Modern AI has been dominated by one idea: predict the next token. But what if intelligence doesn?t have to work that way?

In this episode of The Neuron, we?re joined by Eve Bodnia, Founder and CEO of Logical Intelligence, to explore energy-based models (EBMs)?a radically different approach to AI reasoning that doesn?t rely on language, tokens, or next-word prediction.

With a background in theoretical physics and quantum information, Eve explains how EBMs operate over an energy landscape, allowing models to reason about many possible solutions at once rather than guessing sequentially. We discuss why this matters for tasks like spatial reasoning, planning, robotics, and safety-critical systems?and where large language models begin to show their limits.

You?ll learn:

What energy-based models are (in plain English)

Why token-free architectures change how AI reasons

How EBMs reduce hallucinations through constraints and verification

Why EBMs and LLMs may work best together, not in competition

What this approach reveals about the future of AI systems

To learn more about Eve?s work, visit https://logicalintelligence.com.

For more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

AI is moving fast ? and 2026 is shaping up to be a turning point.
In this livestream, Corey and Grant from The Neuron break down our biggest AI predictions for 2026, including:

? Which companies, tools, and model types are most likely to come out on top

? Who could lose ground (and what?s driving the shift)
? The wildcards most people aren?t factoring in yet
? What to watch across AI policy, agents, open source, and consumer adoption

? The skills and strategies that will matter most in 2026
Join us live for audience Q&A and a real-time debate on the hottest AI takes ? then drop your prediction in the comments: what?s the biggest AI surprise coming in 2026? ?

Subscribe for weekly AI coverage from The Neuron and more livestreams like this.
?? https://theneuron.ai

In this special episode, we go hands-on with three cutting-edge AI tools from Google Labs. First, Jaclyn Konzelman (Director of Product Management) demos Mixboard, an AI-powered concepting board that transforms ideas into visual presentations using Nano Banana Pro. Then, Thomas Iljic (Senior Director of Product Management) shows us Flow, Google's AI filmmaking tool that lets you create, edit, and animate video clips with unprecedented control. Finally, Megan Li (Senior Product Manager) walks us through Opal, a no-code AI app builder that lets anyone create custom AI workflows and mini-apps using natural language.

Subscribe to The Neuron newsletter: https://theneuron.ai

Links:

Mixboard: https://mixboard.google.com 

Flow: https://flow.google 

Opal: https://opal.google 

Google Labs: https://labs.google 

Autonomous coding agents are moving from demos to real production workflows. In this episode, Factory AI co-founder and CTO Eno Reyes explains what "Droids" really are?fully autonomous agents that can take tickets, modify real codebases, run tests, and work inside existing dev workflows.

We dig into Factory's context compression research (which outperformed both OpenAI and Anthropic), what makes a codebase "agent-ready," and why Stanford research found that the ONLY predictor of AI success was codebase quality?not adoption rates or token usage.

Whether you're a developer curious about autonomous coding tools or just want to understand where AI engineering is headed, this episode is packed with practical insights.

? Try Factory AI: https://factory.ai

? Subscribe to The Neuron newsletter: https://theneuron.ai

? Resources mentioned:
? Factory's compression research: https://factory.ai/news/evaluating-compression

AI reasoning models don?t just give answers ? they plan, deliberate, and sometimes try to cheat.

In this episode of The Neuron, we?re joined by Bowen Baker, Research Scientist at OpenAI, to explore whether we can monitor AI reasoning before things go wrong ? and why that transparency may not last forever.

Bowen walks us through real examples of AI reward hacking, explains why monitoring chain-of-thought is often more effective than checking outputs, and introduces the idea of a ?monitorability tax? ? trading raw performance for safety and transparency.

We also cover:

Why smaller models thinking longer can be safer than bigger models

How AI systems learn to hide misbehavior

Why suppressing ?bad thoughts? can backfire

The limits of chain-of-thought monitoring

Bowen?s personal view on open-source AI and safety risks

If you care about how AI actually works ? and what could go wrong ? this conversation is essential.

Resources:

Title URL

Evaluating chain-of-thought monitorability | OpenAI https://openai.com/index/evaluating-chain-of-thought-monitorability/

Understanding neural networks through sparse circuits | OpenAI https://openai.com/index/understanding-neural-networks-through-sparse-circuits/

OpenAI's alignment blog: https://alignment.openai.com/

? Subscribe for more interviews with the people building AI

? Join the newsletter at https://theneuron.ai

Everyone is rushing to build AI agents ? but most companies are setting themselves up for failure.

In this episode of The Neuron, Darin Patterson, VP of Market Strategy at Make, explains why agentic AI only works if your automation foundation is solid first. We break down when to use deterministic workflows vs AI agents, how to avoid fragile automation sprawl, and why visibility into your entire automation landscape is now mission-critical.

You?ll see real examples of building agents in Make, how Model Context Protocol (MCP) fits into modern workflows, and why orchestration ? not hype ? is the real unlock for scaling AI safely inside organizations.

Subscribe to The Neuron newsletter for more interviews with the leaders shaping the future of work and AI: https://theneuron.ai

IBM just released Granite 4.0, a new family of open language models designed to be fast, memory-efficient, and enterprise-ready ? and it represents a very different philosophy from today?s frontier AI race.

