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.
Is compute the main roadblock? Or the models are not big enough for AGI?
Ulrik Hansen, president and co-founder of Encord, argues that the true bottleneck is data.
In this episode of Inference, we get into:
Why models are mostly interchangeable, but data orchestration makes or breaks real-world AI
Tesla’s compounding advantage from live human feedback vs. Waymo’s cautious rollout
Why robotics lags behind digital AI – and how feedback loops shape both
The coming split between “cheap” intelligence (facts and patterns) and “expensive” intelligence (creativity, taste, vision)
What is the new connection economy
We also discuss the risks: synthetic data eating its own tail, the trust and safety challenges that make brand more valuable than ever, and why Ulrik believes the next 10 years will bring more change than the last 50.
This is a conversation about the future of AI systems, the bottlenecks that matter, and what it means when humans and machines start sharing the same workflows. Watch it!
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Guest:
Ulrik Hansen, president and co-founder of Encord
https://www.linkedin.com/in/ulrik-stig-hansen-2658273b/
https://x.com/ulrikstighansen
https://x.com/encord_team
https://encord.com/
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Chapters
Turing Post is a newsletter about AI’s past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live.
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#AI #FutureOfAI #DataBottleneck #SelfDriving #Tesla #Waymo #Robotics
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