The Grittiest Conversations of 2025: AI, Business & Beyond
In this recap episode, we highlight the best moments from our 2025 interviews and reflect on the ideas that defined the year.
Featuring:
David Rubenstein (co-founder of Carlyle)
Yamini Rangan (CEO of HubSpot)
Ben Chestnut (co-founder of Mailchimp)
Winston Weinberg (co-founder and CEO of Harvey)
Garrett Lord (co-founder of Handshake)
Aidan Gomez (co-founder and CEO of Cohere)
Michelle Zatlyn (co-founder of Cloudflare)
Evan Spiegel (co-founder and CEO of Snap)
Connect with Joubin
X: https://x.com/Joubinmir
LinkedIn: https://www.linkedin.com/in/joubin-mirzadegan-66186854/
Email: grit@kleinerperkins.com
Follow on LinkedIn:
https://www.linkedin.com/company/kpgrit
Follow on X:
https://x.com/KPGrit
Learn more about Kleiner Perkins: https://www.kleinerperkins.com/
Synthetic Data and the Future of AI | Cohere CEO Aidan Gomez
How do companies like Salesforce and Dell scale intelligence across every cloud?
Aidan Gomez, co-founder and CEO of Cohere, explains how they’re building AI that works across all enterprise systems and deploys anywhere, giving companies true flexibility and security.
He joins Joubin Mirzadegan for a wide-ranging conversation on why synthetic data went from dismissed to indispensable, and how the race among AI labs is really unfolding.
Guest: Aidan Gomez, co-founder and CEO of Cohere
Connect with Aidan:
X
LinkedIn
Connect with Joubin:
X
LinkedIn
Email: grit@kleinerperkins.com
Learn more about Kleiner Perkins
Model Plateaus and Enterprise AI Adoption with Cohere's Aidan Gomez
In this episode of No Priors, Sarah is joined by Aidan Gomez, cofounder and CEO of Cohere. Aidan reflects on his journey to co-authoring the groundbreaking 2017 paper, “Attention is All You Need,” during his internship, and shares his motivations for building Cohere, which delivers AI-powered language models and solutions for businesses. The discussion explores the current state of enterprise AI adoption and Aidan’s advice for companies navigating the build vs. buy decision for AI tools. They also examine the drivers behind the flattening of model improvements and discuss where large language models (LLMs) fall short for predictive tasks. The conversation explores what the market has yet to account for in the rapidly evolving AI ecosystem, as well as Aidan’s personal perspectives on AGI—what it might look like and when it could arrive.
Sign up for new podcasts every week. Email feedback to show@no-priors.com
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AidanGomez
Show Notes:
0:00 Introduction
0:36 Co-authoring “Attention is all you need”
2:27 Leaving Google and founding Cohere
4:04 Cohere’s mission and models
6:15 Pitfalls of current AI
8:14 How enterprises are deploying AI today
10:58 Build vs. buy strategy for AI tools
14:37 Barriers to enterprise adoption
20:04 Which types of companies should pretrain models?
24:25 Addressing flaws in open-source models
25:12 Current and expected progress in scaling laws
29:54 Advances in multi-step problem solving and reasoning
32:29 Key drivers behind the flattening curve of model improvements
36:25 Exploring AGI
39:59 Limitations of LLMs
42:10 What the market has mispriced
The Next Gen AI Models: Reliable, Consistent, Trustworthy — With Aidan Gomez
Aidan Gomez is the co-author of the "Attention Is All You Need" paper that launched the AI revolution and CEO of Cohere, an enterprise AI company. Gomez joins Big Technology to discuss the myths, facts, and realities of today's AI landscape. Tune in to hear why the real value of AI isn't in flashy consumer apps but in automating crucial back-office processes that could save businesses billions. We also cover the truth about AI capabilities, the likelihood of AGI, synthetic data training, and whether an intelligence explosion is possible. Hit play for a refreshingly grounded discussion about where AI is actually making an impact, from one of the field's pioneering voices.
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20VC: Chips, Models or Applications; Where is the Value in AI | Is Compute the Answer to All Model Performance Questions | Why Open AI Shelved AGI & Is There Any Value in Models with OpenAI Price Dumping with Aidan, Gomez, Co-Founder @ Cohere
Aidan Gomez is the Co-founder & CEO at Cohere, the leading AI platform for enterprise, having raised over $1BN from some of the best with their last round pricing the company at a whopping $5.5BN. Prior to Cohere, Aidan co-authored the paper "Attention is All You Need," which introduced the groundbreaking Transformer architecture. He also collaborated with a number of AI luminaries, including Geoffrey Hinton and Jeff Dean, during his time at Google Brain, where the team focused their efforts on large-scale machine learning.
In Today's Episode with Aidan Gomez We Discuss:
1. Compute vs Data: What is the Bottleneck:
Does Aidan believe that more compute will result in an equal increase in performance?
How much longer do we have before it becomes a case of diminishing returns?