In this episode of The Neuron, IBM Research?s David Cox joins us to unpack why IBM treats AI models as tools rather than entities, how hybrid architectures dramatically reduce memory and cost, and why openness, transparency, and external audits matter more than ever for real-world deployment.

We dive into long-context efficiency, agent safety, LoRA adapters, on-device AI, voice interfaces, and why the future of AI may look a lot more boring ? in the best possible way.

If you?re building AI systems for production, agents, or enterprise workflows, this conversation is required listening.

Subscribe to The Neuron newsletter for more interviews with the leaders shaping the future of work and AI: https://theneuron.ai

Imagine an AI that doesn?t just output answers ? it remembers, adapts, and reasons over time like a living system. In this episode of The Neuron, Corey Noles and Grant Harvey sit down with Zuzanna Stamirowska, CEO & Cofounder of Pathway, to break down the world?s first post-Transformer frontier model: BDH ? the Dragon Hatchling architecture.

Zuzanna explains why current language models are stuck in a ?Groundhog Day? loop ? waking up with no memory ? and how Pathway?s architecture introduces true temporal reasoning and continual learning.

We explore:

? Why Transformers lack real memory and time awareness

? How BDH uses brain-like neurons, synapses, and emergent structure

? How models can ?get bored,? adapt, and strengthen connections

? Why Pathway sees reasoning ? not language ? as the core of intelligence

? How BDH enables infinite context, live learning, and interpretability

? Why gluing two trained models together actually works in BDH

? The path to AGI through generalization, not scaling

? Real-world early adopters (Formula 1, NATO, French Postal Service)

? Safety, reversibility, checkpointing, and building predictable behavior

? Why this architecture could power the next era of scientific innovation

From brain-inspired message passing to emergent neural structures that literally appear during training, this is one of the most ambitious rethinks of AI architecture since Transformers themselves.

If you want a window into what comes after LLMs, this interview is essential.

Subscribe to The Neuron newsletter for more interviews with the leaders shaping the future of work and AI: https://theneuron.ai

Carina Hong dropped out of Stanford's PhD program to build "mathematical superintelligence" ? and just raised $64M to do it. In this episode, we explore what that actually means: an AI that doesn't just solve math problems but discovers new theorems, proves them formally, and gets smarter with each iteration. Carina explains how her team solved a 130-year-old problem about Lyapunov functions, disproved a 30-year-old graph theory conjecture, and why math is the secret "bedrock" for everything from chip design to quant trading to coding agents. We also discuss the fascinating connections between neuroscience, AI, and mathematics.

Lean more about Axiom: https://axiommath.ai/ 

Subscribe to The Neuron newsletter: https://theneuron.ai

Nick Talken started a 3D printing materials company in a trailer lab in his co-founder's backyard, sold it to a 145-year-old German chemical giant, then spun out an AI platform that's now transforming R&D for Fortune 100 companies. Albert Invent's foundational AI model?trained on 15 million molecular structures?is helping scientists at companies like Kenvue (maker of Tylenol, Neutrogena, and Listerine) compress projects from 3 months to 2 days. We dig into how enterprises train bespoke AI models on proprietary data, why you can't just use ChatGPT for chemistry, and what becomes possible when AI can "think like a chemist."

Subscribe to The Neuron newsletter: https://theneuron.ai

Albert Invent website: https://www.albertinvent.com

Kenvue partnership announcement: https://www.businesswire.com/news/home/20251014240355/en/

Most enterprise knowledge is trapped in meetings?and then lost forever. Otter.ai CEO Sam Liang explains how his company turned meeting transcription into a $100M+ revenue business by solving a problem most companies don't even realize they have.In this episode, we cover:- Why meetings are your company's most expensive activity (and how to measure ROI on them)- Building a "meeting-centric knowledge base" that captures voice data other systems miss- How Otter organizes enterprise knowledge like Slack?but for spoken conversations- Real-time sales coaching that feeds reps answers during customer calls- AI avatars that attend meetings on your behalf (and ask questions for you)- The technical challenges of understanding dialects, tone, and context in voice AI- How one financial company used Otter to onboard new clients instantly with full conversation history- Privacy vs. utility: designing permission systems for meeting data- The future of active AI agents that contribute to meetings, not just transcribe themSam previously worked on the blue dot location platform for Google Maps and now runs a company that's transcribed over 1 billion meetings. If you're thinking about how AI can actually improve enterprise workflows (not just automate busywork), this conversation is packed with specific, tactical insights.A special thank you to this episode's sponsor, SAS: https://www.sas.com/en/whitepapers/how-aiot-is-reshaping-industrial-efficiency-security-and-decision-making.html?utm_source=other&utm_medium=cpm&utm_campaign=-globalResources mentioned:? Otter.ai $100M ARR announcement: https://otter.ai/blog/otter-ai-breaks-100m-arr-barrier-and-transforms-business-meetings-launching-industry-first-ai-meeting-agent-suite? HIPAA compliance: https://otter.ai/blog/otter-ai-achieves-hipaa-compliance? Otter.ai: https://otter.aiSubscribe to The Neuron newsletter: https://theneuron.ai? CHAPTERS0:00 - Introduction & Sam's Background1:16 - From Meeting Notes to Enterprise Knowledge04:48 - Building a Meeting-Centric Knowledge Base06:14 - Why Meetings Are Your Most Expensive Activity05:40 - Solving Information Silos with AI07:56 - A Message from our Sponsor SAS9:11 - Meeting Transcriptions Alone Aren't the Answer17:34 - Leader Dashboards & AI Workflows18:49 - AI Avatars: Send Your Digital Self to Meetings21:45 - Active AI Agents That Talk Back23:13 - Privacy, Permissions & Corporate Culture26:08 - Technical Challenges: Understanding Context & Tone34:37 - Privacy vs. Utility Trade-offs37:25 - The Future of Meetings in 202739:27 - Competing with Microsoft & Google43:02 - How Otter Generated Over $1 Billion in Customer ROI46:05 - What Excites & Concerns Sam About AI49:09 - Security Risks of AI Avatars49:50 - Final Thoughts on the Future of AI at WorkHosted by: Corey Noles and Grant HarveyGuest: Sam Liang, Co-founder & CEO, Otter.aiPublished by: Manique SantosEdited by: Kush Felisilda

