AI has created challenges around giving credit and compensation to original creators whose work is used to train AI models. This is a complex issue because AI often learns from vast amounts of data scraped from the internet, raising concerns about copyright infringement and fair use.New solutions are emerging, like those from ProRata.ai, that aim to track the origin of AI-generated content and share revenue with the original creators, ensuring they are properly compensated for their contributions.

What is the true purpose of AI? What should the ideal human-AI relationship look like?Do we want an AI co-pilot that collaborates on key decisions and helps execute important tasks, or do we prefer an AI minion that simply handles tasks we don’t want to do or aren’t good at doing?

Some of the very brightest minds in AI say we're hitting a wall with scaling laws. Others say we're not. Which is it? And for those building real-world applications, how does the answer impact your business?

The existing processes and systems for screening for talent are starting to not work in the new AI era. How are companies actually finding and retaining technical talent in 2024, and where are we headed in the future?

How companies are applying AI in real-world scenarios and the challenges of moving from experimentation to production.

You can make custom models through fine tuning, continued pretraining, or even training from scratch, but what does that get you vs using the best available models out of the box? How will that change with time as hardware improves and costs go down?

This will explore key metrics and milestones for a successful raise, offering tools and tactics to make it a smooth fundraise, so founders can get back to building their business.

We'll explore how startup founders can leverage Corporate Venture Capital (CVC) collaborations to accelerate growth, drive innovation, and unlock valuable resources.Learn actionable insights on building impactful connections with established tech leaders, navigating the unique benefits of CVC support, and positioning your company for long-term success through strategic alignment.

Beyond the co-pilots and chatbots, we are at the beginning of a grand opportunity to develop and deploy AI-native enterprise applications that could challenge the entrenched incumbents (as well as the trillions-dollar consulting industry) while changing how we run enterprises.We’ll explore opportunities, approaches, and the role of agentic AI.

Are the first AI IPOs coming soon? What can we expect before EOY and in 2025?This discussion will explore the real exit opportunity for AI companies—especially for those showing traction and moat—as well as which AI startups will likely IPO next year, plus those that may be better suited for acquisition.

GenAI is useful, and expensive. Some people are doing add-ons, some people are giving it away. Inference cost is going down, and models are getting commoditized – but reasoning models seem very token-hungry. What does this all mean for how products are priced and where value accrues?

Agents are a multi-trillion dollar opportunity – they do tasks humans can do and have the potential to eat into labor budgets.But how can we usher in agents responsibly? Which business models will work and which won't? Is the infrastructure ready to support it? Which industries will be affected first, and how are startups finding the right opportunities?Let's look forward to the agentic future and see what's around the corner.

How will AI-powered robotics actually change our workforce and daily life?From industrial automation to personal humanoids, let's bridge the vision vs. reality and explore what's possible today. We'll look beyond the hype and hone in on the opportunities and challenges of a robot-integrated society.

The past year has seen the emergence of increasingly powerful AI models that can reason, write code, and engage in sophisticated dialogue. But as we look toward 2025, it's becoming clear that raw model capability is only part of the story.The real breakthrough lies in how software architecture dramatically enhances these models' abilities — transforming impressive but sometimes unreliable AI systems into dependable, practical tools for business.

Serial entrepreneur Elias Torres shares how he's using AI agents to transform customer success, build his company, and leave behind the model of his earlier successes at Drift, Hubspot, and Performable.

Methods to monitor, improve accuracy and increase reliability. Discuss best practices, what's working, and what's not.

Today’s AI excels at pattern-matching, but building systems that can truly reason remains a fundamental challenge.We'll explore the technical approaches, architectural decisions, and user interfaces that are needed to create AI agents that reason — from reducing ambiguity to tackling novel problems and evaluating their outputs.