The Deep View: Conversations – Détails, épisodes et analyse

AI could change the way we remember, and the way we pay attention. 

In this episode of The Deep View: Conversations, Editor-in-Chief Jason Hiner sits down with Bobak Tavangar, CEO of Brilliant Labs, one of the most intriguing startups in AI hardware today. 

While trillion-dollar giants like Meta and Google race to define the future of AI glasses, Brilliant Labs is taking a radically different path: building in public, going open-source with both software and hardware, and centering their next product, the Halo glasses, around something deeply human. 

The focus? A conversational AI agent for your long-term memories and conversations. 

This isn’t just about smarter wearables. It’s about a bigger idea: 

+ Can AI help us be more present, not less? 
+ Could technology support memory, reflection, and intention instead of distraction? 
+ What does privacy look like when AI can recall your life? 

Jason and Bobak also explore: 

+ What he learned during his time at Apple 
+ Why AI hardware is one of the hardest frontiers in tech 
+ The challenging process of finding a co-founder 
+ Bobak’s philosophy on communicating on social media with purpose, not hype 

Bobak is one of the most thoughtful founders in the AI space, consistently elevating the conversation beyond features and into questions of values, agency, and human experience. 

If you care about where AI, wearables, memory, and attention intersect, this is a conversation you don’t want to miss. 

Subscribe to the podcast for more unique conversations with the brightest minds solving the biggest challenges in AI. 

And don't miss The Deep View daily newsletter. We don’t just cover AI — we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights that keep our audience ahead of the curve and help them put AI to work every day: https://subscribe.thedeepview.com/ 

How do you make AI inference affordable enough to deliver real ROI in the enterprise? 

In this episode of The Deep View Conversations, we talk with Rob May, founder and CEO of Neurometric AI, to break down one of the most urgent challenges in AI today: the soaring cost of inference, and how to bring it down without sacrificing performance. 

Today's AI is increasingly powerful, but it’s also expensive. For enterprises to see real returns, inference costs have to drop dramatically. Neurometric believes the answer lies in "thinking algorithms" paired with small, specialized models and workload-specific optimization. This approach can significantly reduce costs while often improving accuracy and efficiency. Rob walks through how this works in practice and why it matters as AI moves from experimentation to scaled deployment. 

We also talk about:
+ Why the current AI boom pulled Rob back into operating a startup after multiple exits and a move into investing 
+ How founders should think about AI infrastructure, efficiency, and long-term economics 
+ What startup leaders can do to get journalists to pay attention — and a pivotal early-career conversation that led to coverage which changed the trajectory of one of Rob’s companies 

If you’re building, deploying, or investing in AI and wrestling with the economics of inference, this conversation offers a clear, practical perspective on what comes next. 

Thank you to our sponsor, Deel, an AI-native platform for HR, IT, and payroll. Hire, manage, pay, and equip anyone, anywhere. https://www.deel.com/deepview 

Subscribe to the podcast for more unique conversations with the brightest minds solving the biggest challenges in AI. 

And don't miss The Deep View daily newsletter. We don’t just cover AI — we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights that keep our audience ahead of the curve and help them put AI to work every day: https://subscribe.thedeepview.com/ 

I sat down with Brad Zamft, the co-founder and CEO of Heritable Agriculture, to take a deep dive into all the science (both biology and computer science) behind the effort to program plants, why it’s needed and what impacts it might have. 

Episode links: 

• Heritable Agriculture: https://heritable.ag/
• Heritable goes after indoor strawberries: https://heritable.ag/heritable-strawberries 
• The sustainability threat of farming: https://vlsci.com/blog/top-issues-in-agriculture-2024/ ; https://www.epa.gov/climateimpacts/climate-change-impacts-agriculture-and-food-supply
• The risks of monoculture and monocropping: https://foodrevolution.org/blog/monocropping-monoculture/
• The promise of regenerative agriculture: https://theclimatecenter.org/our-work/research/report-the-promise-of-regenerative-agriculture/
• Farming resiliency in the face of climate change: https://sustainability.mit.edu/article/making-agriculture-more-resilient-climate-change

Outline

0:00 – Intro

2:18 – Brad’s journey to Heritable Agriculture

9:29 – Why we need programmable plants

14:23 – Challenges of biology

19:38 – Validating the models

22:14 – How does this all physically work? 

