Imagine your bank with a smarter, faster assistant - one that can answer your questions, streamline tasks, and even empower staff. Rohan, Shayne, and Rishi dive into the world of conversational AI for financial institutions.

They discuss:

- How Posh is revolutionizing customer service for credit unions and community banks with chatbots, voice assistants, and a knowledge assistant for employees.

- The evolution of AI, from early models to the powerful capabilities of GPT-3. This conversation explores the challenges of creating natural, human-like conversations while navigating regulations in finance.

- Copilot vs. Autopilot: Posh's unique approach that balances the efficiency of AI with the irreplaceable value of human interaction.

- Privacy and Security First: How Posh tackles these critical concerns in the financial sector, ensuring data protection and client trust.

Ram shares how he built Colaberry, a company that trains veterans for tech careers, combining social impact with a sustainable business model.

Rohan and Ram talk about how Colaberry leverages AI to empower job seekers and reshape industries. They also explore the future of work: how AI will change roles for engineers, salespeople, and everyone in between.

They further discuss:

- How to build a profitable business with a social mission

- The secret weapon for veteran career success (it's not what you think!)

- Why AI is the new "internet browser" for innovation

- How to stay relevant in a world powered by AI

- Why the human touch will always be crucial in sales

For all the small business owners out there - ever feel like your customers are ghosts in the wind? You hear them but struggle to manage their needs effectively while your team spends hours on dead-end leads, wasting precious time and resources.

Smith.ai is solving this problem, revolutionizing customer engagement for SMBs with the help of AI agents.

Aaron’s career path is anything but ordinary - from starting his career at Google during its growth phase to building a company acquired by The Home Depot. He then became CTO at Home Depot.

But what inspired him to tackle the challenges of small and medium businesses (SMBs)?

This episode dives deep into:

- The unique challenges of SMB customer engagement that can be solved with AI

- Why simply throwing “AI” at a problem can backfire (and what it takes to be effective)

- How Smith AI handles calls and qualify leads, so your team can focus on closing deals

- Advice from Aaron - how to navigate a fast-changing AI landscape (as an employee/business owner/vendor/customer)

Can AI outsmart every annoying noise on your calls?

Rohan and Davit discuss the motivations behind Krisp and the technical complexities of developing real-time noise suppression solutions. We explore the intricacies of AI model training, the importance of data privacy in audio processing, and how Krisp uses cutting-edge tech to make calls sound crystal clear.

Rohan and Michael discuss the future of cloud connectivity and how AI workloads will impact it.

Megaport boasts 60-second deployments, letting users tap into the power of the cloud at lightning speed.

But Megaport isn't just about speed. Rohan and Michael also talk about the strategic importance of connectivity in the AI era, specifically:

- The rise of multi-cloud: How companies use multiple cloud providers for optimal performance, and how Megaport helps them navigate this complex landscape.

- AI workloads and: Why seamless data access across platforms is critical for training powerful AI models, and how that means seamless cloud connectivity will be even more important in the future.

This episode explores the future of healthcare, where AI scribes like Freed take over the tedious task of charting notes.

Erez shares stories of how doctors have become significantly more efficient with Freed.

Rohan and Erez also explore, more broadly, the promise and the challenges surrounding AI’s adoption in medicine.

Rohan and Shayne chat with Yi to discuss AI innovation in customer service.

They also talk about:

- Domain-specific AI: where language models (LMs) are trained to understand specific industries and customer bases.

- Automating efficiency: how LMs can evaluate themselves, leading to more efficient improvement in customer interactions.

- AI limitations: challenges of using LM agents, and the issue of "hallucination" where LMs generate incorrect responses.

Will college degrees survive the incredible pace of skill shifts?

Rohan and David explore the future of learning in a world of shrinking skill lifespans.

David reveals a jaw-dropping stat: the average half-life of a skill (the time it takes for a skill to become half as valuable) has plummeted from 15 years a few decades ago to just 2 years - making skills obsolete in a flash. Lifelong learning is now an imperative, not just a nice to have.

Rohan and David also talk about:

- Whether college degrees are becoming a thing of the past or stepping stones to lifelong learning.

- “Jailbreaking” the traditional college degree and how to thrive in today’s digital age where technology outpaces classrooms.

- Strategies for thriving in a job market where adaptability is the new currency.

- What AI means for the skills of the future

- How Degreed acts as a personal learning GPS, guiding towards relevant skills and career pathways.

Can anyone code – without experience – in the age of AI?

Rahul sheds light on the inspiration behind Julius AI: a brainchild of passionate AI enthusiasts determined to empower everyone with the power to handle complex data analysis tasks regardless of coding experience.

Rohan and Rahul also talk about how Julius AI breaks down barriers, allowing anyone to leverage the power of Python for data analysis and visualization through instructions in plain English language.

The line between human creativity and machine intelligence is blurring. LLMs can now churn out poems, code, and even news articles, raising a burning question: who owns the words?

Rohan, Shayne, and Chris speak about the fast-changing AI x copyright landscape.

They discuss questions such as:

- Can using copyrighted material to train LLMs be considered fair use, or does it cross the line into infringement?

- When AI creates, who gets the credit?

- Can AI-generated data bypass copyright restrictions?

They also talk about the challenges of defining authorship in the age of AI, and how copyright law will need to keep up.