In this episode, we sit down with Pavan Davuluri, Corporate Vice President of Microsoft's Windows + Devices business, to explore how Windows is evolving into an AI-native platform. Pavan leads the team responsible for strategy, design, and delivery of Windows products across the full stack - from silicon and devices to platform, OS, apps, experiences, security, and cloud. With 23 years at Microsoft, he's driven the creation of the Surface line and now oversees how hardware and software fuse together with AI at the center. We explore how Copilot is being deeply integrated into Windows, the engineering shifts required to make Windows a more proactive and intelligent platform, and how Microsoft balances powerful automation with user control. From Surface design standards influencing the broader ecosystem to supporting OEM partners in the AI PC era, Pavan reveals the principles guiding Windows' transformation and what the computing experience will look like in the next five years.

Subscribe to The Neuron newsletter: https://theneuron.ai

Microsoft Surface: https://www.microsoft.com/surface

Windows AI features: https://www.microsoft.com/windows/ai-features

While everyone obsesses over which AI model is smartest, a quiet revolution is happening in the infrastructure layer underneath. Modular just raised $250M at a $1.6B valuation to solve a problem most people don't know exists: AI is locked into expensive, vendor-specific hardware ecosystems. Tim Davis, Co-Founder & President of Modular, joins us to explain why his company is building the "hypervisor for AI"?making it possible to write code once and run it on any GPU, from NVIDIA to AMD to Apple Silicon. We dive into why this matters for businesses, what the Android analogy really means, how companies are seeing 70-80% cost reductions, and whether we're even on the right path to superintelligence.

Subscribe to The Neuron newsletter: https://theneuron.ai

Try Modular: https://modular.com

Getting Started Guide: https://modular.com/get-started

In this episode, we sit down with Scott Guthrie, EVP of Microsoft's Cloud + AI Group, to explore the architecture behind Azure's AI Superfactory. Scott oversees Microsoft's hyperscale cloud computing solutions including Azure, generative AI platforms, and next-generation infrastructure. We dive into Microsoft's strategic approach to AI datacenter buildout, the innovative Fairwater architecture with its 120,000+ fiber miles of AI WAN backbone, and how Microsoft is balancing performance, sustainability, and cost at planet-scale. From dense GPU clusters drawing 140kW per rack to closed-loop liquid cooling systems, Scott reveals the engineering trade-offs behind infrastructure that powers frontier AI models with trillions of parameters. Whether you're an enterprise leader planning AI adoption or a developer curious about cloud architecture, you'll leave understanding how Microsoft is executing on next-gen infrastructure that transforms global challenges into opportunities.

Subscribe to The Neuron newsletter: https://theneuron.ai

Retool CEO David Hsu reveals that 48% of non-engineers are now shipping software. We explore how AI is democratizing software development, why engineers might stop coding internal apps within 18-24 months, and what this means for the future of work. David shares insights from Retool's survey of 10,000+ companies, Retool?s new AppGen program, and how "tomorrow's developers" are using AI to build real production applications on enterprise data.

Subscribe to The Neuron newsletter: https://theneuron.ai

Learn more about Retool: https://retool.com

Computers can see and hear, but they've never been able to smell?until now. In this episode, we sit down with Alex Wiltschko, Founder & CEO of Osmo, to explore how his company is using AI to digitize scent. Alex walks us through how they "teleported" the smell of a fresh plum across their lab, created the world's first AI-designed fragrance molecules, and built Osmo Studio?a platform that lets anyone design custom fragrances in one week instead of two years. We discuss the read/map/write framework for digitizing smell, why scent is tied directly to memory and emotion, and how this technology could eventually detect diseases like cancer and Parkinson's earlier than any current diagnostic. Plus: what does the Museum of Pop Culture smell like, and can AI really create a fragrance from a Bon Iver song?