31:05 – The challenge of adjusting 2 billion years of evolutionary success

34:48 – The risks of AI cracking plant DNA

39:50 – Regenerative Agriculture and tuning for resiliency in the face of climate change

47:53 – How farmers view the approach

51:59 – Tree adjustments

56:28 – The future outlook

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Nada Sanders, a distinguished professor of supply chain management at Northeastern University, to better understand the impact that tariffs and a trade war could have on the business and field of AI. 

Episode Links: 

• The semiconductor pipeline: https://datacenterpost.com/ais-hardware-hunger-the-global-semiconductor-supply-chain-under-pressure/
• The latest on the tariffs and trade war: https://www.bbc.com/news/articles/c62z54gwd22o
• Nvidia’s US push: https://www.thedeepview.co/p/nvidia-to-produce-500-billion-worth-of-supercomputers-in-the-u-s-for-the-first-time
• Apple’s US push: https://www.apple.com/newsroom/2025/02/apple-will-spend-more-than-500-billion-usd-in-the-us-over-the-next-four-years/

Outline: 
0:00 – Intro 
4:09 – The vulnerability of the AI supply chain
19:13 – Is it realistic to bring production back to the US? 
27:31 – Innovation could plateau 
34:04 – The challenge of navigating uncertainty, even if the tariffs come off

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Eric Sydell, the founder and CEO of Vero AI, to break down the challenges of oversight, governance and compliance — and the techno-utopia on the horizon — and the ways in which AI can help, hurt, and generally, disrupt everything. 

Episode links: 

• Ethan Molick: https://www.linkedin.com/posts/emollick_if-ai-development-stopped-this-week-we-would-activity-7272747981752176640-nTKX/
• What even is AI: https://www.ibm.com/think/topics/artificial-intelligence
• Sam Altman says we must regulate AI: https://www.thedeepview.co/p/paris-ai-summit-the-smoke-and-mirrors-of-governance
• EU AI Act: https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
• Challenge of AI regulation: https://www.thedeepview.co/p/report-the-misguided-race-to-regulation
• Nurses and AI: https://www.thedeepview.co/p/current-harms-and-the-real-world-impacts-of-algorithmic-decision-making
• Preslav Nakov fact-checking LLMs: https://aclanthology.org/2024.findings-acl.558/

Outline

0:00 – Intro

2:28 – AI for compliance
4:43 – Overcoming reliability problems

10:16 – Toys VS tools
15:54 – Keeping up with the rate of ‘progress’

22:03 – The challenge of regulation: 

28:55 – Balancing AI with the bottom line

34:38 – The problem with ‘Abundance’

43:11 – How to get the good without all the bad

51:17 – Running to and running from technology

55:02 – Looking for optimism

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Stefan Leichenauer, SandboxAQ's VP of Engineering, to break down the ways in which he’s bringing the two technologies together. 

Check out our breakdown of quantum computing: https://youtu.be/-umrjwGFTRw

Episode links: 

• Quantum sensing: https://www.baesystems.com/en-us/definition/what-is-quantum-sensing
• Sandbox LQMs: https://www.sandboxaq.com/
• Quantum computers: https://www.ibm.com/think/topics/quantum-computing
• Sandbox drug discovery: https://www.sandboxaq.com/solutions/aqbiosim
• Sandbox materials generation: https://www.sandboxaq.com/post/building-better-batteries-with-lqms

Outline

0:00 – Intro

1:36 – How does Sandbox leverage Quantum?

