Inference by Turing Post
Inference by Turing Post
Podcast Description
Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
Podcast Insights
Content Themes
The podcast explores themes centered on AI development, coding philosophy, and AI challenges. Key episodes include discussions on the future of coding with Amjad Masad reflecting on AI agents and their role in software development, Sharon Zhou dissecting AI hallucinations and the importance of grounding benchmarks in reality, and Mati Staniszewski tackling real-time language translation and maintaining emotional nuance in AI voice synthesis, illustrating a commitment to thoughtful, nuanced explorations of AI's impact on society.
Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.
Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.
It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.
If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
At Microsoft Build, I actually sat down with Eric Boyd, Corporate Vice President leading engineering for Microsoft’s AI platform, to talk about what it really means to build AI infrastructure that companies can trust – not just to assist, but to act. We get into the messy reality of enterprise adoption, why trust is still the bottleneck, and what it will take to move from copilots to fully autonomous agents.
We cover:
– When we’ll trust AI to run businesses
– What Microsoft learned from early agent deployments
– How AI makes life easier
– The architecture behind GitHub agents (and why guardrails matter)
– Why developer interviews should include AI tools
– Agentic Web, NLweb, and the new AI-native internet
– Teaching kids (and enterprises) how to use powerful AI safely
– Eric’s take on AGI vs “just really useful tools”
If you’re serious about deploying agents in production, this conversation is a blueprint. Eric blends product realism, philosophical clarity, and just enough dad humor. I loved this one.
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Guest:
Eric Boyd, CVP of AI platform at Microsoft
https://www.linkedin.com/in/emboyd/
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Chapters
0:00 The big question: When will we trust AI to run our businesses?
1:28 From code-completions to autonomous agents – the developer lens
2:15 Agent acts like a real dev and succeeds
3:25 AI taking over tedious work
3:32 Building trustworthy AI vs. convincing stakeholders to trust it
4:46 Copilot in the enterprise: early lessons and the guard-rail mindset
6:17 What is Agentic Web?
7:55 Parenting in the AI age
9:41 What counts as AGI?
11:32 How developer roles are already shifting with AI
12:33 Timeline forecast for 2-5 years re
13:33 Opportunities and concerns
15:57 Enterprise hurdles: identity, governance, and data-leak safeguards
16:48 Books that shaped the guest
Turing Post is a newsletter about AI’s past, present, and future. We explore how intelligent systems are built – and how they’re changing how we think, work, and live.
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