Links:

Osmo: https://www.osmo.ai

Scent Teleportation Update: https://www.osmo.ai/blog/update-scent-teleportation-we-did-it

Osmo Studio: https://osmostudios.ai/

Subscribe to The Neuron newsletter: https://theneuron.ai

Check out the sponsor of this video, Flora: https://dub.florafauna.ai/neuronSubscribe to The Neuron newsletter: https://theneuron.aiHosted by: Corey Noles and Grant HarveyGuest: Alex Wiltschko (Founder & CEO, Osmo)Published by: Manique SantosEdited by: Kush Felisilda

Behind every AI response, there's an invisible army of humans who trained it. In this episode, we talk with Casper Elliott from Invisible Technologies - the company that's trained 80% of the world's top AI models. We explore how models actually learn, why data quality matters more than quantity, what enterprises get wrong about AI deployment, and whether AI will really automate everyone's jobs. Casper shares insights from working with frontier labs, reveals the surprising skills that make great AI trainers (hint: League of Legends helps), and explains why the future needs more humans, not fewer.

Subscribe to The Neuron newsletter: https://theneuron.ai

Learn more about Invisible Technologies: https://invisibletech.ai

Ever wondered who's actually teaching ChatGPT and Claude how to think?

Meet Caspar Eliot from Invisible Technologies - the company behind 80% of the world's top AI model training. In this eye-opening conversation, we uncover the massive human workforce behind "artificial" intelligence, why your League of Legends skills might land you an AI job, and the shocking mistakes enterprises make when deploying AI.

We discuss:

? How AI models really learn (hint: it's not just scraping the internet)

? Why data quality beats data quantity every time

? The Charlotte Hornets' revolutionary AI scouting system

? Whether robots will actually take your job (spoiler: probably not)

? The $14.8 billion Scale AI valuation and what it means

? Why Mark Andreessen thinks VCs won't be automated

Plus: Caspar reveals the #1 mistake companies make with AI deployment and why "AI-ifying" your current process is doomed to fail.

Subscribe to The Neuron newsletter: https://theneuron.ai

Connect with Caspar on LinkedIn: https://uk.linkedin.com/in/caspar-eliot-46b9a55a

Learn more about Invisible Technologies: https://invisibletech.ai?utm_source=neuron&utm_medium=podcast

Please check out the sponsor of this video, Warp.dev: https://warp.dev

So who is Invisible Technologies? In four words: they make AI work. Their platform cleans, labels, and structures company data so it?s ready for AI. It adapts models to each business and adds human expertise when needed ? the same approach used to improve models for over 80% of the world?s top AI companies, including Microsoft, AWS, and Cohere.Their successes span industries from supply chain automation for Swiss Gear, to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets. And get this: Invisible has been profitable for over half a decade, was ranked #2 fastest-growing AI company in 2024, and recently raised $100M to advance its platform technology.

Check them out at Invisible Technologies: https://invisibletech.ai?utm_source=neuron&utm_medium=podcast

From Adobe Max 2025 in Los Angeles, Corey and Grant sit down with Ely Greenfield, Adobe's Chief Technology Officer, to explore the philosophy behind Adobe's practical AI strategy.

Discover why the crowd went wild over AI renaming layers, how Adobe thinks about "additive not subtractive" AI, and where creative tools are heading next. Ely shares Adobe's vision for making AI a creative partner that enhances rather than replaces human artistry, and explains why the best AI features are often the most boring ones.

Topics covered include: the Photoshop AI Assistant, Harmonize for instant compositing, auto-masking in Premiere Pro, the Express conversational workflow, and Adobe's unique approach to balancing automation with creative control.

Read our Adobe Max coverage:

? Adobe Reinvents Creative Suite with AI

? Day 2 Keynote Recap

? NVIDIA's Beyond-GPUs Strategy

This episode was made possible by our sponsor, Clutch: https://clutch.co/resources/how-smbs-see-ai-crawlers?source=theneuron&utm_medium=referral&utm_campaign=newsletter_10-14-2025

Related resources:

? Adobe Max 2025 announcements: https://www.theneuron.ai/explainer-articles/adobe-goes-all-in-on-ai-max-2025-unleashes-creative-ai-arsenal-across-every-tool

? Day 2 Keynote and Sneaks recap: https://www.theneuron.ai/explainer-articles/adobe-max-day-2-the-storyteller-is-still-king-but-ai-is-their-new-superpower

? Check out Adobe Firefly: https://firefly.adobe.com/

? Project Graph demo: https://www.youtube.com/live/wQza2t9Qs64?t=10409s

Make sure to check out Clutch's new report on AI crawling for SMBS! https://clutch.co/resources/how-smbs-see-ai-crawlers?source=theneuron&utm_medium=referral&utm_campaign=newsletter_10-14-2025

Subscribe to The Neuron newsletter for daily AI news: https://theneuron.ai

Original article: https://www.theneuron.ai/explainer-articles/adobe-goes-all-in-on-ai-max-2025-unleashes-creative-ai-arsenal-across-every-tool

AI is changing what we need from our computers?but does that mean you need an "AI PC"? Corey and Grant sit down with Logan Lawler from Dell Technologies who leads Dell Pro Max AI solutions to decode what matters (and what doesn't) when buying or upgrading your next computer. From CPUs and GPUs to memory, NPUs, and traps to avoid, this episode is your practical roadmap for staying future-ready through the next five years of AI-powered work.