What does Aidan mean when he says "he has changed his mind massively on the role of data"? What did he believe? How has it changed?
2. The Value of the Model:
Given the demand for chips, the consumer need for applications, how does Aidan think about the inherent value of models today? Will any value accrue at the model layer?
How does Aidan analyze the price dumping that OpenAI are doing? Is it a race to the bottom on price?
Why does Aidan believe that "there is no value in last year's model"?
Given all of this, is it possible to be an independent model provider without being owned by an incumbent who has a cloud business that acts as a cash cow for the model business?
3. Enterprise AI: It is Changing So Fast:
What are the biggest concerns for the world's largest enterprises on adopting AI?
Are we still in the experimental budget phase for enterprises? What is causing them to move from experimental budget to core budget today?
Are we going to see a mass transition back from Cloud to On Prem with the largest enterprises not willing to let independent companies train with their data in the cloud?
What does AI not do today that will be a gamechanger for the enterprise in 3-5 years?
4. The Wider World: Remote Work, Downfall of Europe and Relationships:
Given humans spending more and more time talking to models, how does Aidan reflect on the idea of his children spending more time with models than people? Does he want that world?
Why does Aidan believe that Europe is challenged immensely? How does the UK differ to Europe?
Why does Aidan believe that remote work is just not nearly as productive as in person?
Aiden Gomez - CEO of Cohere (AI's 'Inner Monologue' – Crucial for Reasoning)
Aidan Gomez, CEO of Cohere, reveals how they're tackling AI hallucinations and improving reasoning abilities. He also explains why Cohere doesn't use any output from GPT-4 for training their models.
Aidan shares his personal insights into the world of AI and LLMs and Cohere's unique approach to solving real-world business problems, and how their models are set apart from the competition. Aidan reveals how they are making major strides in AI technology, discussing everything from last mile customer engineering to the robustness of prompts and future architectures.
He also touches on the broader implications of AI for society, including potential risks and the role of regulation. He discusses Cohere's guiding principles and the health the of startup scene. With a particular focus on enterprise applications. Aidan provides a rare look into the internal workings of Cohere and their vision for driving productivity and innovation.
https://cohere.com/
https://x.com/aidangomez
Check out Cohere's amazing new Command R* models here
https://cohere.com/command
Disclaimer: This is the second video from our Cohere partnership. We were not told what to say in the interview, and didn't edit anything out from the interview.
AI will make money sooner than you think, says Cohere CEO Aidan Gomez
Cohere is one of the buzziest AI startups around right now. It's not making consumer products; it's focused on the enterprise market and making AI products for big companies. And there's a huge tension there: up until recently, computers have been deterministic. If you give computers a certain input, you usually know exactly what output you’re going to get. There’s a logic to it. But if we all start talking to computers with human language and getting human language back, well, human language is messy. And that makes the entire process of knowing what to put in and what exactly we’re going to get out of our computers different than it ever has been before.
Links:
Attention is all you need
On the Dangers of Stochastic Parrots
Introducing the AI Mirror Test, which very smart people keep failing | The Verge
AI isn’t close to becoming sentient | The Conversation
These are Microsoft’s Bing AI secret rules and why it says it’s named Sydney | The Verge
‘Godfather of AI’ quits Google with regrets and fears about his life’s work | The Verge
Microsoft CTO Kevin Scott on Bing’s quest to beat Google | The Verge
Top AI researchers and CEOs warn against ‘risk of extinction’ | The Verge
Google Zero is here — now what? | The Verge
Cara grew from 40k to 650k in a week because artists are fed up with Meta’s AI policies | TechCrunch
How AI copyright lawsuits could make the whole industry go extinct | The Verge
Transcript: https://www.theverge.com/e/23937899
Credits:
Decoder is a production of The Verge and part of the Vox Media Podcast Network.
Our producers are Kate Cox and Nick Statt. Our editor is Callie Wright. Our supervising producer is Liam James.
The Decoder music is by Breakmaster Cylinder.
