AI:AM — AI Memory Chips, Agent Rankings and AI-Powered Networking · October 28, 2026
Notas do episódio
Kepler Computing CEO Debo Olaosebikan explains how ferroelectric memory could increase cache density and improve high-bandwidth memory using standard fab equipment. Arena CEO Anastasios Angelopoulos discusses agent evaluation, alignment failures and model rankings, while Union CEO Samvit Ramadurgam explores AI-assisted brokering, startup hiring and the continuing importance of human relationships.
Chapters
(0:00) Memory, rankings and human connections
(1:27) Claude Duet gets it done, for a price
(3:21) Meet Debo Olaosebikan, Kepler Computing CEO
(4:30) Why AI is rationed and where energy goes
(6:54) Stack the bits instead of shrinking the transistor
(10:02) Finding a material that flips cheaply yet stays stable
(13:29) The winning material is a stack, not one recipe
(16:03) Materials AI is bottlenecked by experiment data
(17:32) Two products: denser cache and efficient HBM
(19:45) Can standard fab tools make Kepler's memory?
(22:12) Could cheaper fabs add tenfold more compute?
(24:25) Three-dimensional silicon comes before leaving silicon
(25:25) Production next year, then a gigawatt ramp
(26:32) Meet Anastasios Angelopoulos from Arena
(27:38) Arena measures work, not multiple-choice answers
(28:43) User satisfaction is only one quality signal
(30:12) Models know when they are being tested
(31:05) Long agent sessions reveal hidden violations
(32:35) Three ways an agent betrays its user
(34:32) Paid evaluations fund Arena's free inference
(35:42) A thank-you message can cost forty dollars
(37:11) Overall rankings can hide language-specific performance
(38:39) Private benchmarks do not prevent repeated-test gaming
(40:32) Coding agents change what evaluators can measure
(42:08) OpenAI leads, but alignment failures persist
(44:18) Production failures must feed agent training
(46:15) Meet Samvit Ramadurgam, Union founder
(47:34) Humans still broker most of the economy
(49:17) Union hires for ideas, not execution
(50:16) A target of two billion tokens per person
(51:43) Cheap models first, heavy models for the hardest cases
(52:36) Why people recoil from AI outreach
(55:27) The long tail is already very long
(57:16) Friendly fees earn more referrals than hard bargaining
(58:50) Humans hold the call, AI holds the memory
(1:00:11) The moat is the network, not the software
(1:02:37) Act two is coordinating humanity itself
(1:04:26) The same tool could organize ethnic hatred
(1:06:44) Humans keep a monopoly on their own perspective
(1:08:14) Cheaper AI startups threaten conventional SaaS
(1:09:20) Can growth absorb the jobs AI replaces?
(1:10:17) Could AI deliver a company in a box?
(1:12:13) Robot kitchens cannot make us eat more
(1:13:22) Can philanthropy make AI status games useful?
Guests
Anastasios Angelopoulos — Cofounder and CEO, Arena (𝕏 | LinkedIn)
Debo Olaosebikan — CEO, Kepler Computing (𝕏 | LinkedIn)
Samvit Ramadurgam — Founder, CEO, Union (𝕏 | LinkedIn)
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