Dell Pro Max Workstations: https://www.dell.com/en-us/plcp/lp/dell-pro-max-pcs 

LM Studio LIVE tutorial: https://www.youtube.com/watch?v=Ai3sBeBdA1Y 

Kiwix Wikipedia Download: https://en.wikipedia.org/wiki/Kiwix 

One Trainer: https://github.com/Nerogar/OneTrainer

Jawset Postshot: https://www.jawset.com/

Subscribe to The Neuron newsletter: https://theneuron.ai

Check out the Reshaping Workflows Podcast: https://reshaping-workflows.simplecast.com/

Learn how to use NVIDIA's Nemotron open-source AI models with VP Kari Briski. We cover what Nemotron is, minimum hardware specs, the difference between Nano/Super/Ultra tiers, when to choose local vs cloud AI, and practical deployment patterns for businesses. Perfect for anyone wanting to run powerful AI locally with full control and privacy.

Resources mentioned:

NVIDIA Nemotron Models: https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/

Start prototyping for free: https://build.nvidia.com/explore/discover

Subscribe to The Neuron newsletter: https://theneuron.ai

Watch more AI interviews: https://www.youtube.com/@TheNeuronAI

AI search is fundamentally changing how people find information online, but it's also creating a Wild West of spam, manipulation, and brand impersonation. SEO expert Mark Williams-Cook joins us to discuss why he calls AI a "leaky bucket," how expired domains are gaming LLMs, and what the death of the link graph means for the future of search. We'll explore practical strategies for making your site visible to AI, the risks brands face from AI phishing, and whether SEO is truly dead or just evolving. Perfect for anyone who owns a website or runs a business.

Subscribe to The Neuron newsletter: https://theneuron.ai

Guest: Mark Williams-Cook - Director at Candour, Founder of AlsoAsked

Find Mark on LinkedIn: https://www.linkedin.com/in/markseo 

Search with Candour podcast: https://withcandour.co.uk/podcast 

Everyone's talking about the AI datacenter boom right now. Billion dollar deals here, hundred billion dollar deals there. Well, why do data centers matter? It turns out, AI inference (actually calling the AI and running it) is the hidden bottleneck slowing down every AI application you use (and new stuff yet to be released).

In this episode, Kwasi Ankomah from SambaNova Systems explains why running AI models efficiently matters more than you think, how their revolutionary chip architecture delivers 700+ tokens per second, and why AI agents are about to make this problem 10x worse.

? This episode is sponsored by Gladia's Solaria - the speech-to-text API built for real-world voice AI. With sub-270ms latency, 100+ languages supported, and 94% accuracy even in noisy environments, it's the backbone powering voice agents that actually work. Learn more at gladia.io/solaria

? Key Links:

? SambaNova Cloud: https://cloud.sambanova.ai

? Check out Solaria speech to text API: https://www.gladia.io/solaria

? Subscribe to The Neuron newsletter: https://theneuron.ai

? What You'll Learn:

? Why inference speed matters more than model size

? How SambaNova runs massive models on 90% less power

? Why AI agents use 10-20x more tokens

? The best open source models right now

? What to watch for in AI infrastructure

? CHAPTERS

Timecode - Chapter Title

0:00 - Intro

2:14 - What is AI Inference?