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#123 Aidan Gomez: How AI Language Models Will Shape The Future
Welcome to Eye on AI, the podcast that keeps you informed about the latest trends, obstacles, and possibilities in the realm of artificial intelligence. In this episode, we have the privilege of engaging in a thought-provoking discussion with Aidan Gomez, an exceptional AI developer and co-founder of Cohere. Aidan's passion lies in enhancing the efficiency of massive neural networks and effectively deploying them in the real world. Drawing from his vast experience, which includes leading a team of researchers at For.ai and conducting groundbreaking research at Google Brain, Aidan provides us with unique insights and anecdotes that shed light on the AI landscape. During our conversation, Aidan explains his collaboration with the legendary Geoffrey Hinton and their remarkable project at Google Brain. We delve into the intricate architecture of AI systems, demystifying the construction of the transformative transformer algorithm. Aidan generously shares his knowledge on the creation of attention within these models and the complexities of scaling such systems. As we explore the fascinating domain of language models, Aidan discusses their learning process, bridging the gap between code and data. We uncover the immense potential of these models to suggest other large-scale counterparts. We gain invaluable insights into Aidan's journey as a co-founder of Cohere, an innovative platform revolutionizing the utilization of language technology. Tune in to Eye on AI now to immerse yourself in a captivating conversation that will expand your understanding of this ever-develop field. (00:00) Preview (00:33) Introduction & sponsorship (02:00) Aidan's background with machine learning & AI (05:10) Geoffrey Hinton & Aidan Gomez working together (07:55) Aidan Gomez & Google Brain's project (12:53) Aidan's role in building AI architecture (15:25) How the transformer algorithm is built (18:25) How do you create attention? (20:40) How do you scale the model? (25:10) How language models learn from code and data (29:55) Did you know the potential of the project? (34:15) Can LLMs suggest other large models? (36:45) How Aidan Gomez started Cohere (41:10) How do people use Cohere? (46:50) Examples of language technology models (48:40) How Cohere handles hallucinations (52:53) The dangers of AI Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Scaling LLMs and Accelerating Adoption with Aidan Gomez at Cohere
On this episode, we’re joined by Aidan Gomez, Co-Founder and CEO at Cohere. Cohere develops and releases a range of innovative AI-powered tools and solutions for a variety of NLP use cases.
We discuss:
- What “attention” means in the context of ML.
- Aidan’s role in the “Attention Is All You Need” paper.
- What state-space models (SSMs) are, and how they could be an alternative to transformers.
- What it means for an ML architecture to saturate compute.
- Details around data constraints for when LLMs scale.
- Challenges of measuring LLM performance.
- How Cohere is positioned within the LLM development space.
- Insights around scaling down an LLM into a more domain-specific one.
- Concerns around synthetic content and AI changing public discourse.
- The importance of raising money at healthy milestones for AI development.
Aidan Gomez - https://www.linkedin.com/in/aidangomez/
Cohere - https://www.linkedin.com/company/cohere-ai/
Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.
Resources:
- https://cohere.ai/
- “Attention Is All You Need”
#OCR #DeepLearning #AI #Modeling #ML
Aidan Gomez of Cohere: building instructable agents
Aidan Gomez, co-founder and CEO of Cohere joins Host Pieter Abbeel to discuss transformers, large language models, command and instruct models, prompt engineering, and LLMs competitive landscape.
Subscribe to the Robot Brains Podcast today | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast and Twitter @therobotbrains.
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#80 AIDAN GOMEZ [CEO Cohere] - Language as Software
We had a conversation with Aidan Gomez, the CEO of language-based AI platform Cohere. Cohere is a startup which uses artificial intelligence to help users build the next generation of language-based applications. It's headquartered in Toronto. The company has raised $175 million in funding so far.
Language may well become a key new substrate for software building, both in its representation and how we build the software. It may democratise software building so that more people can build software, and we can build new types of software. Aidan and I discuss this in detail in this episode of MLST.
Check out Cohere -- https://dashboard.cohere.ai/welcome/register?utm_source=influencer&utm_medium=social&utm_campaign=mlst
Support us!
https://www.patreon.com/mlst
YT version: https://youtu.be/ooBt_di8DLs
TOC:
[00:00:00] Aidan Gomez intro
[00:02:12] What's it like being a CEO?
[00:02:52] Transformers
[00:09:33] Deepmind Chomsky Hierarchy
[00:14:58] Cohere roadmap
[00:18:18] Friction using LLMs for startups
[00:25:31] How different from OpenAI / GPT-3
[00:29:31] Engineering questions on Cohere
[00:35:13] Francois Chollet says that LLMs are like databases
[00:38:34] Next frontier of language models
[00:42:04] Different modes of understanding in LLMs
[00:47:04] LLMs are the new extended mind
[00:50:03] Is language the next interface, and why might that be bad?
References:
[Balestriero] Spine theory of NNs
https://proceedings.mlr.press/v80/balestriero18b/balestriero18b.pdf
[Delétang et al] Neural Networks and the Chomsky Hierarchy
https://arxiv.org/abs/2207.02098
[Fodor, Pylyshyn] Connectionism and Cognitive Architecture: A Critical Analysis
https://ruccs.rutgers.edu/images/personal-zenon-pylyshyn/docs/jaf.pdf
[Chalmers, Clark] The extended mind
https://icds.uoregon.edu/wp-content/uploads/2014/06/Clark-and-Chalmers-The-Extended-Mind.pdf
[Melanie Mitchell et al] The Debate Over Understanding in AI's Large Language Models
https://arxiv.org/abs/2210.13966
[Jay Alammar]
Illustrated stable diffusion
https://jalammar.github.io/illustrated-stable-diffusion/
Illustrated transformer
https://jalammar.github.io/illustrated-transformer/
https://www.youtube.com/channel/UCmOwsoHty5PrmE-3QhUBfPQ
[Sandra Kublik] (works at Cohere!)
https://www.youtube.com/channel/UCjG6QzmabZrBEeGh3vi-wDQ
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