4:35 – What makes a sensor a Quantum sensor? 
8:00 – What would a Quantum computer need to do to be ready for use? 

11:30 – What reliable Quantum computers mean for Sandbox and AI 
15:18 – Sandbox’s Large Quantitative Models 

27:52 – Specialist systems VS generalist systems
35:41 – Black Boxes and LQMS 

37:45 – LQMs and hallucination
41:50 – LQMs and drug discovery
50:00 – The cost associated with LQMs

53:37 – LQMs and materials generation
56:55 – Future outlook  

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

At HumanX, I sat down with Dr. David Cox — the VP for AI models at IBM Research and the IBM Director of the MIT-IBM Watson AI Lab — to dissect those complex, nuanced differences between biological brains and the artificial neural networks behind LLMs, and how it all relates to the pursuit of AGI. 

Episode links: 

• Neural networks: https://www.ibm.com/think/topics/neural-networks
• Convolutional neural networks: https://www.geeksforgeeks.org/introduction-convolution-neural-network/
• Everything we know about the human brain: https://ny.pbslearningmedia.org/resource/stn15.sci.neuro.colbrain/what-we-still-dont-know-about-the-brain/
• MIT Flywire diagram: https://www.nature.com/immersive/d42859-024-00053-4/index.html
• Language and thought are not the same thing:https://mcgovern.mit.edu/2019/05/02/ask-the-brain-can-we-think-without-language/
• Decoding internal monologues: https://pmc.ncbi.nlm.nih.gov/articles/PMC7252628/
• Anthropic’s anthropomorphization: https://www.thedeepview.co/p/the-public-health-crisis-of-ai
• AGI and existential risk: https://www.thedeepview.co/p/the-nobel-prize-and-the-mainstreaming-of-ai-s-x-risk#4

Outline

0:00 — Intro

2:07 — What is intelligence? 
4:36 — How AI boosts our understanding of the brain
8:09 — The differences between neurons and artificial neurons
12:13 — How much do we know — and not know — about biological brains
15:49 — LLMs and the illusion of intelligence
20:07 — Language vs Thought

23:37 — Should we train models not to use the first person? 
28:04 — The pursuit of AGI 

34:26 — IBM’s model approach
35:49 — AGI is a distraction
40:02 — How big a deal is AI? 
45:26 — The risk of the AI brain drain

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Igor Jablokov, the founder and chairman of Pryon, to talk about the ways in which the field of AI has grown and changed, and where it might go from here. Igor worked as a program director at IBM, developing an early iteration of IBM Watson, before he struck out on his own. His first startup, Yap, was later acquired by Amazon, where it evolved into Alexa. 

Episode Links: 

• Self-driving progress: https://www.thedeepview.co/p/progress-predictions-2025-robots-avs-and-technical-advancements
• Reuters copyright lawsuit: https://www.thedeepview.co/p/study-most-people-can-t-identify-deepfakes
• Musk v Altman: https://www.entrepreneur.com/business-news/musk-v-altman-billionaires-attorneys-face-off-in-court/486647
• Chatbots, mental health and Character AI: https://www.thedeepview.co/p/i-downloaded-character-ai-it-s-profoundly-disturbing
• The AI bubble: https://www.thedeepview.co/p/what-the-trade-war-might-mean-for-ai
• The power struggle of AGI: https://www.thedeepview.co/p/how-big-tech-is-using-the-ai-race-and-the-specter-of-agi-to-cement-its-power-agi-openai-google
• AI in the enterprise: https://www.thedeepview.co/p/humanx-ai-s-inflection-point-conference-artifcial-intelligence

Outline: 

