The Deep View: Conversations

Latest Episodes:

#19: Programmable plants - Brad Zamft Apr 22, 2025

Show notes

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.

#18: What Trump's tariffs mean for AI - Nada Sanders Apr 16, 2025

Show notes

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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#17: AI, compliance and utopia: Can tech actually make the world better? - Eric Sydell Apr 15, 2025

Show notes

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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#16: AI & Quantum: Sandbox AQ's technological revolution - Stefan Leichenauer Apr 08, 2025

Show notes

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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#15: Tools, not gods: IBM VP on AI, neuroscience and the nature of intelligence - David Cox Apr 01, 2025

Show notes

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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#14: The five taboos that Silicon Valley broke - Igor Jablokov Mar 25, 2025

Show notes

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

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#13: The climate impact of AI - Shaolei Ren Mar 18, 2025

Show notes

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

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#12: Director of Microsoft Research talks AI for Science - Chris Bishop Mar 11, 2025

Show notes

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

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#11: Why we need AI guardrails - Liran hason Mar 04, 2025

Show notes

I sat down with Liran Hason, the VP of AI at Coralogix, to talk AI guardrails: what they look like, how they work and why we need them.

Episode links:

AI has been around for decades: https://www.weforum.org/stories/2024/10/history-of-ai-artificial-intelligence/
Deterministic VS probabilistic AI: https://towardsdatascience.com/deterministic-vs-probabilistic-deep-learning-5325769dc758/
AI in the enterprise: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work
Air Canada lawsuit: https://www.forbes.com/sites/marisagarcia/2024/02/19/what-air-canada-lost-in-remarkable-lying-ai-chatbot-case/
Character AI sued: https://www.thedeepview.co/p/character-ai-sued-for-mental-health-decline-in-teenage-users-allegedly-encouraged-user-to-murder-his
AI trade runs out of steam: https://www.thedeepview.co/p/nvidia-beats-expectations-but-wall-street-wanted-more

Outline

0:00 – Intro

1:57 – AI guardrails … in 2019
4:51 – How consumers view guardrails in AI

11:03 – Tempered excitement in the enterprise

13:05 – Why do we need guardrails

17:59 – The role of regulation

24:07 – Why don’t developers guardrail their systems?

28:30 – Detecting hallucinations with guardrail models

34:11 – Guardrailing AGI

41:33 – Is the AI revolution slowing?

44:18 – How guardrails enable a positive outcome

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#10: The state of AI with IBM's Chief Scientist - Ruchir Puri Feb 25, 2025

Show notes

I sat down with Dr. Ruchir Puri, the chief scientist of IBM Research, for a wide-ranging discussion on the state of AI today. We talk about everything from AGI and X-risk to reliability in language models, the viability of agents and the pending economic impact of the technology.

Episode Links:

Artificial general intelligence: https://www.thedeepview.co/p/the-nobel-prize-and-the-mainstreaming-of-ai-s-x-risk
Microsoft and OpenAI’s AGI definition: https://www.theinformation.com/articles/microsoft-and-openais-secret-agi-definition?rc=sbfmgm
AI agents: https://www.thedeepview.co/p/prog-predictions-series-draft-ef9c081b34af8540
AI and job loss: https://www.thedeepview.co/p/chatgpt-s-impact-on-the-labor-market-openai-generative-ai-artificial-intelligence-job-loss-report-st
Technological revolution: https://www.thedeepview.co/p/south-korea-stakes-a-claim-in-the-ai-race
The Free Press article mentioned at 38:29: https://www.thefp.com/p/freddie-de-boer-is-ai-the-greatest-invention-or-overhyped

Outline:

0:00 – Intro
3:16 – The pace of improvement
8:56 – Unraveling ‘AGI’
14:47 – The inflection point of AI agents
21:54 – Thinking about reliability
26:14 – The economic implications of AI
32:37 – Is AI like the Industrial Revolution?
38:29 – How useful is AI, actually?
43:57 – Existential risk

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