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.
Hi, I’m Ksenia, founder of Turing Post.
On this channel, I talk to the people shaping AI and pay attention to the ideas, shifts, and details others might miss.
Inference is my interview show with innovators, builders, founders, and thinkers moving AI forward.
Attention Span is where I slow down on what deserves a closer look: the signals, questions, and stories hiding between the headlines.
Subscribe for the unusual takes. And always stay curious!
Is Google over? Many people are asking, but that is the wrong lens.
We look at what actually happened and why this leadership reset may be good for Google, and even better for Jeff Dean and Demis Hassabis.
Dean left Google after 27 years with Sanjay Ghemawat, Oriol Vinyals, and Quoc Le to launch Discovery Loop, which aims to automate scientific experimentation. The same day, Hassabis stepped back from running Google DeepMind, while Koray Kavukcuoglu took control of Gemini models, frontier research, the Gemini app, and developer teams under Sundar Pichai.
Taken together, these moves reveal what Google is becoming.
Read the FOD editorial that preceded this episode: https://www.turingpost.com/p/google-ai-race-hassabis-pichai
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Hashtags
#JeffDean #DiscoveryLoop #GoogleDeepMind #Gemini #ArtificialIntelligence
Links:
Google, “The next chapter of our AI momentum” (official leadership announcement): https://blog.google/company-news/inside-google/message-ceo/next-chapter-ai-momentum/
Jeff Dean, Discovery Loop launch announcement: https://x.com/JeffDean/status/2085034604172603724
Jeff Dean, redacted farewell note: https://x.com/JeffDean/status/2085083442669318443
Discovery Loop, mission and team: https://www.discoveryloop.com/
Wired, “Jeff Dean Leaves Google to Launch Discovery Loop”: https://www.wired.com/story/jeff-dean-google-discovery-loop-startup/
Turing Post FOD editorial, “Why ‘The Actual Reason Why Google Fell Out of the AI Race Changes Everything’ Is Wrong”: https://www.turingpost.com/p/google-ai-race-hassabis-pichai
Alphabet 2026 proxy statement, beneficial ownership and voting power: https://www.sec.gov/Archives/edgar/data/1652044/000130817926000342/goog-20260424.htm
Google I/O 2026 keynote remarks, internal coding and developer-agent figures: https://blog.google/intl/en-in/company-news/technology/sundar-pichai-io-2026/
Google Cloud Next 2026 remarks, AI-generated code figure: https://blog.google/innovation-and-ai/infrastructure-and-cloud/google-cloud/cloud-next-2026-sundar-pichai/
Reuters, Google AI leadership changes and delayed flagship release: https://www.reuters.com/business/google-shakes-up-ai-leadership-deepmind-chief-shifts-role-2026-08-05/
The Information, Google’s coding-model strike team: https://www.theinformation.com/articles/google-creates-strike-team-improve-coding-models
The Information, Koray’s Gemini consolidation: https://www.theinformation.com/articles/googles-new-ai-architect-plans-spread-gemini-everywhere
Google, combining Brain and DeepMind in 2023: https://blog.google/innovation-and-ai/technology/ai/april-ai-update/
Jeff Dean, official Google Research profile: https://research.google/people/jeff/
University of Washington, “Whole-Program Optimization of Object-Oriented Languages”: https://projectsweb.cs.washington.edu/research/projects/cecil/pubs/jdean-thesis.html
University of Washington, whole-program optimization paper and Vortex results: https://projectsweb.cs.washington.edu/research/projects/cecil/www/Papers/whole-program.html
University of Minnesota, Dean on his parallel neural-network thesis: https://cse.umn.edu/cs/news/cse-alumnus-jeff-dean-returns-campus-commencement
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