0:00 – Intro
2:15 – How the AI field has changed 
7:43 – The five taboos Silicon Valley broke
12:11 – The ‘adulting’ of AI 
15:27 – How big of a deal might AI be?
17:52 – The hyperscalers won’t get to AGI
21:42 – Digital god and ‘synthetic slaves’
25:19 – X-Risk and the safety debate
32:53 – Brute-forcing intelligence
37:59 – Cracking AI in the enterprise
44:50 – The bubble
48:15 – AI is an orchestra

Get The Deep View — your daily source for in-depth, fact-based reporting on artificial intelligence — in your inbox every morning. Subscribe here! (https://www.thedeepview.co/subscribe)

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Shaolei Ren, an associate professor of Electrical and Computer Engineering at the University of California, Riverside, to break down his recent research into the water consumption, electricity consumption and public health impact of the data centers being used to power generative AI. 

Episode Links: 

• The water consumption of GenAI: https://arxiv.org/pdf/2304.03271
• The public health crisis of GenAI: https://arxiv.org/pdf/2412.06288
• Water consumption VS water use: https://www.wri.org/insights/whats-difference-between-water-use-and-water-consumption
• Pepsi Co’s water consumption: https://www.pepsico.com/our-impact/esg-topics-a-z/water#approach
• Google and Microsoft’s water consumption: https://www.thedeepview.co/p/google-emissions-are-spiking-due-to-increased-energy-demands-of-ai
• Elon Musk’s Memphis data center: https://www.thedeepview.co/p/the-public-health-crisis-of-artificial-intelligence

Outline: 

0:00 – Intro
1:27 – The water consumption of AI
7:30 – The difference between water ‘consumption’ and water ‘use’
16:15 – The impact of reasoning models 
18:03 – A solution to AI’s water problem
19:58 – The public health cost of AI 
27:55 – Addressing the problem
33:52 – The dichotomy of the AI industry
42:37 – A cost-benefit analysis
48:49 – Looking ahead

Get The Deep View — your daily source for in-depth, fact-based reporting on artificial intelligence — in your inbox every morning. Subscribe here!

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.

I sat down with Dr. Chris Bishop, a Microsoft technical fellow and the director of Microsoft Research AI for Science, to sink into the details of what AI is actually unlocking for science, and what kind of AI is doing it. 

Episode Links: 

• 5th paradigm of scientific discovery: https://cacm.acm.org/opinion/the-5th-paradigm-ai-driven-scientific-discovery/
• Microsoft Aurora: https://www.microsoft.com/en-us/research/blog/introducing-aurora-the-first-large-scale-foundation-model-of-the-atmosphere/
• The environmental cost of AI: https://www.thedeepview.co/p/the-public-health-crisis-of-artificial-intelligence
• MatterGen: https://www.thedeepview.co/p/report-ai-is-everywhere-already-even-if-we-don-t-know-it
• The dubious nature of AGI: https://www.thedeepview.co/p/the-nobel-prize-and-the-mainstreaming-of-ai-s-x-risk
  
  

Outline:

0:00 – Intro
2:13 – The importance of domain expertise in AI 
5:17 – The promise of AI for science
12:47 – Project Aurora and climate modeling 
15:27 – The cost-benefit analysis of AI 
18:43 – Weather prediction models VS ChatGPT
21:36 – AI to shield against engineering disasters
24:36 – How does Microsoft decide which applications to pursue
27:32 – Microsoft Research’s main areas of focus
33:24 – MatterGen and material generation
39:24 – How the wet lab is changing
42:19 – Is AGI a worthwhile pursuit for scientific advancement? 
 47:43 – Technological optimism and the way forward

Get The Deep View — your daily source for in-depth, fact-based reporting on artificial intelligence — in your inbox every morning. Subscribe here!

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Artificial intelligence is a complicated topic, bound by a number of complex threads — technical science, ethics, safety, regulation, neuroscience, psychology, philosophy, investment and — above all — humanity. On The Deep View: Conversations, Ian Krietzberg, host and Editor-in-Chief at The Deep View, breaks it all down, cutting through the hype to make clear what's important and why you should care.