The Thoughtworks podcast plunges deep into the latest tech topics that have captured our imagination. Join our panel of senior technologists to explore the most...
The release of DeepSeek's AI models at the end of January 2025 sent shockwaves around the world. The weeks that followed have been rife with hype and rumor, ranging from suggestions that DeepSeek has completely upended the tech industry to claims the efficiency gains ostensibly unlocked by DeepSeek are exagerrated. So, what's the reality? And what does it all really mean for the tech industry? In this episode of the Technology Podcast, two of Thoughtworks' AI leaders — Prasanna Pendse (Global Director of AI Strategy) and Shayan Mohanty (Head of AI Research) — join hosts Prem Chandrasekaran and Ken Mugrage to provide a much-needed clear and sober perspective on DeepSeek. They dig into some of the technical details and discuss how the DeepSeek team was able to optimize the limited hardware at their disposal, and think through what the implications might be for the industry in the months to come. Read Prasanna's take on DeepSeek on the Thoughtworks blog: https://www.thoughtworks.com/insights/blog/generative-ai/demystifying-deepseek
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AI testing, benchmarks and evals
Generative AI's popularity has led to a renewed interest in quality assurance — perhaps unsurprising given the inherent unpredictability of the technology. This is why, over the last year, the field has seen a number of techniques and approaches emerge, including evals, benchmarking and guardrails. While these terms all refer to different things, grouped together they all aim to improve the reliability and accuracy of generative AI. To discuss these techniques and the renewed enthusiasm for testing across the industry, host Lilly Ryan is joined by Shayan Mohanty, Head of AI Research at Thoughtworks, and John Singleton, Program Manager for Thoughtworks' AI Lab. They discuss the differences between evals, benchmarking and testing and explore both what they mean for businesses venturing into generative AI and how they can be implemented effectively. Learn more about evals, benchmarks and testing in this blog post by Shayan and John (written with Parag Mahajani): https://www.thoughtworks.com/insights/blog/generative-ai/LLM-benchmarks,-evals,-and-tests
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Exploring the intersections of software architecture
Software architecture necessarily intersects with a diverse range of critical things, including implementation, infrastructure, data and engineering practices. All these elements require serious consideration and reflection if you're to architect effectively. To discuss these various intersections, Thoughtworks' Neal Ford and his long-time collaborator Mark Richards join host Prem Chandrasekaran on the Thoughtworks Technology Podcast. They dive into why these intersections matter, what they mean for software architects and how individuals and teams can go about addressing them.
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Who should make software architecture decisions?
Who should be involved in the process of making decisions about software architecture? That's a question that's been puzzling Thoughtworker Andrew Harmel-Law for some time — so much so that he decided to write a book about it. The result is Facilitating Software Architecture. Published by O'Reilly in December 2024, it's both an argument for and a guide to involving more people in the architecture decision process. To discuss the topic and the book, Andrew joined hosts Neal Ford and Prem Chandrasekaran on the Technology Podcast. They explore why including more roles in software architecture matters today, some of the common objections to and risks of such an approach, alongside techniques and practices that can make doing it in fast-paced and dynamic organizations easier. "It's quite magical when you see this blossoming of understanding of what it is that architects do... It's not less architecture, it's more. It's just happening in a broader sphere." — Andrew Harmel-Law You can find Andrew's book on the O'Reilly website: https://www.oreilly.com/library/view/facilitating-software-architecture/9781098151850/
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Generative AI's uncanny valley: Problem or opportunity?
With the rise of generative AI, the concept of the uncanny valley — where human resemblance unsettles, disturbs or disgusts — is more relevant than ever. But is it a problem that technologists need to tackle? Or does it offer an opportunity for greater thoughtfulness about the ways generative AI is being built, deployed and used? In this episode of the Technology Podcast, host Lilly Ryan is joined by Srinivasan Raguraman to discuss generative AI's uncanny valley and explore how it might offer a model for thinking through our expectations about generative AI outputs and effects. Taking in everything from the experiences of end users to the mental models engineers bring to AI development, listen for a wide-ranging dive into the implications of the uncanny valley in our experience of generative AI today. Read Srinivasan's recent article (written with Ken Mugrage): https://www.technologyreview.com/2024/10/24/1106110/reckoning-with-generative-ais-uncanny-valley/
The Thoughtworks podcast plunges deep into the latest tech topics that have captured our imagination. Join our panel of senior technologists to explore the most important trends in tech today, get frontline insights into our work developing cutting-edge tech and hear more about how today’s tech megatrends will impact you.
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