
← Machine Learning Street Talk (MLST)11 sept. · 2 h 02 min
How Replication Could Teach Machines What Good Science Looks Like — Edward Hughes
<p>Can a machine learn the judgement that separates a plausible-looking result from a faithful experiment? Edward Hughes, Chief Scientist and co-founder of Inherent, joins Tim Scarfe to argue that creativity is not optimisation, and that the missing capability in AI is choosing which questions are worth asking.</p><p><br></p><p>SPONSOR:</p><p>---</p><p>Cyber Fund built the Monastery to help founders ship products that were impossible a year ago.</p><p>Apply now: https://cyber.fund</p><p>---</p><p><br></p><p>Edward makes the case that Move 37 was innovative rather than creative, and that the field, not the individual, decides what counts as a discovery. That reframing runs through Csikszentmihalyi, Deutsch and exaptation into open-endedness, where deceptive goals and imperfect world models turn out to be the point rather than the problem. The second half turns to the paper: Replica, a task space built by redacting figures from real papers, and Faraday, a 27-billion-parameter model trained to steer a frontier coding agent that then beats the frontier on held-out replications.</p><p><br></p><p>---</p><p>TIMESTAMPS:</p><p>00:00:00 Cold open: Move 37, Faraday and collective intelligence</p><p>00:01:08 Sponsor: CyberFund</p><p>00:01:46 Inherent's $50M raise and the road from string theory</p><p>00:09:14 Three timescales of learning: weights, context, culture</p><p>00:13:47 Move 37 was innovative, not creative: the field decides</p><p>00:20:39 Creativity as satisficing: the urinal and evolution</p><p>00:25:06 Exaptation and the Tristan chord: creativity in context</p><p>00:30:56 Coherence for whom? Deutsch's hard-to-vary explanations</p><p>00:35:53 Why copying is creative: Deutsch and the constraint engineer</p><p>00:42:27 Societies of agents and the strong Moravec paradox</p><p>00:45:51 Evaluate in hindsight: from Lean proofs to climate change</p><p>00:51:56 Picbreeder, local goals and why discovery needs deception</p><p>00:57:21 Spaghetti proofs, translation layers and superhuman Go</p><p>01:00:37 Does nature compress? Naturalness and real patterns</p><p>01:07:36 Why replicate? Replica's redacted figures and Faraday</p><p>01:12:31 Faraday beats Codex, Claude and GLM 5.2 on held-out tasks</p><p>01:15:31 Replication to innovation: how the Transformer happened</p><p>01:18:26 Deep replication: what Faraday learns from Voyager and GNoME</p><p>01:23:37 Can the AI scientist cheat? Goodharting the judge</p><p>01:29:09 Inside Replica: scale-down, 8xB300 runs