his work at FirstMark Capital. In this episode he shares his findings on the ML and AI landscape and the interesting trends that are developing.

  • Applying Federated Machine Learning To Sensitive Healthcare Data At Rhino Health

    September 10th, 2023  |  49 mins 54 secs

    A core challenge of machine learning systems is getting access to quality data. This often means centralizing information in a single system, but that is impractical in highly regulated industries, such as healthchare. To address this hurdle Rhino Health is building a platform for federated learning on health data, so that everyone can maintain data privacy while benefiting from AI capabilities. In this episode Ittai Dayan explains the barriers to ML in healthcare and how they have designed the Rhino platform to overcome them.

  • Using Machine Learning To Keep An Eye On The Planet

    June 17th, 2023  |  42 mins 32 secs

    Satellite imagery has given us a new perspective on our world, but it is limited by the field of view for the cameras. Synthetic Aperture Radar (SAR) allows for collecting images through clouds and in the dark, giving us a more consistent means of collecting data. In order to identify interesting details in such a vast amount of data it is necessary to use the power of machine learning. ICEYE has a fleet of satellites continuously collecting information about our planet. In this episode Tapio Friberg shares how they are applying ML to that data set to provide useful insights about fires, floods, and other terrestrial phenomena.

  • The Role Of Model Development In Machine Learning Systems

    May 28th, 2023  |  46 mins 41 secs

    The focus of machine learning projects has long been the model that is built in the process. As AI powered applications grow in popularity and power, the model is just the beginning. In this episode Josh Tobin shares his experience from his time as a machine learning researcher up to his current work as a founder at Gantry, and the shift in focus from model development to machine learning systems.

  • Real-Time Machine Learning Has Entered The Realm Of The Possible

    March 9th, 2023  |  34 mins 29 secs

    Machine learning models have predominantly been built and updated in a batch modality. While this is operationally simpler, it doesn't always provide the best experience or capabilities for end users of the model. Tecton has been investing in the infrastructure and workflows that enable building and updating ML models with real-time data to allow you to react to real-world events as they happen. In this episode CTO Kevin Stumpf explores they benefits of real-time machine learning and the systems that are necessary to support the development and maintenance of those models.

  • How Shopify Built A Machine Learning Platform That Encourages Experimentation

    February 2nd, 2023  |  1 hr 6 mins

    Shopify uses machine learning to power multiple features in their platform. In order to reduce the amount of effort required to develop and deploy models they have invested in building an opinionated platform for their engineers. They have gone through multiple iterations of the platform and their most recent version is called Merlin. In this episode Isaac Vidas shares the use cases that they are optimizing for, how it integrates into the rest of their data platform, and how they have designed it to let machine learning engineers experiment freely and safely.