3:19 - Why Inference is the Real Challenge

9:18 - A message from our sponsor, Gladia Solaria

10:16 - The 95% ROI Problem Discussion

13:47 - SambaNova's Revolutionary Chip Architecture

15:19 - Running DeepSeek's 670B Parameter Models

18:11 - Developer Experience & Platform

21:26 - AI Agents and the Token Explosion

24:33 - Model Swapping and Cost Optimization

31:30 - Energy Efficiency 10kW vs 100kW

36:13 - Future of AI Models Bigger vs Smaller

39:24 - Best Open Source Models Right Now

46:01 - AI Infrastructure Next 12 Months

47:09 - Agents as Infrastructure

50:28 - Human-in-the-Loop and Trust

52:55 - Closing and Resources

Article Written by: Grant Harvey

Hosted by: Corey Noles and Grant Harvey

Guest: Kwasi Ankomah

Published by: Manique Santos

Edited by: Adrian Vallinan

In this special hands-on episode, Corey Noles and Grant Harvey dive into OpenAI's Sora 2 - the AI video platform that's part TikTok, part meme generator, and 100% chaos. Watch as they navigate the new social media-style interface, create ridiculous videos featuring Sam Altman at a Berlin techno rave filled with clowns, and discover why Sam has become the "Tom from MySpace" of AI-generated content.The hosts explore Sora 2's key features including the viral "cameo" system that lets you loan your likeness to other creators, the remix functionality, and the surprisingly robust prompt editing capabilities. They demonstrate the platform's strengths (incredibly fast generation, social features, creative possibilities) and weaknesses (no timeline editor for scrubbing through footage, occasional voice mismatches, server delays during peak times).Key takeaways include practical prompting tips for better results, how to set up and optimize your cameo preferences, and why being descriptive in your prompts makes all the difference. Grant and Corey also discuss the broader implications: Is this OpenAI's answer to TikTok? How does this fit into the AI landscape where every major player now has a social platform? And most importantly - why is everyone making Sam Altman breakdance?Whether you're AI-curious or a seasoned prompt engineer, you'll learn how to navigate Sora 2's interface, avoid common pitfalls, and maybe even create your own viral AI video. Plus, find out why Corey's "realistic physique was not okay on Sora" and had to optimize his cameo settings with ChatGPT's help.? CHAPTERSTimecode - Chapter Title0:00 - Introduction: What is Sora 21:03 - Sam Altman is the Tom from MySpace of AI1:57 - Mobile App Tour & Social Features3:42 - Remix Feature: Editing Sam's Bedtime4:12 - The Secret to Better Prompting6:40 - Profile Features & Your Drafts8:44 - Understanding Cameos10:40 - How to Set Up Your Cameo13:00 - Optimizing Cameo Preferences with ChatGPT15:05 - Live Demo of Creating A Video18:25 - Using the Edit Feature20:09 - First Video Results23:32 - Fixing a Bad Video26:49 - Finding & Following People30:33 - Exploring Trending Videos32:50 - Why OpenAI Built a Social Platform35:34 - Training Data Implications38:00 - Voice Input and Pro Prompting Tips40:02 - The First AI-Native Social Media45:43 - Final ThoughtResources: - Sora 2 launch: https://openai.com/index/sora-2/- Download the app https://apps.apple.com/us/app/sora-by-openai/id6744034028- Sora app on the web: https://sora.chatgpt.com/exploreP.S: First comment gets an invite code. Grant has 4 atm :)

In this episode, we're joined by Ahmed El-Kishky, research lead at OpenAI, to discuss their historic victory at the International Collegiate Programming Contest (ICPC) where their AI system solved all 12 problems, beating every human team in the world finals.

We dive into how they combined GPT-5 with experimental reasoning models, the dramatic last-minute solve, and what this means for the future of programming and AI-assisted science.

Ahmed shares behind-the-scenes stories from Azerbaijan, explains how AI learns to test its own code, and discusses OpenAI's path from this win to automating scientific discovery over months and years.

Subscribe to The Neuron: https://theneuron.ai

WisprFlow: https://wisprflow.ai/neuron

OpenAI: https://openai.com

Microsoft AI CEO Mustafa Suleyman (co-founder of DeepMind) joins The Neuron to discuss his provocative essay on "Seemingly Conscious AI" and why machines that mimic consciousness pose unprecedented risks - even when they're not actually alive. We explore how 700 million people are already using AI as life coaches, Microsoft's massive $208B revenue strategy for AI, and exclusive features like Copilot Vision that can see everything you see in real-time.Key topics:? Why AI consciousness is an illusion - and why that's dangerous ? Microsoft's 2 gigawatt datacenter expansion (2.5x Seattle's power usage)? MAI-1 Preview breaking into the top 10 models globally? The future of AI browsers and autonomous agents? Why granting AI rights could threaten humanitySubscribe to The Neuron newsletter (580,000+ readers): https://theneuron.aiResources mentioned:? Mustafa's essay "Seemingly Conscious AI Is Coming" https://mustafa-suleyman.ai/seemingly...? Try Copilot Vision: https://copilot.microsoft.com? Microsoft Edge AI features: https://www.microsoft.com/en-us/edge? MAI-1 Preview models: https://microsoft.ai/news/two-new-in-...Special thanks to today's sponsor, Wispr Flow: https://wisprflow.ai/neuron

Steve Brown's house burned down in a wildfire?and accidentally saved his life. When doctors missed his aggressive blood cancer for over a year, Steve built a swarm of AI agents that diagnosed it in minutes and helped design his treatment. Now he's turning that breakthrough into CureWise, a precision oncology platform helping cancer patients become better advocates. We explore agentic medicine, AI safety in healthcare, and how swarms of specialized AI agents are changing cancer care from diagnosis to treatment selection.

? Get on the CureWise waitlist: https://curewise.com

? Subscribe to The Neuron newsletter: https://theneuron.ai

Illia Polosukhin, co-author of Attention Is All You Need and co-founder of NEAR Protocol, believes today's centralized AI ecosystem is broken. In this episode, he explains why User-Owned AI is the path forward ? making systems private, verifiable, and aligned with users rather than corporations. We explore confidential computing, interoperable AI agents, and what a more sustainable AI future might really look like.

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Thomson Reuters just launched Deep Research?an AI system that doesn't just search legal databases, but plans and strategizes like an experienced attorney. In this episode, we explore how one of the world's largest legal research companies is using AI agents to transform how lawyers work, the challenges of building AI for high-stakes legal decisions, and what this means for the future of knowledge work. CTO Joel Hron shares insights from testing with 1,200+ customers, tackling hallucination risks in legal settings, and building professional-grade AI systems.

Resources mentioned: Thomson Reuters Deep Research: https://www.prnewswire.com/news-releases/thomson-reuters-launches-cocounsel-legal-transforming-legal-work-with-agentic-ai-and-deep-research-302521761.html 

Westlaw & KeyCite: https://legal.thomsonreuters.com/en/products/westlaw/keycite 

Claude Code for development: https://www.anthropic.com/claude-code 

LinkedIn: Joel HronThomson Reuters Medium blog: https://medium.com/tr-labs-ml-engineering-blog 

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Today we go deeper on Google's AI stack with Logan Kilpatrick: what AI Studio is great at, how it fits with Firebase/Colab/Gemini CLI/Jules, and where "thinking" models make sense. We cover real-world workflows?from game prototyping and screen-share assistance to legal/privacy basics and on-device micro-apps. Logan shares his insights on vibe coding, the future of AI development, and Google's open-source strategy with Gemma models.

