Nathan Labenz and Prakash Narayanan lead this AI:AM highlights episode with a live, hosts-only exploration of Anthropic’s “global workspace” paper, including the J-space and J-lens claims about readable concepts inside language models and the limits of what current probes can see. The episode then moves through Prakash’s AI Engineer World’s Fair field notes, Pangram AI-writing detector experiments, Dan Schwarz of FutureSearch on past-casting and AI superforecasting, Zeev Farbman on open world models, and Kunle Olukotun on the compute layer. The central stake is whether interpretability tools, forecasting benchmarks, enterprise deployment patterns, and AI hardware can make increasingly capable systems more legible and governable before their reasoning becomes too hidden to trust.
For full show notes, links, and references, read the episode page:https://www.cognitiverevolution.ai/ai-am-highlights-exploring-the-j-space-ai-superforecasters-sambanova-s-chips-ltx-video-gen/
Sponsor:
Claude:
Claude by Anthropic is an AI collaborator that understands your workflow and helps you tackle research, writing, coding, and organization with deep context. Get started with Claude and explore Claude Pro at https://claude.ai/tcr
CHAPTERS:
(00:00) J-space paper preview
(05:37) Monitoring hidden reasoning
(13:31) Scale and critiques (Part 1)
(17:18) Sponsor: Claude
(19:09) Scale and critiques (Part 2)
(19:10) Finding hidden goals
(30:00) Anthropomorphic safety optimism
(39:02) Engineer field notes
(42:41) Detecting AI writing
(49:30) Enterprise workflow risks
(52:08) Forecasts and world models
(01:35:15) Building Q live
(01:37:24) SambaNova inference architecture
(01:42:38) AI chip taxonomy
(01:47:27) Bandwidth over capacity
(01:53:32) Testing model iterations
(01:55:35) Enforcing espoused values
(01:58:06) AI panopticon bargain
(02:01:40) Closing programming note
(02:02:29) Episode Outro
(02:05:48) Outro
PRODUCED BY:
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