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

In Season 2, Episode 2 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/

In this episode of The Deep View Conversations, we sit down with Merrill Lutsky, cofounder and CEO of Graphite — a company using artificial intelligence to transform how engineers write, review, and ship code.

What started as an internal tool to streamline software deployment has grown into something larger: a vision for how AI can augment, not replace, the craft of engineering — and reshape how teams collaborate at scale.

Merrill walks us through Graphite’s early pivots, the development of its AI reviewer Diamond, and how the company is rethinking the bottleneck that stands between building and shipping code.

We also go beyond the product to explore deeper questions:
Will coding become fully automated?
How do we balance speed and safety in an era of AI-written software?
And what does craftsmanship mean when machines start to create?