Resources mentioned:

Google AI Studio: https://aistudio.google.com/

Gemini CLI: https://github.com/google-gemini/gemini-cli

Kaggle Game Arena: https://www.kaggle.com/competitions

Google Firebase: https://firebase.google.com/

Gemma models: https://ai.google.dev/gemma

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What does it take to steer a 3,500-person company into the age of generative AI? ZoomInfo founder and CEO Henry Schuck joins us to unpack the company's journey from data powerhouse to AI-first GTM platform, the cultural shifts that enabled it, and the hard-won lessons any leader can borrow. We explore how they reduced teams from 26 to 2 people using AI agents, why 2/3 of employees now use AI daily, and the critical role of data infrastructure in AI success.

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Learn more about ZoomInfo: https://www.zoominfo.com

What does "AI governance" really entail, and why does it matter right now? Credo AI founder Navrina Singh joins The Neuron to unpack risk buckets, Model Trust Scores, and the regulatory zig-zag between the EU and the U.S.?so you can move fast without crashing the car. We dive into open source safety, agent governance, and test OpenAI's brand new open source model live.

Learn more about AI governance: https://credo.ai/resources

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A lot of people aren't sure whether they should just chat with an AI model, craft a structured prompt, spin up a project, or unleash a full-blown agent. In this episode, we break down the differences between these approaches and share a practical decision-making framework. We'll show how simple prompts excel for quick, isolated tasks, why structured prompts improve clarity and focus, when a project (workflow) is better for predictable, repeatable processes, and where autonomous agents shine for dynamic, open-ended problems. Along the way we'll demo real examples, share tips for avoiding unnecessary complexity, and help listeners decide which tool fits their use case.

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In this hands-on episode, Corey and Grant attempt to build three different AI apps in one hour using Google AI Studio - with zero coding experience required. They create an Inbox Zero email organizer, a meme generator that roasts their photos, and a spontaneous adventure planner with interactive maps. Watch as they navigate errors, discover workarounds, and prove that anyone can build functional AI apps without being a developer.

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Original article: https://www.theneuron.ai/newsletter/googles-ai-makes-you-apps

Read more: https://www.theneuron.ai/explainer-articles/how-to-build-an-ai-agent-part-one-testing-googles-firebase-studio-ai-agent-builder

Google AI Studio:? https://aistudio.google.com?

NoCodeMBA Tutorial: https://youtu.be/ANth52yyr9U?si=L9iT1-eYgB8nOfrg

Alternative builders mentioned:

- Lovable:? https://lovable.dev?

- Claude Artifacts:? https://claude.ai?

- V0 by Vercel:? https://v0.dev?

- Bolt.new:? https://bolt.new?

OpenAI just dropped ChatGPT Agent, and we test it LIVE for the first time. Watch as we put this "true" AI agent through its paces - from finding the perfect Gibson Les Paul to building competitive intelligence reports. We explore what makes this different from Zapier-style automation, demonstrate real-world use cases, and discuss why this might be the beginning of America's first super app. Plus: can it actually convince Corey's wife he needs a new guitar?

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Original article: https://www.theneuron.ai/newsletter/openais-new-agent-is-here

Read More: https://www.theneuron.ai/explainer-articles/how-to-build-your-own-ai-agent-without-being-a-pro-coder

https://www.theneuron.ai/newsletter/operator-book-me-some-clients

ChatGPT Agent: https://openai.com/index/introducing-chatgpt-agent/

N8N: https://n8n.io/

Headlines scream that AI is "breaking the classroom," but is the story that simple? In this episode we explore the real cracks in today's education system, how AI sometimes widens them, and?more importantly?how the same technology could personalize learning, free teachers to teach, and shift schools from rote memorization to true mastery. We discuss the UCLA "CheatGPT" controversy, MIT's brain study, Alpha School's 2-hour learning model, and OpenAI's new $10M teacher training initiative.

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WTF is going on with AI and education: https://www.theneuron.ai/explainer-articles/wtf-is-going-on-with-ai-and-education

One Useful Thing (Ethan Mollick) Post-apocalyptic education: 

https://www.oneusefulthing.org/p/post-apocalyptic-education 

MIT study: https://www.media.mit.edu/publications/your-brain-on-chatgpt/ 

Ethan Mollick again, ?Against brain damage?: 

https://www.oneusefulthing.org/p/against-brain-damage  

OpenAI working with teachers union: https://openai.com/global-affairs/aft/ 

Make it Stick book: https://www.makeitstick.com/

Will AI turbocharge our output?or erode our standards in the rush to automate? In this episode, strategist Andreas Welsch (ex-SAP, author of The AI Leadership Handbook) joins Corey Noles and Grant Harvey to weigh the promise of higher productivity against the peril of slipping quality. Expect plain-language insights on agentic AI, governance that scales, and the human skills and metrics that reveal whether AI is lifting the bar?or lowering it.

