No Priors Ep. 109 | With Sarah and Elad

In this episode of No Priors, Sarah and Elad examine the current state of AI. They break down the recent dip in public markets, how tariffs could impact the tech industry, and where opportunities remain in large language models. They highlight the opportunities in more specialized models, new approaches to model development, and how the market is beginning to standardize with integrations like the Model Context Protocol (MCP). The episode ends with a look at early consumer AI applications and what types of expertise will matter most in the coming years. Show Notes: 0:00 Improvements in image gen 4:42 Public markets 8:08 Effects of tariffs on tech 9:42 Today’s large model market 11:34 Opportunities in specialized models 16:30 Research advances in model approaches 21:10 What expertise will matter? 24:30 Anthropic’s Model Context Protocol 26:30 Consumer applications

Sarah GuohostElad Gilhost

Apr 2, 202527mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

AI Image Breakthroughs, Macro Jitters, and the Maturing Model Ecosystem

Sarah and Elad discuss the latest leap in AI image and animation generation, framing it as another recurring “wow moment” on a steady curve of quality, control, and aesthetic sophistication. They argue that, despite market volatility, early-stage software startups—especially in AI—are largely insulated from macro concerns, with venture and model funding still deep and active. The conversation then shifts to the evolving foundation model landscape, including convergence on capabilities, unexplored vertical model opportunities, and the tension between one general model and many specialized ones. They close by describing a temporarily more stable AI stack—models, infra, orchestration, and emerging standards like MCP—before predicting the next wave of disruption and consumer products.

IDEAS WORTH REMEMBERING

5 ideas

AI image and animation quality is improving in recurring, dramatic waves.

From early GAN art and seven-fingered Midjourney images to today’s polished animations, each new generation resets user expectations and exposes how much more room there still is for quality and control.

Macro market turbulence matters far less to early-stage software startups than people think.

For small, viable startups—especially pure software plays—cycles in the NASDAQ, tariffs, and sentiment tend to be a shrug unless funding in venture dries up dramatically or you’re on the cusp of an IPO.

Foundation language models are converging on capability, making distribution and product differentiation crucial.

Benchmarks show many top models clustered in performance, so advantages will increasingly come from distribution, user experience, verticalization, and how well models are integrated into real workflows.

There is large, underexplored opportunity in vertical and scientific models beyond language.

Domains like physics, materials, robotics, and specialized healthcare models may hold significant economic and societal value, but they’re underfunded relative to their potential because they’re harder and less trendy than generic LLMs.

Data collection and generation are the core bottlenecks for non-text AI domains.

Unlike language and code, where data is abundant and digital, robotics, chemistry, and other physical domains require expensive, bespoke data generation (labs, robots, experiments), which favors companies that can build those engines.

WORDS WORTH SAVING

5 quotes

I feel like every year or two, there's this moment in the image gen world where people have a 'Wow, that's amazing' moment again.

— Elad

For day-to-day technology startups, particularly ones that are not doing hardware, it should really be of minimal actual day-to-day impact.

— Elad

Often, the interest level of people working in the industry to build models is divorced from the economic value of these models.

— Elad

Anytime you go into the physical world, it's always harder to generate data.

— Elad

It feels like a period of brief consolidation... I think we should enjoy the calm while it lasts for, you know, the next week or whatever it is.

— Elad

Advances in AI image generation, animation, and controllabilityImpact of macroeconomic conditions and tariffs on tech and startupsConvergence and competition in foundation language modelsVertical and domain-specific models (biology, physics, robotics, etc.)Data collection challenges for non-text, real-world AI applicationsModel architectures, trade-offs (speed vs. reasoning), and orchestrationEcosystem maturation: agents, MCP, infra standardization, and investment climate

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