Try for free
"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis
"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis

AI in the AM: 99% off search, GPT-5.5 is "clean", model welfare analysis, & efficient analog compute

26 April 2026 2:38:01 Erik Torenberg, Nathan Labenz

Listen to episode

About this episode

This edition of AI in the AM features Anna Patterson on Ceramic.ai’s pivot to low-cost enterprise search for LLMs, designed to combine public and private data with stronger fact-checking. Lukas Petersson returns with new Andon Labs results on Opus 4.7 and GPT-5.5, including surprising differences in performance, behavior, and “ruthless” tactics. Zvi Mowshowitz unpacks model welfare and how to interpret troubling model behavior, while Naveen Verma explains EnCharge AI’s analog in-memory computing approach for dramatically more efficient local inference.



Sponsors:

AvePoint:

AvePoint is building the control layer for AI agents so you can securely govern, audit, and recover every action at scale. Design trusted agentic outcomes from day one at https://avpt.co/tcr

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

VCX:

VCX, by Fundrise, is the public ticker for private tech, giving everyday investors access to high-growth private companies in AI, space, defense tech, and more. Learn how to invest at https://getvcx.com

Tasklet:

Build your own Cognitive Revolution monitoring agent in one click.
Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai



More AI podcast episodes

Browse all →

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 "The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support