Guest: Andreas Welsch LinkedIn: https://www.linkedin.com/in/andreasmwelsch

AI Leadership Handbook: https://www.aileadershiphandbook.com/order

What's the BUZZ? Podcast: https://www.intelligence-briefing.com/podcast

The AI MEMO Newsletter: https://www.intelligence-briefing.com/newsletter

Work with Andreas (AI strategy, workshops, training): https://www.intelligence-briefing.com

OWASP Top 10 LLMs: https://owasp.org/www-project-top-10-for-large-language-model-applications/

There are no new ideas in AI, only new datasets: https://blog.jxmo.io/p/there-are-no-new-ideas-in-ai-only

N8N to start automating your own tasks (not a promo; this is just the best tool for the job): https://n8n.io/ or https://n8n.io/workflows for template workflows to try.

The Neuron Newsletter: https://www.theneuron.ai

In Ep 3 we explore DeepSeek's open-source R-series models that claim GPT-4-level performance at a fraction of the cost. We unpack whether you can realistically run DeepSeek on a laptop, where it beats (and lags) OpenAI, and the serious security implications of using Chinese AI services. Listeners will learn the economics, hardware realities, and safe alternatives for using these powerful open-source models.

How to pick the best AI for what you actually need:

https://www.theneuron.ai/newsletter/how-to-pick-the-best-ai-model-for-what-you-actually-need

Artificial Analysis to compare top AI models:

https://artificialanalysis.ai/

Previous coverage of DeepSeek:

https://www.theneuron.ai/newsletter/deepseek-returns

https://www.theneuron.ai/newsletter/10-wild-deepseek-demos

https://www.theneuron.ai/explainer-articles/deepseek-r2-could-crush-ai-economics-with-97-lower-costs-than-gpt-4

U.S. Military allegations against DeepSeek:

https://www.reuters.com/world/china/deepseek-aids-chinas-military-evaded-export-controls-us-official-says-2025-06-23/

ChatGPT data privacy concerns:

https://www.theneuron.ai/explainer-articles/your-chatgpt-logs-are-no-longer-private-and-everyones-freaking-out

OpenAI?s response to NYT lawsuit demands:

https://openai.com/index/response-to-nyt-data-demands/

How to run Open source models:

Go to Hugging Face for the models: https://huggingface.co/

Use Ollama or LM Studio (our recommendation) to run the model locally:

https://ollama.com/

https://lmstudio.ai/

In Ep 2 we ask: "Panic or Progress? Reading Between the Lines of AI Safety Tests." We unpack the recent Claude Opus 4 "blackmail" test result, OpenAI's new transparency pledge, and why safety evaluations sometimes sound scarier than they are. Listeners will leave with a clear framework for interpreting headline-grabbing safety reports?and practical advice on when to worry, when to wait, and how to separate red flags from red herrings.

Will AI really erase half of all white-collar jobs, as Anthropic CEO Dario Amodei warns? We unpack the numbers, the hype, and the hidden opportunities, then hand the mic to Microsoft's Alexia Cambon for fresh research on how to thrive in an AI-saturated workday. Listeners will learn how roles are shifting, which skills stay scarce, and concrete moves to keep their careers future-proof.

After a long wait, Apple is finally in the game with AI. They?re launching Apple Intelligence with MacOS Sequoia and iOS 18. Pete breaks down some top features and how our devices will change moving forward.

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The US government is opening up antitrust inquiries into the likes of Nvidia, OpenAI and Microsoft. Who's leading the charge, and what could they be looking at?

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Former OpenAI researcher Leopold Aschenbrenner has released a series of essays talking about how he sees AI playing out and what we should all do about it. Pete digs into his extremely impressive background and his arguments around why we?re about to get AGI.

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Nvidia CEO Jensen Huang has announced their next line of products called Rubin as Nvidia races to build what he calls ?intelligence factories?. Pete breaks down the big picture and what it all means for us.

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Anthropic did something no other AI lab has done: cracked the code on what?s happening while an AI model is working. Pete breaks down the latest research and what it means for steering AI models.

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Microsoft?s launch event for Copilot+ PCs was only available to press and content creators. Pete?s taking you through the launch, what stands out and what to look for next.

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OpenAI Chief Scientist Ilya Sutskever and Head of Alignment Jan Leike have left the company, with the latter citing concerns around OpenAI?s approach to building safe AI systems. Pete gives you the 101 on the debate at hand, the history of this debate at OpenAI and what to expect moving forward.

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Google I/O 2024 was a laundry list of AI launches, with Google trying their best to position themselves as the leading company in AI. Pete breaks down the key parts of their long keynotes and how to understand Google?s approach to AI moving forward.

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In a surprise launch, OpenAI dropped GPT-4 Omni, their new leading model. They also made a bunch of paid features in ChatGPT free and announced a new desktop app. Pete breaks down what you should know and what this says about AI.

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OpenAI releases its Model Spec, which tries to define how AI models should behave. Some highlights and examples, along with some more existential questions.

Next, you know what Gen Z ought to really love about AI? Customer support. The patterns in their behavior and some unexpected ways that AI is impacting the field.

Finally, we?ve heard so many times that OpenAI is partnering with media companies. Now, we finally know what?s behind those deals.

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